Journal articles on the topic 'Best Smart Watches'

This article discusses the recent demand for silent alarms. If the device is kept close to a user’s body, such as on her\his wrist or in a back pocket, vibration is well suited for this type of alarm. The technology has been used for sometime in pagers, for example, and the field could someday be expanded to watches and a variety of medical equipment. The most common form of vibrating alert involves a motor that rotates an eccentric weight in an electromagnetic field. However, the smallest of these motors is still too large to fit in watches and other consumer products. Piezoceramic materials can produce motion by receiving electric potential across their polarized surfaces. Using finite-element analysis and optimization, engineers at Philips Corp. in Sunnyvale, Calif., have developed a miniature vibrator/piezo-bender that consumes only 8 milliamperes. In addition to optimization and actual shake tests, ergonomic research has been done to find the best way of improving the vibration performance of these silent alarms. Although the piezo-vibrator device shook strongly enough to get the wearer's attention in most environmental circumstances, that awareness improved greatly when vibrations were pulsed or interrupted.

With the development of sensor and communication technologies, the Internet of Things (IoT) subsystem is gradually becoming a crucial part in vehicles. It can effectively enhance functionalities of vehicles. However, new attack types are also emerging. For example, a driver with the smart key in their pocket can push the start button to start a car. At the same time, security issues in the push-to-start scenario are pervasive, such as smart key forgery. In this study, we propose a vehicle Passive Entry Passive Start (PEPS) system that adopts deep learning algorithms to recognize the driver using the electrocardiogram (ECG) signals measured on the driver’s smart watch. ECG signals are used for personal identification. Smart watches, serving as new smart keys of the PEPS system, can improve convenience and security. In the experiment, we consider commercial smart watches capable of sensing ECG signals. The sample rate and precision are typically lower than those of a 12-lead ECG used in hospitals. The experimental results show that Long Short-Term Memory (LSTM) models achieve the best accuracy score for identity recognition (91%) when a single ECG cycle is used. However, it takes at least 30 min for training. The training of a personalized Auto Encoder model takes only 5 min for each subject. When 15 continuous ECG cycles are sensed and used, this can achieve 100% identity accuracy. As the personalized Auto Encoder model is an unsupervised learning one-class recognizer, it can be trained using only the driver’s ECG signal. This will simplify the management of ECG recordings extremely, as well as the integration of the proposed technology into PEPS vehicles. A FIDO (Fast Identify Online)-like environment for the proposed PEPS system is discussed. Public key cryptography is adopted for communication between the smart watch and the PEPS car. The driver is first verified on the smart watch via local ECG biometric authentication, and then identified by the PEPS car. Phishing attacks, MITM (man in the middle) attacks, and replay attacks can be effectively prevented.

Over the years, Recommender systems have emerged as a means to provide relevant content to the users, be it in the field of entertainment, social-network, health, education, travel, food or tourism. Further,with the expeditious development of Big Data and Internet of Things (IoT), technology has successfully associated with our everyday life activities with smart healthcare being one. The global acceptance towards smart watches, wearable devices or wearable biosensors have paved the way for the evolution of novel applications for personalized eHealth and mHealth technologies. The data gathered by wearables can further be interpreted using Machine learning algorithms and shared with healthcare experts to provide suitable recommendations. In this work, we study the role of recommender systems in IoT and Cloud and vice-versa. Further, we have analyzed the performance of different machine learning techniques on SWELL dataset. Based on the results, it is observed that 2 Class Neural network performs the best with 98% accuracy.

As the technology revolving around IoT sensors develops in a rapid manner, the subsequent social networks that are essential for the growth of the system will be utilized as a means to filter the objects that are preferred by the consumers. The ultimate purpose of the system is to give the customers personalized recommendations based on their preference. Similarly, the location and orientation will also play a crucial role in identifying the preference of the customer is a more efficient manner. Almost all social networks make use of location information to provide better services to the users based on the research performed. Hence there is a need for developing a recommender system that is dependent on location. In this paper, we have incorporated a recommender system that makes use of recommender algorithm that is personalized to take into consideration the context of the user. The preference of the user is analysed with the help of IoT smart devices like the smart watches, Google home, smart phones, ipads etc. The user preferences are obtained from these devices and will enable the recommender system to gauge the best resources. The results based on evaluation are compared with that of the content-based recommender algorithm and collaborative filtering to enable the recommendation engine’s power.

The Internet of Medical Things (IoMT) is a huge, exciting new phenomenon that is changing the world of technology and innovating various industries, including healthcare. It has specific applications and changes in the medical world based on what can be done for clinical workflow models. The first and most fundamental thing that IoMT does in healthcare is to bring a flood of new data into medical processes. In this study, an efficient Internet of Medical Things based cancer detection model was proposed. In fact, for many, new fitness monitors and watches are one of the best examples on the Internet; these mobile, portable, wearable devices can record real-time heart rate, blood pressure, and eye movement of cancer patients. These details are sent to doctors or anywhere else. The proposed method leads to a kind of big data renaissance in the health service. The proposed model gets more accuracy while comparing with the existing models. This will help the doctors to analyze the patients’ health report and provides better treatment.

Technological advancements affect everyday life; they benefited our daily routines, habits, and activities. Underwater diving is one of the most interesting and attractive activities for tourists worldwide but could be risky and challenging. When paths are not clear, diving might take additional time and effort leading to some health problems. Thus, providing divers with proper direction information to surf underwater can be useful and helpful. Also, monitoring diverse health statuses and alerting them in case of any undesirable condition can increase their safety. Smart devices such as mobiles, watches, sensor devices, cellular networks along with the Internet of Things (IoT) can all provide location-based services. Such services can help in providing the best path for the divers and monitor their health status during diving. This paper proposes a new underwater routing approach, called Underwater Routing for Smart Diving “URSD”, which provides divers with routing information to visit underwater cultural or natural resources and monitors their health status during the diving period. The URSD approach was simulated and compared with the shortest path. Results showed that the URSD helped divers to route within paths that have a larger number of nodes, furthermore, it could enhance and improve divers experience and help them mitigate underwater risks.

Parkinson’s disease affects millions worldwide with a large rise in expected burden over the coming decades. More easily accessible tools and techniques to diagnose and monitor Parkinson’s disease can improve the quality of life of patients. With the advent of new wearable technologies such as smart rings and watches, this is within reach. However, it is unclear what method for these new technologies may provide the best opportunity to capture the patient-specific severity. This study investigates which locations on the hand can be used to capture and monitor maximal movement/tremor severity. Using a Leap Motion device and custom-made software the volume, velocity, acceleration, and frequency of Parkinson’s (n = 55, all right-handed, majority right-sided onset) patients’ hand locations (25 joints inclusive of all fingers/thumb and the wrist) were captured simultaneously. Distal locations of the right hand, i.e., the ends of fingers and the wrist showed significant trends (p < 0.05) towards having the largest movement velocities and accelerations. The right hand, compared with the left hand, showed significantly greater volumes, velocities, and accelerations (p < 0.01). Supplementary analysis showed that the volumes, acceleration, and velocities had significant correlations (p < 0.001) with clinical MDS-UPDRS scores, indicating the potential suitability of using these metrics for monitoring disease progression. Maximal movements at the distal hand and wrist area indicate that these locations are best suited to capture hand tremor movements and monitor Parkinson’s disease.

Abstract: Wearable electronics and its related technologie’s demand is growing tremendously in recent years .The major developments that accelerated this growth are decrement in the size of wireless devices, advancement of high-speed wireless networks, accessibility of ultra-compact, evolving battery technologies. Most of the Wearable electronic devices for example smart watches, wristbands, rings etc; we use various types of antennas to sense, fetch, and exchange data wirelessly. As one of the best antennas in many terms like compact size, flexibility and easy design is the micrpstrip patch antenna, therefore designing of the same is done. We are designing a microstrip patch antenna as a wearable antenna for its main usage in WBAN (Wideband Body Area Network). The software of CST studio suite which is a 3D electromagnetic analyzer is udes to design the required antenna, where the methodology of cascading of two antennas is taken into account for the design with required gain.

As image-based deep learning becomes pervasive on every device, from cell phones to smart watches, there is a growing need to develop methods that continually learn from data while minimizing memory footprint and power consumption. While memory replay techniques have shown exceptional promise for this task of continual learning, the best method for selecting which buffered images to replay is still an open question. In this paper, we specifically focus on the online class-incremental setting where a model needs to learn new classes continually from an online data stream. To this end, we contribute a novel Adversarial Shapley value scoring method that scores memory data samples according to their ability to preserve latent decision boundaries for previously observed classes (to maintain learning stability and avoid forgetting) while interfering with latent decision boundaries of current classes being learned (to encourage plasticity and optimal learning of new class boundaries). Overall, we observe that our proposed ASER method provides competitive or improved performance compared to state-of-the-art replay-based continual learning methods on a variety of datasets.

It is estimated 1 in 3 clinical trials utilize a wearable device to gather real-time participant data, including sleep habits, telemetry, and physical activity. While wearable technologies (including smart watches, USBs, and implantable devices) have been revolutionary in their ability to provide a higher precision and accuracy to data acquisition external to the research milieu, there is hesitancy among providers and participants alike given security concerns, perception of cyber-related threats, and meaning attributed to privacy issues. The purpose of this research is to define cyber-situational awareness (CSA) as it pertains to clinical trials, evaluate its current measurement, and describe best practices for research investigators and trial participants to enhance protections in the digital age. This paper reviews integrated elements of CSA within the process of informed consent when wearable devices are implemented for trial procedures. Evaluation of CSA as part of informed consent allows the research site to support the participant in knowledge gaps surrounding the technology while also providing feedback to the trial sponsor as to technology improvements to enhance usability and wearability of the device.

Biometric systems designed on wearable technology have substantial differences from traditional biometric systems. Due to their wearable nature, they generally capture noisier signals and can only be trained with signals belonging to the device user (biometric verification). In this article, we assess the feasibility of using low-cost wearable sensors—photoplethysmogram (PPG), electrocardiogram (ECG), accelerometer (ACC), and galvanic skin response (GSR)—for biometric verification. We present a prototype, built with low-cost wearable sensors, that was used to capture data from 25 subjects while seated (at resting state), walking, and seated (after a gentle stroll). We used this data to evaluate how the different combinations of signals affected the biometric verification process. Our results showed that the low-cost sensors currently being embedded in many fitness bands and smart-watches can be combined to enable biometric verification. We report and compare the results obtained by all tested configurations. Our best configuration, which uses ECG, PPG and GSR, obtained 0.99 area under the curve and 0.02 equal error rate with only 60 s of training data. We have made our dataset public so that our work can be compared with proposals developed by other researchers.

Action recognition is essential in security monitoring, home care, and behavior analysis. Traditional solutions usually leverage particular devices, such as smart watches, infrared/visible cameras, etc. These methods may narrow the application areas due to the risk of privacy leakage, high equipment cost, and over/under-exposure. Using wireless signals for motion recognition can effectively avoid the above problems. However, the motion recognition technology based on Wi-Fi signals currently has some defects, such as low resolution caused by narrow signal bandwidth, poor environmental adaptability caused by the multi-path effect, etc., which make it hard for commercial applications. To solve the above problems, we first propose and implement a position adaptive motion recognition method based on Wi-Fi feature enhancement, which is composed of an enhanced Wi-Fi features module and an enhanced convolution Transformer network. Meanwhile, we improve the generalization ability in the signal processing stage to avoid building an extremely complex model and reduce the demand for system hardware. To verify the generalization of the method, we implement real-world experiments using 9300 network cards and the PicoScenes software platform for data acquisition and processing. By contrast with the baseline method using original channel state information(CSI) data, the average accuracy of our algorithm is improved by 14% in different positions and over 16% in different orientations. Meanwhile, our method has best performance with an accuracy of 90.33% compared with the existing models on public datasets WiAR and WiDAR.

AbstractHeart rate variability (HRV) is a powerful measure to gain information on the activation of the central nervous system and is thus a strong indicator for the overall health and emotional state of a person. Currently, the gold standard for HRV analysis is the examination of R-peaks in electrocardiograms (ECG), which requires a placement of electrodes on the torso. This is often impracticable, especially for the use in daily routines or 24/7 measurements. Photoplethysmograms (PPG) are an alternative to ECG assessment and are easier to acquire, e.g. by using fitness trackers or smart watches. Nevertheless, PPG data is more susceptible to motion artifacts. Hence, goal of this work is to develop and evaluate an artificial neural network (ANN) approach to estimate the R-peak locations in complex PPG signals. Public data collections were used as benchmark to compare our ANN-based approach to state-of-the-art methods. Results show that ANNs can improve HRV estimation during motion. HRV estimations from baseline methods (decision-tree based and automatic multiscalebased peak detection) were compared with the best performing neural network (3L-GRU) using the TROIKA dataset with respect to reference parameters obtained from a manual selection of the peaks in ECG data. In most cases, the neural network based HRV estimation was closer to the reference HRV compared to baseline methods (lower μ and σ ) Also, σ is smaller for the best performing ANN approach across most HRV parameters. Inclusion of another PPG or acceleration channel did not affect HRV estimation. Although, the neural network learning approach outperforms conventional methods, the examined PPG-based HRV estimation has still accuracy limitations. Nonetheless, the proposed estimation approach opens up new directions for further improvement.

Background Multicomponent family interventions underline current best practice in childhood obesity treatment. Mobile health (mHealth) adjuncts that address eating and physical activity behaviors have shown promise in clinical studies. Objective This study aimed to describe process methods for applying an mHealth intervention to reduce the rate of eating and monitor physical activity among children with obesity. Methods The study protocol was designed to incorporate 2 mHealth apps as an adjunct to usual care treatment for obesity. Children and adolescents (aged 9-16 years) with obesity (BMI ≥98th centile) were recruited in person from a weight management service at a tertiary health care center in the Republic of Ireland. Eligible participants and their parents received information leaflets, and informed consent and assent were signed. Participants completed 2 weeks of baseline testing, including behavioral and quality of life questionnaires, anthropometry, rate of eating by Mandolean, and physical activity level using a smart watch and the myBigO smartphone app. Thereafter, participants were randomized to the (1) intervention (usual clinical care+Mandolean training to reduce the rate of eating) or (2) control (usual clinical care) groups. Gender and age group (9.0-12.9 years and 13.0-16.9 years) stratifications were applied. At the end of a 4-week treatment period, participants repeated the 2-week testing period. Process evaluation measures included recruitment, study retention, fidelity parameters, acceptability, and user satisfaction. Results A total of 20 participants were enrolled in the study. A web-based randomization system assigned 8 participants to the intervention group and 12 participants to the control group. Attrition rates were higher among the participants in the intervention group (5/8, 63%) than those in the control group (3/12, 25%). Intervention participants undertook a median of 1.0 training meal using Mandolean (25th centile 0, 75th centile 9.3), which represented 19.2% of planned intervention exposure. Only 50% (9/18) of participants with smart watches logged physical activity data. Significant differences in psychosocial profile were observed at baseline between the groups. The Child Behavior Checklist (CBCL) mean total score was 71.7 (SD 3.1) in the intervention group vs 57.6 (SD 6.6) in the control group, t-test P<.001, and also different among those who completed the planned protocol compared with those who withdrew early (CBCL mean total score 59.0, SD 9.3, vs 67.9, SD 5.6, respectively; t-test P=.04). Conclusions A high early attrition rate was a key barrier to full study implementation. Perceived task burden in combination with behavioral issues may have contributed to attrition. Low exposure to the experimental intervention was explained by poor acceptability of Mandolean as a home-based tool for treatment. Self-monitoring using myBigO and the smartwatch was acceptable among this cohort. Further technical and usability studies are needed to improve adherence in our patient group in the tertiary setting.

The health status of patients is recorded in various sources, such as medical records, portable devices (smart watches, fitness trackers, etc.), forming a characteristic current health status of patients. The goal of the study was the development of medical card software for the analysis of data from fitness bracelets. This will provide an opportunity to collect data for further use of cluster analysis and improvement of the functionality and accuracy of medical monitoring. The object of the study is the use of linear regression to analyze and predict heart rate based on data collected using fitness bracelets. In order to solve this problem, an information system was developed that uses linear regression to analyze the effect of parameters such as Very Active Distance, Fairly Active Minutes, and Calories on the heart rate (Value). Training and validation were performed on data from fitness bracelets. The results confirm the effectiveness of linear regression in predicting heart rate based on the parameters of fitness bracelets. The accuracy of the model was compared under the conditions of aggregation and without it, which allows us to draw conclusions about the optimal conditions for using linear regression for the analysis of fitness data. The study proves the adequacy of the obtained results according to the Student’s criterion. The calculated Student’s t test is 1.31, with the critical test ¾ 2.62. Which proves the adequacy of the developed model. The results of the study confirm that the linear regression model is an effective tool for individual monitoring and optimization of physical activity based on data from fitness bracelets. It is worth considering that the use of linear regression has its limitations and is not always the best choice for complex nonlinear dependencies. In such cases, other machine learning methods may need to be considered.

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose.............................................................................................................................................................................................. Since the valuation of a born-global speculative start-up (BGSS) has been a guessing game and there is no framework in the literature from ethical fashion smart wearable (EFSW) venture valuation perspective, this research explores to create a holistic model using multi-stage valuation method to valuate BGSS at its inception and investigates how ethical is ethical fashion? Background................................................................................................................................................................................................ The concept of ‘Born-Global’ firm was introduced into business theory during 1988. Nowadays, ventures start with a global vision from their inception to introduce products and services in overseas markets. Speculative investment has been a common practice to start-up expedition. Investors gamble on speculative start-ups. The inception phase of any start-up is the embryonic phase and is, therefore, more speculative than successive phases for additional investments. BGSS at its inception possess no operating history. Today fashion industry is one of the largest industries globally, growing leaps and bounds with valuation at 3 trillion U.S. dollars. The emerging smart fashion wearable market projected to cross US$ 30 billion during 2017. Fashion exists not only in garments but also other wearable such as the bracelet, watches, jewelry, and other accessories. Ethical fashion is all about betterment for the people and community at large. This paper identifies the relevant actors and their impact on the ethical aspects and status of the fashion industry. Methodology............................................................................................................................................................................................... The methodology used in this research both qualitative and quantitative approach. Since ethical fashion is a social phenomenon, the qualitative approach is appropriate to deal with various perspective analysis of ethical fashion using case study on four ethical fashion smart wearable ventures. The quantitative method calibrates the valuation of a BGSS at the inception stage using a noble pragmatic multi-stage valuation method because it provides the incentive to focus on achieving the best risk/cost ratio. Contribution.............................................................................................................................................................................................. This research bestows valuable insight using a noble multi-stage valuation method that has been proven successful based on author´s extensive practice to value BGSS at its inception contributing new knowledge to the literature. The application of informing system to frame the discussion on the inter-disciplinary domain of ethical fashion smart wearable creates awareness for fashion industry stakeholders and academic researchers. Findings.................................................................................................................................................................................................... The analysis shows that BGSS is a contemporary phenomenon since so many smart fashions wearable companies have gone through thought provoking and compelling stories to became successful in a highly competitive smart fashion wearable industry. BGSS concept is a brand-new perspective in the EFSW academic research. The findings of this research provide information to various stakeholders of the fashion industry and benefit to a global community at large with a more nuanced understanding of the changes and challenges of the emerging EFSW industry and the way to measure the valuation of a venture at its inception. Recommendations for Practitioners......................................................................................................................................................... This paper reveals nuance understanding for the practitioners in the BGSS valuation at its inception. Since all the traditional valuation methods have their drawbacks when applied to the inception stage of BGSS, this study recommends using multi-stage valuation method because it provides incentive for the best risk/cost ratio. Fashion brands (designers and other stakeholders) should abide by the ethical criteria to make a difference in the global community at large by reducing degradation of the environmental conditions. For the future of ethical fashion, ethical choices must be an available alternative to customers. Fashion companies need to embark upon design to not only be ethical but also stylish, therefore need to create trust by adopting transparency and integrity throughout the value chain. Fashion brand should take advantage of ethical fashion criteria to provide assurance to consumers with socio-cultural aspects in mind, to promote their fashion collections effectively. Recommendation for Researchers............................................................................................................................................................... More research work needs to be accomplished to have a clear analysis of the ethical fashion perspective to cover environmental, socio-cultural, fair trade, human rights, animal rights and other aspects. It is important to study the various stages of BGSS valuation from growth stage to initial public offering stage and beyond to bridge the gap between academic research and practitioners using the multi-stage valuation method. Impact on Society.......................................................................................................................................................................................... Since ethical fashion is of great significance for the contemporary society, raising awareness among various cultural communities globally to promote avantgarde ways regarding ethical fashion criteria, specifically to curb the degradation of the environment, stopping the cruelty on animals and protecting the human rights among consumers is paramount. Future Research............................................................................................................................................................................................ This study will bridge the gap between practice and academic research, scholars should embark upon creating a total addressable market (TAM) theory and empirical analysis studies because the total addressable market is the key and practical determinant of BGSS success. Ethical fashion academic research should be pursued beyond sustainability on smart wearable.

Today as diseases grow rapidly, the responsibilities of the health clinics in giving services to patients increase and patients have to be more monitored and controlled. Remote systems of monitoring patients result in reducing cost, ease of movement, and also persistent control of patients by their doctors, so that patient can be monitored without need to go to the clinic. Recent advances in the field of ubiquitous sciences as well as using smartphones have resulted in increasingly use of this devices in remote monitoring of patients. <br><br> The aim of this paper is to design and implement a ubiquitous health system using smartphones and sensors of smart-watches. This is accomplished through the information sent to the smartphone from the sensors of the watch, e.g. heart beat measurement sensor and ultraviolet ray. Then, this information is analyzed in the smartphone and some information based on the position of the patient and the path of him/her using GIS analyses as well as the information about the health level of the patient is sent to the doctor via SMS or phone call. Unnatural heart beats can be resulted in diseases such as Heart Failure and Arterial Fibrillation. With the approach adopted in this study, the patient or the doctor could be aware of these diseases at any time. The proposed approach is a low cost, without need to complex and resilient equipment, system in ubiquitous health that does not limit the movement of the patient.

Abstract Interventions utilizing consumer-grade wearable and mobile devices may support older adult health and wellness. However, rapid technology change and short industry product release cycles limit timely incorporation of these devices. We developed a novel, multi-stage process to rapidly move from within-team evaluations to lab- and field-based participants studies based on small-sample technology testing methods from Human-Computer Interaction. We present findings from a first-stage evaluation of the Amazfit Bips smart watch for potential use in studies with older adults as part of the methodology validation. A four-person research team conducted evaluations using: 1) a wearables framework for user experience and feature availability; and 2) the System Usability Scale (SUS). Evaluators wore the watch seven days straight from the box. User experience checklists indicated high usability. However, corresponding comments identified challenges with downloading the mobile app, pairing the watch and phone, navigating watch and mobile interfaces, and privacy controls. Average SUS score was 65.6 indicating marginal usability (C grade). While meeting study goals, divergence in usability perceptions suggest the process could be improved by completing each set of instruments separately for the watch and mobile app rather than all at once. Given failures in pairing, app navigation challenges, and small screen size, the Amazfit Bips may be best suited for studies among older adults with a high degree of technical proficiency. For those with little technical experience or high disease burden, training materials and dedicated training with support may be required. Future steps are lab- and field-based tests with older adult participants.

Pollution is a growing issue these days. It is necessary to analyze environment & keep it in check for a for best future as well as healthy living for all. Here we propose an Envi-ronment Monitoring System that permit us to watch & check live environment in espe-cially areas through Internet of Things (IOT). IoT supported a real time environmental monitoring system. It plays a crucial role in today’s world through a huge and pro-tract-ed system of sensor networks concerned to the environment & its parameters. This technique deals with monitoring important environmental conditions like temperature, humidity & CO level using the sensor & then this data is shipped to the web page. This information is often access from anyplace over the internet & then the sensor in-formation is presented as graphical statistics during mobile application. This paper explains & present the implementation & outcome of this environmental system uses the sensors for temperature, humidity, air quality & different environmental parameters of the surrounding space. This data is often used to take remote actions to regulate the conditions. Information is pushed to the distributed storage & android app get to the cloud & present the effect to the end users. The system employs a Node MCU, DHT-11 sensor, MQl35 sensor, which transmits data to WEBPAGE. An Android application is made which accesses the cloud data and displays results to the end users. The sensors interact with microcontroller which processes this information & transmit it over internet. This system is best method for any use in monitoring the environment and handling it because everything is controlled automatically through all the time of the process. The results say everything about the application of this system across different field where it was controlled precisely and effectively which further explains that this system easily makes our work easier because of this automatic monitoring system worries about other unexpected climate issues for world.

Background An estimated 60%-90% of patients with cancer experience moderate to severe pain. Poorly managed cancer pain negatively affects the quality of life for both patients and their family caregivers and can be a particularly challenging symptom to manage at home. Mobile and wireless technology (“Smart Health”) has significant potential to support patients with cancer and their family caregivers and empower them to safely and effectively manage cancer pain. Objective This study will deploy a package of sensing technologies, known as Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), and evaluate its feasibility and acceptability among patients with cancer-family caregiver dyads. Our primary aims are to explore the ability of BESI-C to reliably measure and describe variables relevant to cancer pain in the home setting and to better understand the dyadic effect of pain between patients and family caregivers. A secondary objective is to explore how to best share collected data among key stakeholders (patients, caregivers, and health care providers). Methods This descriptive two-year pilot study will include dyads of patients with advanced cancer and their primary family caregivers recruited from an academic medical center outpatient palliative care clinic. Physiological (eg, heart rate, activity) and room-level environmental variables (ambient temperature, humidity, barometric pressure, light, and noise) will be continuously monitored and collected. Behavioral and experiential variables will be actively collected when the caregiver or patient interacts with the custom BESI-C app on their respective smart watch to mark and describe pain events and answer brief, daily ecological momentary assessment surveys. Preliminary analysis will explore the ability of the sensing modalities to infer and detect pain events. Feasibility will be assessed by logistic barriers related to in-home deployment, technical failures related to data capture and fidelity, smart watch wearability issues, and patient recruitment and attrition rates. Acceptability will be measured by dyad perceptions and receptivity to BESI-C through a brief, structured interview and surveys conducted at deployment completion. We will also review summaries of dyad data with participants and health care providers to seek their input regarding data display and content. Results Recruitment began in July 2019 and is in progress. We anticipate the preliminary results to be available by summer 2021. Conclusions BESI-C has significant potential to monitor and predict pain while concurrently enhancing communication, self-efficacy, safety, and quality of life for patients and family caregivers coping with serious illness such as cancer. This exploratory research offers a novel approach to deliver personalized symptom management strategies, improve patient and caregiver outcomes, and reduce disparities in access to pain management and palliative care services. International Registered Report Identifier (IRRID) DERR1-10.2196/16178

Purpose: Given the growth in the use of wearable measuring technology, this study aimed to investigate the frequency of writing about wearable monitoring devices in the field of sports sciences and sports-related health professions during the years affected by the COVID-19 pandemic (2020 to 2022). The goal was to observe the number of studies right before the quarantine and during the first years of pandemic. Methodology: A systematic literature analysis was performed in the Web of Science Core Collection (WoS CC) and Scopus databases in March 2023. The filters used in the search were the following: original scientific papers in the English language and open access. The research field was sports sciences in the past three years (2020–2022) in the Wos CC, and health professions and medicine in Scopus. Results: The initial search resulted in 54 studies in the WoS, 16 of which were included in a detailed qualitative analysis, and 297 studies in Scopus with 19 of them analyzed (35 altogether). The keywords used were “fitness watch” (sport watch, smartwatch), “smart shoes”, “smart clothing”, “smart ring”, “smart belt”, and “smart glasses”. In the past three years, there has been a steady increase in the number of studies using smart monitoring devices to measure their data (nine in 2020, nine in 2021, and seventeen in 2022). Results showed that the most used device is a smartwatch, while the most carried out studies were about physical activity and daily activities of living. Furthermore, there are more studies about measuring devices being used as testing equipment than about device performance in general. Conclusions: This study summarizes various research conducted in the field of sports with the use of wearable measuring devices to determine the frequency of use of such devices in sport studies.

The study purpose was to assess the reliability and validity of Polar V800 smart watch in measuring various cricket-specific movements. Materials and methods. Only one trained male volunteer was selected to perform all the cricket specific movements to minimize individual error and eliminate between-subject variability. Polar V800 obtained distances were compared with real field markings. Results. Split-half Reliability Statistical method has been used and 'r' score for the measurements taken has been found to be 0.93. 95% confidence intervals also express a good reliability score. The criterion validity method was used to determine the validity of the dataset. The Pearson correlations (r) have been found ranging from 0.86 to 0.99. Predicted best fit line of linear regression has been found as y = 0.9722 X + 0.0046 (where y = observed value, X = real field distance). One way ANOVA followed by Tukey’s post hoc test on observed 10m sprint, 20m sprint and run-a-three movements show maximum significant difference with other cricket-specific movements. The mean percentage of bias for all cricket-specific movements has been found to be -2.20 ± 13.17. Conclusions. The study reveals that Polar V800 smart watch has an acceptable accuracy, reliability, and validity for measuring various cricket specific movements with certain limitations.

The fast growth of cities and the resulting rise in traffic have made it necessary to create effective parking control systems. This paper talks about how to build and set up an Internet of Things (IoT)-enabled smart parking system. IoT technology is used in the suggested system to solve problems with current parking systems, like wasteful use of space, traffic jams, and damage to the environment. A detailed mathematical model is created to find the best way to assign parking spaces, cut down on the time it takes to look for open spots, and improve the overall user experience. The system design combines different Internet of Things (IoT) parts, like sensors, motors, and communication units, so parking places can be managed and watched in real time. The math model includes methods for allocating parking spots dynamically based on data from IoT sensors gathered in real time. The goal of this model is to guess where parking spots will be available, make the best use of those places, and cut down on the time people spend looking for parking. The technology also uses machine learning to look at old data and get better at making predictions over time. Details about how to implement are talked about in depth, such as the hardware setup, transmission methods, and program parts. A lot of models and real-life tests in a city are used to judge the system's success. The results show big changes in how parking spaces are used, less traffic, and lower pollution, all of which make cities more sustainable. The suggested smart parking system that uses the Internet of Things (IoT) is a cost-effective and scalable answer to today's parking problems. More work will be done in the future to improve the system's abilities using advanced machine learning techniques and to spread its use to more cities. This study shows that IoT technology has the ability to change the way cities work and make life better in smart cities.

Every day, millions of people logon to the Internet to view their favorite TV show on Netflix, or similar streaming services, or to watch the latest viral video on YouTube. Two things are paramount, 1) that they receive the best streaming quality available, and 2) the video starts to play as quickly as possible. There is nothing worse than a video that stops and starts, takes forever to view or constantly changes between viewable qualities (resolutions). Due to our limited download speeds (bandwidth), in most houses it is not uncommon to hear “Stop downloading, I’m trying to watch something on Netflix”. When we couple this rise in online streaming with the growing number of portable devices (smart phones, tablets, laptops) we see an ever-increasing demand for high-definition online videos while on the move. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to ...

BACKGROUND: Manual interpretation of single-lead ECGs (SL-ECGs) is often required to confirm a diagnosis of atrial fibrillation. However accuracy in detecting atrial fibrillation via SL-ECGs may vary according to clinical expertise and choice of smart device. AIMS: To compare the accuracy of cardiologists, internal medicine residents and medical students in detecting atrial fibrillation via SL-ECGs from five different smart devices (Apple Watch, Fitbit Sense, KardiaMobile, Samsung Galaxy Watch, Withings ScanWatch). Participants were also asked to assess the quality and readability of SL-ECGs. METHODS: In this prospective study (BaselWearableStudy, NCT04809922), electronic invitations to participate in an online survey were sent to physicians at major Swiss hospitals and to medical students at Swiss universities. Participants were asked to classify up to 50 SL-ECGs (from ten patients and five devices) into three categories: sinus rhythm, atrial fibrillation or inconclusive. This classification was compared to the diagnosis via a near-simultaneous 12-lead ECG recording interpreted by two independent cardiologists. In addition, participants were asked their preference of each manufacturer’s SL-ECG. RESULTS: Overall, 450 participants interpreted 10,865 SL-ECGs. Sensitivity and specificity for the detection of atrial fibrillation via SL-ECG were 72% and 92% for cardiologists, 68% and 86% for internal medicine residents, 54% and 65% for medical students in year 4–6 and 44% and 58% for medical students in year 1–3; p <0.001. Participants who stated prior experience in interpreting SL-ECGs demonstrated a sensitivity and specificity of 63% and 81% compared to a sensitivity and specificity of 54% and 67% for participants with no prior experience in interpreting SL-ECGs (p <0.001). Of all participants, 107 interpreted all 50 SL-ECGs. Diagnostic accuracy for the first five interpreted SL-ECGs was 60% (IQR 40–80%) and diagnostic accuracy for the last five interpreted SL-ECGs was 80% (IQR 60–90%); p <0.001. No significant difference in the accuracy of atrial fibrillation detection was seen between the five smart devices; p = 0.33. SL-ECGs from the Apple Watch were considered as having the best quality and readability by 203 (45%) and 226 (50%) participants, respectively. CONCLUSION: SL-ECGs can be challenging to interpret. Accuracy in correctly identifying atrial fibrillation depends on clinical expertise, while the choice of smart device seems to have no impact.

This research is based on the phenomenon of selling goods with live broadcasts on social media since the Covid-19 pandemic to know several factors that influence purchase intentions on live streaming shopping on the sale of used goods in Batam City. The study was conducted by collecting 330 samples obtained by distributing questionnaires to people who had watched live broadcasts of used clothes on social media. The data is processed using Smart PLS version 26. The results of this study indicate that Social Interaction does not affect Purchase Intention, followed by Social Interaction which affects Trust. Consumer involvement has a significant effect on trust, followed by perceived economic benefits which have a significant effect on trust, subjective norms and perceived prices have a significant effect on purchase intention. Meanwhile, Subjective Norm does not affect Purchase Intention. For the moderating effect, trust has a significant effect on purchase intention. Through this research, it is hoped that it can provide a view to the public that selling through live broadcasts is the best marketing system

‘Continuous effort, not strength or intelligence, is the key to understanding our potential.’ Margaret J Wheatley The focus of any academic or research author is to share his or her findings, and to gain respect and reward for publishing. The ideal journal is one that not only publishes an article quickly but also helps the author to improve the article before publication through peer review, selects only the best research so that the author’s article lies alongside other high quality articles, and provides maximum (and long-term) visibility and access to the article. Unfortunately, in the real world, authors need to make tradeoffs between high quality journals, those that work quickly, those that are willing to accept the article and those that provide the best access. Into this mix has come the potential of open access as a means of increasing visibility: journals publish the article without a subscription barrier so anyone, anywhere, can read the article. However, the growth of open access (pushed by institutions, grant bodies and governments as a means of improving human health and knowledge) has come with some unforeseen consequences. In this article, Jeffrey Beall discusses one recent phenomenon that has arisen from the open access movement: that of ‘predatory publishers’. These are individuals or companies that use the open access financial system (author pays, rather than library subscribes) to defraud authors and readers by promising reputable publishing platforms but delivering nothing of the sort. They frequently have imaginary editorial boards, do not operate any peer review or quality control, are unclear about payment requirements and opaque about ownership or location, include plagiarised content and publish whatever somebody will pay them to publish. Predatory publishers generally make false promises to authors and behave unethically. They also undermine the scholarly information and publishing environment with a deluge of poor quality, unchecked and invalidated articles often published on temporary sites, thus losing the scholarly record. Jeffrey Beall, a librarian in Denver, US, has watched the rise of such fraudulent practice, and manages a blog site that names publishers and journals that he has identified as predatory. While Beall’s lists can provide librarians and knowledgeable authors with information on which journals and publishers to be cautious about, several legitimate publishers, library groups and others have joined forces to educate and inform authors in what to look for when selecting journals to publish in (or read). This initiative, called Think. Check. Submit. (http://thinkchecksubmit.org/), was launched in the latter half of 2015 and hopes to raise awareness of disreputable journals while clearly separating them from valid, high quality, open access journals (of which there are many). PIPPA SMART Guest Editor

Heart rate variability (HRV) represents the activity and balance of the autonomic nervous system and its capability to react to internal and external stimuli. As a measure of general body homeostasis, HRV is linked to lifestyle factors and it is associated with morbidity and mortality. It is easily accessible by heart rate monitoring and gains interest in the era of smart watches and self-monitoring. In this review, we summarize effects of weight loss, training, and nutrition on HRV with a special focus on obesity. Besides weight reduction, effects of physical activity and dietary intervention can be monitored by parameters of HRV, including its time and frequency domain components. In the future, monitoring of HRV should be included in any weight reduction program as it provides an additional tool to analyze the effect of body weight on general health and homeostasis. HRV parameters could, for example, be monitored easily by implementation of an electrocardiogram (ECG) every two to four weeks during weight reduction period. Indices presumibly showing beneficial changes could be a reduction in heart rate and the number of premature ventricular complexes as well as an increase in standard deviation of normal-to-normal beat intervals (SDNN), just to name some.

In the event of a kidnapping or a medical emergency, a person is often incapacitated to be able to call for help. And it’s usually too late before the first responders arrive on-scene. Currently, a vast array of ‘safety’ devices available in the market are often far too rudimentary such as double tapping the power button that isn’t very practical, or an app on a smart watch that is a huge investment in the first place. The Smart Band aims to eliminate the need for a physical trigger by the person who finds himself in dangerous situations like kidnapping, front-facing some wild animal, heart attack, etc., and rather senses the heartbeat. The Smart Band is designed as a personalized wearable device, wherein the user heart beat rate is collected and trained using machine learning algorithm, which triggers the alert system automatically when the event is identified. Hence the accuracy of assessing emergency situation will be high and false rate will be reduced. As soon as the event is detected, the band relays GPS coordinates to first responders and emergency contacts, which will be sent via the Network Carrier (SIM card module) directly from the band, not relying on a mobile phone, which is usually out of reach during such emergency situations. In essence, the Smart Band consists of a GPS tracker, a heartbeat sensor, a Network module, and a Bluetooth module, all existing technologies which have been mass produced to an extent that the end product can be made affordable, and in huge quantities as well. On further development the smart band can be customized to a finely wearable jewel which can serve the purpose autonomously.

ASD is characterised by severe and violent behavioural issues that are referred to as "meltdowns (upset) or tantrums (collapse)" and can include aggression, hyperactivity, intolerance, unpredictability and self-injury. This research work intends to develop and implement a non-invasive real-time Upset or Collapse Detection System (UCDS) for people with ASD. With a certain model of smart watch, the non-invasive biological indications such as Pulse Rate (PR), Skin Temperature (ST), and Galvanic Skin Reaction (GSR) can be artificially captured. In order to create the UCDS, deep learning algorithms like CNN, LSTM, and the hybrid of CNN-LSTM are given the physiological signals that are captured to a server. The deep learning algorithm could recognise aberrant upset or collapse states from real-time physiological signs after being trained. Deep learning algorithms including CNN, LSTM, and CNN-LSTM are used to train and test the proposed UCDS system, and it is discovered that hybrid CNN-LSTM beat them all with an average training and testing accuracy of 96% and a low mean absolute error (MAE) of 0.10 for training and 0.04 for testing. Furthermore, the suggested UCDS system is supported by 93% of the ASD caretakers.

Background Inadequately managed pain is a serious problem for patients with cancer and those who care for them. Smart health systems can help with remote symptom monitoring and management, but they must be designed with meaningful end-user input. Objective This study aims to understand the experience of managing cancer pain at home from the perspective of both patients and family caregivers to inform design of the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) smart health system. Methods This was a descriptive pilot study using a multimethod approach. Dyads of patients with cancer and difficult pain and their primary family caregivers were recruited from an outpatient oncology clinic. The participant interviews consisted of (1) open-ended questions to explore the overall experience of cancer pain at home, (2) ranking of variables on a Likert-type scale (0, no impact; 5, most impact) that may influence cancer pain at home, and (3) feedback regarding BESI-C system prototypes. Qualitative data were analyzed using a descriptive approach to identity patterns and key themes. Quantitative data were analyzed using SPSS; basic descriptive statistics and independent sample t tests were run. Results Our sample (n=22; 10 patient-caregiver dyads and 2 patients) uniformly described the experience of managing cancer pain at home as stressful and difficult. Key themes included (1) unpredictability of pain episodes; (2) impact of pain on daily life, especially the negative impact on sleep, activity, and social interactions; and (3) concerns regarding medications. Overall, taking pain medication was rated as the category with the highest impact on a patient’s pain (=4.79), followed by the categories of wellness (=3.60; sleep quality and quantity, physical activity, mood and oral intake) and interaction (=2.69; busyness of home, social or interpersonal interactions, physical closeness or proximity to others, and emotional closeness and connection to others). The category related to environmental factors (temperature, humidity, noise, and light) was rated with the lowest overall impact (=2.51). Patients and family caregivers expressed receptivity to the concept of BESI-C and reported a preference for using a wearable sensor (smart watch) to capture data related to the abrupt onset of difficult cancer pain. Conclusions Smart health systems to support cancer pain management should (1) account for the experience of both the patient and the caregiver, (2) prioritize passive monitoring of physiological and environmental variables to reduce burden, and (3) include functionality that can monitor and track medication intake and efficacy; wellness variables, such as sleep quality and quantity, physical activity, mood, and oral intake; and levels of social interaction and engagement. Systems must consider privacy and data sharing concerns and incorporate feasible strategies to capture and characterize rapid-onset symptoms.

Summary Objectives: Wearable systems can be broadly defined as mobile electronic devices that can be unobtrusively embedded in the user’s outfit as part of the clothing or an accessory. In particular, unlike conventional mobile systems, they can be operational and accessed without or with very little hindrance to user activity. To this end they are able to model and recognize user activity, state, and the surrounding situation: a property, referred to as context sensitivity. Wearable systems range from micro sensors seamlessly integrated in textiles through consumer electronics embedded in fashionable clothes and computerized watches to belt worn PCs with a head mounted display. The wearable computing concept is part of a broader framework of ubiquitous computing that aims at invisibly enhancing our environment with smart electronic devices.The goal of the paper is to provide a broad overview of wearable technology and its implications for health related applications. Methods: We begin by summarizing the vision behind wearable computing. We then describe a framework for wearable computing architecture and the main technological aspects. Finally we show how specific properties of wearable systems can be used in different health related application domains. Results: Wearable computing is an emerging concept building upon the success of today’s mobile computing and communication devices. Due to rapid technological progress it is currently making a transition from a pure research stage to practical applications. Many of those applications are in health related domains, in particular, health monitoring, mobile treatment and nursing. Conclusions: Within the next couple of years wearable systems and more general ubiquitous computing will introduce profound changes and new application types to health related systems. In particular they will prove useful in improving the quality and reducing the cost of caring for the aging population.

OBJECTIVES/GOALS: Research objectives include prototyping a mobile phone application that allows physicians to monitor CD19-directed CAR T-cell therapy patients remotely after discharge. This app will also enable standardized data collection across different centers that provide CAR-T cell therapy and allow for the harmonization of follow-up protocols. METHODS/STUDY POPULATION: Literature review and semi-structured interviews with patients, clinical coordinators, and other experts in the field will be used to determine what parameters must be included in the mobile application prototype to effectively monitor the side effects of CD19-directed CAR T-cell therapy. The mobile phone application will be designed using process mapping to integrate data from self-reporting and wearable technologies, including the Garmin smart watch. Figma will then be used to develop new screens based on an existing patient monitoring app for Allogeneic Stem Cell Transplant follow-up. Finally, a preliminary feasibility study will be conducted to collect feedback on the app prototype from CAR T-cell therapy patients, providers, and stakeholders. RESULTS/ANTICIPATED RESULTS: The anticipated results of this study include an app prototype that will include the functionalities required to monitor patients for adverse effects of CD19-directed CAR T-cell therapy. This will include the parameters that will be recorded or measured using a combination of self-reporting, a reliable body temperature sensor, and the Garmin watch which monitors basic vitals, activity, and sleep. Additional parameters may be added during the stakeholder co-design process. The app prototype will include a physician interface where doctors can monitor their patients and will be alerted if they require further physician assessment. It is expected that the app will provide standardized monitoring of patients when they are discharged from the hospital after receiving CAR T-cell therapy. DISCUSSION/SIGNIFICANCE: This app will allow physicians to monitor patients for general follow-up and adverse effects, including cytokine release syndrome and neurotoxicity. Future studies may utilize this app to develop best practices for harmonizing CAR-T follow-up protocols across Canada.

Abstract Introduction The Photoplesthymogram (PPG) raw waveform is the basis for both the pulse rate and oximetry during polysomnography (PSG) and Home Sleep Apnea Tests (HSAT). The PPG has also recently become ubiquitous as a basis of continuous measurement for the most widely adopted consumer sleep technologies, particularly smart watches. In this study, we clinically validate AI performance for interoperable, PPG-based epoch-by-epoch Sleep-Wake staging (PPG-SW), Total Sleep Time (PPG-TST), and Respiratory Rate (PPG-RR), when compared to 1) PSG-based panel scoring by technologists (RPSGTs) and 2) PSG-based AI scoring (EEG-SW, EEG-TST, Effort Belt-RR). Methods We applied stratified random sampling with proportionate allocation to a database of N&gt;10,000 retrospective PSGs. We controlled for: 1) Obstructive sleep apnea severity, 2) Sleepiness, 3) Medical diagnoses including sleep, psychiatric, neurologic, neurodevelopmental, cardiac, pulmonary, metabolic disorders, 4) Medications including benzodiazepines, antidepressants, stimulants, opiates, sedative-hypnotics, 5) Demographics including sex, age, BMI, weight, and height, to establish representative adult (N=100) PSG studies from which PPG samples were obtained. Double blinded scoring was prospectively collected for each PSG by 3 experienced RPSGTs randomized from a pool of 6 scorers. RR was established by mode when two scorers agreed on RR value and median otherwise. Results AI EEG-SW demonstrated 96%/94%/95% Sensitivity/Specificity/Accuracy compared to 2/3 majority PSG staging, and AI PPG-SW demonstrated 90%/89%/90% Sensitivity/Specificity/Accuracy compared to the same PSG panel. AI EEG-TST achieved a Pearson Correlation Coefficient (R-value) of 0.968 and AI PPG-TST achieved 0.873 R-value compared to 2/3 majority PSG-TST. When compared to the RR panel consensus in N=282 one-minute RR scoring epochs of PSG, AI Effort Belt-RR performance was &lt;= 2 breaths-per-minute (brpm) in 93.6% of epochs with an average difference of 0.992 brpm, and AI PPG-RR performance was &lt;= 2 brpm in 92.2% of epochs with an average difference of 0.996 brpm. Conclusion The study shows interoperable AI analysis performs robustly in evaluating PPG-based epoch-by-epoch sleep-wake stages, total sleep time, and respiratory rate, demonstrating state-of-art accuracy when compared to a prospective, double-blinded PSG scoring panel. This work has implications for consumer sleep technology, HSAT accuracy, inpatient sleep monitoring, and may support the growth of HSATs by increasing total sleep time accuracy and reliability. Support (if any):

Machine learning is a rapidly growing field with widespread application in various industries, including healthcare. In recent years, significant advancements in machine learning have enhanced our understanding of data analytics and prediction models in analyzing physiological data, such as blood oxygen levels, heart rate, and blood pressure. This paper focuses on physical activity in adolescence during the pandemic period. The study showed that going outside for a short walk can increase blood oxygen levels. Furthermore, the consumption of certain foods can also raise oxygen saturation levels. Maintaining a high blood oxygen level during exercise can improve athletic performance and reduce injury risk. However, during exercise, the blood oxygen level tends to decrease as the heart rate increases to supply more oxygen to the body. When the blood oxygen level drops too low during exercise, it can lead to fatigue, shortness of breath, and even fainting. By tracking heartbeats, blood oxygen levels, and other physiological parameters during exercise with the YAMAY Smart Watch wearable device, individuals can gain insights into their body's response to physical activity and adjust their exercise routine accordingly. After collecting data using wearable devices and mobile apps, machine learning algorithms can be trained to predict changes in physiological parameters of post-activity, providing valuable insights into the effectiveness of different exercises and identifying potential health risks. Our study used supervised machine learning classification algorithms to predict the expected data with the target data. We used K-fold cross-validation techniques to split the dataset into training, validation, and test sets for the supervised machine learning classification algorithms. After testing each of the machine learning models (K-Nearest Neighbor (KNN), Naïve Bayes, and Random Forest), it was found that the Random Forest had the best prediction accuracy of 98.75%. On the other hand, KNN had a poor prediction accuracy, lower than 41.1%. Therefore, the Random Forest model can accurately predict the effect of change on the oxygen saturation level during exercise.

Febriartha Dwi Wahyu Safitra1, Ni Kadek Yuni Utami 2, Ni Wayan Ardiarani Utami3 1,2,2Sekolah Tinggi Desain Bali, Denpasar,Bali - Indonesia e-mail: febrisafitra97@gmail.com1 A B S T R A C T Movie theater is one of public entertainment designed to give a good quality audio-visual and services to people who would like to spend their time to watch a movie. The purpose of this redesign is to increasing the quality of services provided into movie theater, also to attracting public interest of Indonesian movie world by serving a good facilities and accommodation of watching movie activities. The process of collecting information data by doing an observation to site location at the movie theater, and do an interviewed with one of the staff, also one of customer at the movie theater. The result of those observation will be analyzed using qualitative analyses method and glass box method by listing what people’s demand as for services and facilities should be provide at movie theater, to figuring what rooms that needed, as well as theme and concept for the design. The conclusion is Futuristic Entertainment applied as theme and concept at theater’s interior redesign has a hope will become the new face of the Movie Theater as of facing high business competition among movie theater industry also to calibrate the Industry 4.0 era where internet based at most of life aspect, nowadays. Key words : movie theater, movie, watching, services, public, Futuristic, Entertainment, redesign, interior A B S T R A K Bioskop merupakan salah satu tempat sarana hiburan untuk menonton film yang dirancang memberikan kualitas audio-visual yang baik dan kegiatan pelayanan dalam meningkatkan kenyamanan dalam menonton film. Tujuan dari redesain interior ini untuk dapat meningkatkan kualitas pelayanan pada bioskop, serta meningkatkan minat masyarakat untuk menghargai perfilman di Indonesia dengan memberikan fasilitas dan sarana yang baik dalam kegiatan menonton film. Proses pengumpulan data dilakukan dengan observasi ke lokasi site bioskop tersebut dan melakukan wawancara pada salah satu pegawai bioskop, serta salah satu pengunjung dari bioskop. Hasil dari observasi tersebut kemudian di analisa menggunakan metode analisa kualitatif dan metode desain glass box, dengan mendata pelayanan yang harus disediakan pada area bioskop, untuk mengetahui kebutuhan ruang, serta tema dan konsep dalam redesain interior. Simpulan redesain pada interior bioskop menggunakan tema dan konsep Futuristic Entertainment, yang mana dari tema dan konsep tersebut akan memberikan wajah baru untuk menghadapi persaingan bisnis bioskop yang semakin tinggi dan sekaligus menyesuaikan era Industry 4.0 sekarang, dimana Internet based pada hampir segala aspek kehidupan. Kata Kunci: bioskop, film, menonton, pelayanan, masyarakat, Futuristic, Entertainment, redesain, interior. PENDAHULUAN Di digital era seperti sekarang ini, menonton film menjadi salah satu pilihan sarana hiburan bagi masyarakat untuk melepas penat maupun kebosanan akan rutinitas sehari-hari. Cerita-cerita dalam film dapat diadaptasi dari novel, dokumentasi ilmiah, autobiografi, sejarah dari sebuah peristiwa, maupun dari kisah nyata seseorang yang menarik untuk diangkat ke dalam sebuah film, sehingga sebuah film pun juga dapat menjadi media visual informasi bagi masyarakat luas. Sekarang ini bioskop sebagai tempat pemutaran film-film sudah banyak tersebar di seluruh wilayah Indonesia. Hal ini dilihat dari jumlah layar bioskop yang semakin bertambah, sekaligus berpengaruh pada pertambahan jumlah penonton Indonesia. Menurut data GPBSI (Gabungan Pengusaha Bioskop Indonesia), jumlah layar bioskop di Indonesia terus bertambah dalam dekade terakhir, pada tahun 2008 tercatat ada 574 layar, kemudian terus bertambah menjadi 1518 layar pada 2017, bertambah lagi menjadi 1774 pada 2018, dan hingga pada per 13 Mei 2019, bertambah 87 layar, sehingga total jumlah menjadi 1861 layar bioskop. Di Kota Madiun sendiri terdapat 2 bioskop yang beroperasi yaitu New Star Cineplex (NSC) Timbul Jaya Plaza dan CGV*Blitz, dari kedua bioskop terdapat perbedaan dari segi fasilitas, jumlah pengunjung bioskop, dan juga desain yang diterapkan. Berdasarkan data survey pengunjung pada Goggle Trend yang diambil dari bulan September – November 2019, menunjukkan perbedaan signifikan jumlah pengunjung antara bioskop NSC Timbul Jaya Plaza Madiun dengan bioskop CGV*Blitz, dimana jumlah pengunjung di bioskop NSC Timbul Jaya Plaza cenderung lebih rendah dari bioskop CGV*Blitz. Gambar 1. Data perbadingan jumlah pengunjung bioskop [Sumber : Google Trend, 2019] Kurang nya pembaharuan dari segi fasilitas dan desain pada interior bioskop NSC Timbul Jaya Plaza Madiun juga menjadi salah satu faktor sepinya pengunjung pada bioskop. Gambar 2. Keadaan eksisting bioskop NSC Timbul Jaya Plaza Madiun [Sumber : dokumentasi pribadi, 2020] Maka dari itu di dalam makalah ini akan dibahas redesain interior dari bioskop dengan menggunakan tema dan konsep Futuristic Entertainment yang bertujuan memberikan suasana baru pada bioskop untuk menghadapi persaingan bisnis bioskop yang semakin ketat seiring pertumbuhan jumlah layar bioskop yang semakin meningkat setiap bulannya dan era Industry 4.0 yang semakin canggih, selain itu pembaharuan dari segi desain dan hiburan dapat menarik perhatian pengunjung untuk datang ke bioskop NSC ini. METODE PENELITIAN 2.1 Metode Pengumpulan Data Terdapat dua data pada metode ini, yaitu Data Primer dengan dilakukan pengumpulan informasi-informasi melalui wawancara pada salah satu staff bioskop dan salah satu pengunjung bioskop. Data Sekunder dengan mengumpulkan data informasi dari berbagai sumber referensi akurat. Metode ini diyakini dapat memberikan data yang akurat, dan dapat memberikan gambaran jelas permasalahan pada bioskop. 2.2 Metode Analisa Data Metode Analisa Data pada redesain ini menggunakan metode kualitatif. Metode dengan pendekatan kualitatif merupakan metode penelitian yang di gunakan untuk meneliti pada populasi atau sampel tertentu, pengumpulan data menggunakan instrument penelitian, analisis data bersifat deskripsi. Metode penelitian kualitatif sering disebut metode penelitian naturalistik karena penelitianya di lakukan pada kondisi yang alamiah (natural setting). Dimana untuk hasil desainnya lebih bersifat umum, fleksibel serta berkembang dan muncul dalam proses penelitian. Kesimpulannya desain hanya digunakan sebagai asumsi untuk melakukan penelitian sehingga desain harus bersifat fleksibel dan terbuka. 2.3 Metode Desain Metode yang digunakan pada redesain ini yaitu metode glass box, dimana metode yang menggunakan parameter yang terukur, sesuai dengan fakta dan telah dianalisisa secara mendalam serta sistematis. Sehingga metode desain menggunakan sistem ini hasilnya diharapkan mampu rasional sehingga memenuhi standar kenyamanan. HASIL DAN PEMBAHASAN 3.1 Lokasi Site Bioskop ini berlokasi di Jalan Pahlawan Kav. 46 – 48, Mangu Harjo, Kota Madiun. Untuk akses ke bioskop tersebut sangatlah mudah, karena bangunan Timbul Jaya Plaza sendiri berada tepat dipinggir jalan raya dan berada di tengah kota Madiun sebagai pusat perekonomian kota tersebut sehingga mudah untuk ditemukan. Dari lokasi tersebut dapat dihasilkan data berupa eksisting dari bioskop tersebut. 3.2 Tema dan Konsep Menentukan tema dan konsep merupakan langkah awal dalam meredesain suatu interior. Hal ini akan memberikan gambaran yang jelas suatu ruangan dari segi bentuk, warna, dan material yang akan digunakan, sehingga memiliki visual yang menarik. Tema yang diaplikasikan pada redesain ini adalah Futuristic, Futuristik sendiri merupakan tema desain yang berorientasi pada masa depan, dengan banyak menggunakan bentukan yang tidak lazim, dan jarang diterapkan pada furniture pada umumnya. Dalam tema futuristik yang akan diterapkan pada redesain ini memiliki karakteristik dan ciri-ciri tersendiri, seperti tampilan artistik namun memiliki bentuk sederhana, elegant modern, dan dengan nuansa ruangan yang penuh dengan permainan lampu. (a) (b) Gambar 3. (a) Ruangan tema futuristic (b) aksen garis lampu pada garis pada furniture futuristic [Sumber : pinterest, 2020] Konsep yang diplikasikan pada redesain ini adalah Entertainment. Konsep ini mengambil elemen dari bioskop ini sendiri yaitu sebagai tempat hiburan yang sekaligus memberikan kesan dan pengalaman terbaik untuk menonton film bagi pengunjungnya. Dari tema dan konsep akan muncul suatu skema warna yang akan banyak diterapkan pada interior, yaitu cyan, hitam dan putih. Untuk material, banyak akan diterapkan menggunakan bahan stainless steel, aluminium, dan kaca tempered glass. 3.3 Scheme Color Dalam setiap konsep desain ruangan, terdapat warna-warna yang akan secara dominan muncul dalam pengaplikasiannya. Pada tema ini akan memiliki skema warna : Gambar 4. Scheme Color Redesain Bioskop New Star Cineplex Timbul Jaya Plaza Madiun [Sumber : dokumentasi pribadi, 2020] 3.4 Visualisasi tema dan konsep Tema dan konsep yang akan diterapkan pada interior adalah Futuristic Entertainment pada bagian lantai, dinding, ceiling/plafond, furniture, ruangan, dan fasilitas pada bioskop. Lantai Area lantai bioskop yang akan diterapkan adalah lobby bioskop dan area ruang teater. a) Lobby Gambar 5. Lantai Karpet [Sumber : dokumentasi pribadi, 2020] Pada bagian lobby bioskop, diaplikasikan karpet sebagai lapisan penutup lantai, dan aksen garis lampu untuk futuristic look yang mengelilingi area ruangan lobby, selain sebagai aksen, penggunaan garis ini berfungsi sebagai garis emergency ketika keadaan darurat terjadi, yang akan menyala untuk menuntun pengunjung ke arah pintu keluar. b) Ruang Teater Gambar 6. Lantai Ruang Teater [Sumber : dokumentasi pribadi, 2020] Area ruang teater diberikan lapisan karpet tile, dengan hidden lamp pada bagian tangga teater. Hidden lamp pada tangga selain berfungsi sebagai penunjuk jalan bagi penonton, sekaligus sebagai lampu emergency, penunjuk jalan ketika dalam keadaan darurat. Dinding Area yang akan diterapkan yaitu pada dinding lobby, ruang tunggu dan ruang teater. a) Lobby Gambar 7. Dinding Lobby [Sumber : dokumentasi pribadi, 2020] Dinding lobby menggunakan bentuk yang simetris, asimetris dan banyak menggunakan permainan hidden lamp untuk menyesuaikan konsep futuristik pada ruangan. b) Ruang Tunggu Gambar 8. Dinding Ruang Tunggu [Sumber : dokumentasi pribadi, 2020] Pada area dinding ini di aplikasikan bentuk simetris organic berbentuk honeycomb, bentuk ini menjadi focal point di salah satu sudut area ruang tunggu sebagai futuristic look. c) Ruang Teater Gambar 9. Dinding Ruang Teater [Sumber : dokumentasi pribadi, 2020] Dinding pada ruang teater, diterapkan backdrop untuk menambah kesan futuristik dalam ruangan, dan sebagai menambah pencahayaan ruangan. Ceiling/Plafond Area yang diterapkan yaitu pada lobby, ruang teater, dan lorong Exit Ruang Teater 2. a) Lobby Gambar 10. Plafond Ruang Lobby [Sumber : dokumentasi pribadi, 2020] Pada area lobby menggunakan drop ceiling yang terdapat hidden lamp di dalamnya mengelilingi lampu gantung. Penggunaan ceiling ini untuk memberikan tambahan pencahayaan dan menambah estetika futuristik pada ruangan. b) Ruang Teater Gambar 11. Plafond Ruang Teater [Sumber : dokumentasi pribadi, 2020] Ceiling pada area bioskop terdapat lampu pada setiap garis nya untuk memberikan futuristic look pada ruangan. Selain itu ceiling pada area ini sedikit diberikan bentuk lengkungan sebagai pengatur akustik audio ruangan. c) Lorong Exit Teater 2 Gambar 12. Plafond area lorong exit teater 2 [Sumber : dokumentasi pribadi, 2020] Area lorong exit diaplikasikan plafon kaca dengan ceiling yang tinggi, ukuran ruang lorong yang sempit, tidak ingin memberikan kesan claustrophobic pada pengunjung sehingga penggunaan plafond kaca memberikan kesan ruang yang lebih lapang, dan banyak penggunaan permainan lampu untuk memberikan daya tarik pada pengunjung. Furniture Gambar 13. Bentuk Desain [sumber : dokumentasi pribadi, 2020] Furniture pada area lobby memiliki bentuk yang berbeda dan memiliki bentukan yang simple. Furniture pada konsep ini banyak menggunakan LED strip yang mengikuti garis bentuknya, selain sebagai penambahan pencahayaan pada ruangan, sekaligus menambah estetika pada ruangan. Ruangan Bioskop Salah satu ruangan yang diterapkan tema dan konsep ini yaitu area lorong exit teater 2. Gambar 14. Area Lorong Exit Teater 2 [sumber : dokumentasi pribadi, 2020] Permainan lampu dan penempatan permainan cermin pada ruangan, untuk memberikan suasana fun dan eye catching pada para pengunjung, sehingga menjadi daya tarik tersendiri bagi pengunjung. Fasilitas Bioskop Fasilitas ini sebagai pelayanan yang diberikan oleh bioskop kepada pengunjung yang datang. a) Penggunaan teknologi terbaru pada bioskop. (Proyektor NEC NC3200S) Pengaplikasian proyektor versi ini akan memberikan kualitas gambar video 2K – 4K dan kontras warna yang jernih, sehingga akan memanjakan mata para penonton film. b) Audio berkualitas Dolby Atmos Pengaplikasian audio berkualitas Dolby Atmos akan memberikan kualitas suara yang lebih jernih, dan tampak realistis, sehingga memberikan pengalaman menonton yang menyenangkan. c) Fasilitas pendukung yang berbasis Smart Technology Pengaplikasian fasilitas yang telah mendukung Smart Technology selain mempermudah aktivitas agar lebih efisien, juga akan menarik pengunjung untuk datang, mencoba fasilitas baru yang belum pernah mereka coba. d) Online Based and Self-Service activity Pada era industry 4.0 sekarang ini, hampir segala aspek kegiatan sehari-hari barbasis pada internet, dan online dimana hal ini dimaksudkan untuk mempermudah kegiatan masyarakat agar lebih efisien. Dari keunggulan tersebut juga dapat diterapkan pada fasilitas hiburan publik seperti pada bioskop. Pemesanan tiket film tidak perlu lagi harus datang mengantri ke bioskop, cukup memesan tiketnya via online. Jika pun tidak sempat memesan tiket online bisa langsung memesan tiket on the spot, dengan self-service pada ticket box, yang telah disediakan layanan pemesanan tiket. Selain pelayanan pemesanan tiket film, kegiatan ini juga akan diterapkan pada pemesanan makanan di cinema café. Pengunjung dapat memesan makanan secara online melalui aplikasi sebelum menonton, ataupun on the spot. Sistem pembelian on the spot memiliki 2 cara, yaitu memesan sebelum menonton, atau ketika sedang menonton film. Pesan makanan sebelum menonton dapat dilakukan di cinema café dengan sistem self-service, pemesanan ketika sedang menonton dapat dilakukan melalui layanan customer service yang di install pada setiap kursi penonton, layanan ini terhubung langsung pada cinema café yang nantinya akan dibawakan makanan/minuman nya ke dalam ruang teater oleh pegawai cinema café. Material Bahan Material yang digunakan disesuaikan dengan tema dan konsep yang akan diterapkan pada bioskop. Penggunaan material logam seperti stainless steel, aluminum, dan besi banyak digunakan pada ruang interior, hal ini untuk memberikan kesan glossy pada ruangan. (a) (b) (c) Gambar 15. (a) Aluminum (b) Stainless Steel (c) Besi [Sumber : google, 2020] Selain itu penggunaan bahan kaca tempered glass dan cermin untuk memberikan reflective, bersih, sederhana, dan elegan. (a) (b) Gambar 16. (a) Kaca Tempered Glass (b) Kaca Cermin [Sumber : google, 2020] Lalu adanya penambahan material akustik, seperti rockwool dan gypsum digunakan pada area ruang teater sebagai pengaturan akustik pada ruangan. (a) (b) Gambar 17. (a) Kaca Tempered Glass (b) Kaca Cermin [Sumber : google, 2020] 3.5 Branding Branding pada New Star Cineplex ini bertujuan untuk mengenalkan desain logo baru pada bioskop ini, dengan tampilan yang berbeda dengan dengan sebelumnya menyesuaikan dengan konsep baru pada bioskop. Logo (a) (b) Gambar 18. (a) Logo Before (b) Logo After [Sumber : dokumentasi pribadi, 2020] Desain dari logo baru ini menyesuaikan dengan tema yang diterapkan pada ruang bioskop, yaitu futuristik dengan skema warna hitam, putih dan cyan. Font pada “New Star” dan “Cineplex” dirubah untuk mendukung tema menjadi lebih modern. Bentuk bintang dari logo sebelumnya masih tetap dipertahankan dan sedikit diberikan pembaharuan dari segi warna logo, untuk identitas diri dari bioskop tersebut. Tiket Film Gambar 19. Desain tiket bioskop [Sumber : dokumentasi pribadi, 2020] Desain tiket film ini terinspirasi oleh desain tiket film yang ada di Korea Selatan. Setiap tiket film terdapat gambar poster dari film yang ingin ditonton, bertujuan sebagai kenang-kenangan dan menambah daya tarik pecinta film bioskop yang gemar mengoleksi tiket film yang sudah ditonton. Interface pada aplikasi online Gambar 20. Interface pada aplikasi online [Sumber : dokumentasi pribadi, 2020] Pada desain aplikasi bioskop ini menyesuaikan dengan tema pada bioskop, sehingga dibuat simple agar mudah pengoperasian nya oleh masyarakat. 3.6 Hasil Desain Berikut beberapa hasil desain penerapan dari tema dan konsep pada bioskop Façade Gambar 21. Façade bioskop [Sumber : dokumentasi pribadi, 2020] Lobby Gambar 22. Lobby bioskop [Sumber : dokumentasi pribadi, 2020] Ruang Teater Gambar 23. Ruang Teater [Sumber : dokumentasi pribadi, 2020] Lorong Exit Teater 2 Gambar 24. Ruang Teater [Sumber : dokumentasi pribadi, 2020] SIMPULAN Bioskop New Star Cineplex (NSC) Timbul Jaya Plaza kota Madiun, bioskop ini berada di area pusat perbelanjaan (mall), dimana NSC merupakan salah satu tenant yang menjadi pendukung perputaran ekonomi pada area mall tersebut. Sayang, kurangnya minat pengunjung untuk datang ke bioskop, sedikit menghambat perputaran tersebut. Persaingan akan bisnis tempat pemutaran film semakin ketat, dimana setiap bulannya jumlah bioskop semakin bertambah dan hal ini menjadi tantangan bagi pengusaha bisnis bioskop untuk tetap mempertahankan usahanya. Maka dari itu, dari pihak pengelola harus tetap terus melakukan inovasi, perawatan, dan peningkatan fasilitas yang terdapat pada bioskop. Selain itu penerapan konsep Futuristic Entertainment ini bertujuan memberikan fasilitas hiburan yang bernuansa masa depan, sehingga dapat mengimbangi persaingan bisnis tempat bioskop yang semakin berkembang setiap bulannya. Apalagi di era Industry 4.0 sekarang ini dimana segala aspek didasari oleh teknologi internet dan online harus dapat diterapkan dalam segala hal, termasuk pada bioskop sebagai media hiburan masyarakat untuk memperluas jangkauan nya. DAFTAR PUSTAKA A. Wicaksono, D. Kharisma, dan S. Sastra. Ragam Desain Interior Modern. Cibubur, Jakarta Timur: Griya Kreasi (Penebar Swadaya Grup). 2014. A. Wicaksono, dan E. Tisnawati. Teori Interior. Cibubur, Jakarta Timur: Griya Kreasi (Penebar Swadaya Grup). 2014. P. Satwiko. Fisika Bangunan 1. Yogyakarta: CV Andi Offset. 2004. L. Doelle. 1972. Environmental Acoustics. New York, NY: Reprinted with permission from McGraw-Hill Book Company. 1972. W. Swasty. A-Z Warna Interior: Rumah Tinggal. Cibubur, Jakarta Timur: Griya Kreasi (Penebar Swadaya Grup). 2010. V. Leiwakabessy. 2013. “LANDASAN KONSEPTUAL PERENCANAAN DAN PERANCANGAN CINEMA AND FILM LIBRARY DI YOGYAKARTA, no. 3, http://e-journal.uajy.ac.id/3395/3/2TA13281.pdf, (Diakses pada 11 Desember 2019) Tim CNN Indonesia. 2019. “Jumlah Layar Bioskop Indonesia Mulai Kejar Korea Selatan”, Jakarta, 16 Mei. https://www.cnnindonesia.com/hiburan/20190516152929-220-395469/jumlah-layar-bioskop-indonesia-mulai-kejar-korea-selatan, Diakses pada 11 Desember 2019) Dekoruma, Kania. 2018. “8 Ciri Desain Futuristik, Gaya Desain Interior Masa Depan” Jakarta, 27 April. https://www.dekoruma.com/artikel/66939/gaya-desain-futuristik, (Diakses pada 11 Desember 2019) D. Agasbrama. 2014. “Konsep Desain Interior Futuristik” Jakarta, 15 Mei, https://interiorudayana14.wordpress.com/2014/05/15/konsep-desain-interior-futuristik/, (Diakses pada 11 Desember 2019) N. Khmairah, S. Wahyuning. 2017. “KAJIAN KARAKTERISTIK PENCAHAYAAN BUATAN PADA BIOSKOP (STUDI KASUS : CINEMACITRA XXI,MALL CIPUTRA,KOTA SEMARANG)” MODUL 17, no. 1(2017): 75-77. http://dx.doi.org/10.14710/mdl.17.2.2017.75-77, (Diakses pada 11 Januari 2020

An Individual method of living on with a daily existence it directly influences on your overall health. Since stress is the significant infection of our human body. Like depression, heart attack and mental illness. WHO says “Globally, more than 264 million people of all ages suffer from depression.”[8]. Also the report says that most of the time people are stressed because of their work. 10.7% of People disorder with stress, anxiety and depression [8]. There are different method to discovering stress ex. Smart watches, chest belt, and extraordinary machine. Our principle objective is to figure out pressure progressively utilizing smart watches through their Sensor. There are different kinds of sensor available to find stress such as PPG, GSR, HRV, ECG and temperature. Smart watches contain a wide range of data through various sensor. This kind of gathered information are applied on various machine learning method. Like linear regression, SVM, KNN, decision tree. Technique have distinct, comparing accuracy and chooses best Machine learning model. This paper investigation have different analysis to find and compare accuracy by various sensors data. It is also check whether using one sensor or multiple sensors such as HRV, ECG or GSR and PPG to predict the better accuracy score for stress detection.

Purpose At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications. Design/methodology/approach Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications. Findings This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development. Originality/value To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.

Many smart mobile devices, including smartphones, smart televisions, smart watches, and smart vacuums, have been powered by Android devices. Therefore, mobile devices have become the prime target for malware attacks due to their rapid development and utilization. Many security practitioners have adopted different approaches to detect malware. However, its attacks continuously evolve and spread, and the number of attacks is still increasing. Hence, it is important to detect Android malware since it could expose a great threat to the users. However, in machine learning intelligence detection, too many insignificant features will decrease the percentage of the detection’s accuracy. Therefore, there is a need to discover the significant features in a minimal amount to assist with machine learning detection. Consequently, this study proposes the Pearson correlation coefficient (PMCC), a coefficient that measures the linear relationship between all features. Afterwards, this study adopts the heatmap method to visualize the PMCC value in the color of the heat version. For machine learning classification algorithms, we used a type of fuzzy logic called lattice reasoning. This experiment used real 3799 Android samples with 217 features and achieved the best accuracy rate of detection of more than 98% by using Unordered Fuzzy Rule Induction (FURIA).

AbstractEvery year millions of people, from all walks of life, spend months training to run a traditional marathon. For some it is about becoming fit enough to complete the gruelling 26.2 mile (42.2 km) distance. For others, it is about improving their fitness, to achieve a new personal-best finish-time. In this paper, we argue that the complexities of training for a marathon, combined with the availability of real-time activity data, provide a unique and worthwhile opportunity for machine learning and for recommender systems techniques to support runners as they train, race, and recover. We present a number of case studies—a mix of original research plus some recent results—to highlight what can be achieved using the type of activity data that is routinely collected by the current generation of mobile fitness apps, smart watches, and wearable sensors.

Abstract Introduction With the recent developments in wearable technology, detecting arrhythmias has become much easier. Although smartwatches are commonly used to detect patients with atrial fibrillation, there is no consensus on their efficiency in detecting supraventricular tachycardias (SVT). Methods & Results Electrophysiological procedures were performed on 47 patients that have been previously documented to have SVT by a 12-lead ECG. All patients had sinus rhythm before the procedure. A narrow complex SVT which patients had at least once was induced by electrophysiological methods. Induced SVTs were recorded with a 6th-generation Apple Watch as one rhythm strip. Among the induced tachycardias, 27 typical AVNRT, 11 AVRT and 9 AT/AFLwere diagnosed. These records obtained from the smartwatch were evaluated by 3 cardiology residents and 3 attending cardiologists. Evaluated records were predicted among attending physicians with a minimum sensitivity of 66.0% and maximum sensitivity of 76.6%. Among residents, minimum and maximum sensitivity rates were 68.1% and 74.5%, respectively. The reliability between residents and attendings was assessed separately using Fleiss’s kappa method. The interrater reliability was found to be Kappa=0.465 (p&lt;0.001), 95% CI (0.30-0.63) within the group of residents and Kappa=0.519, (p&lt;0.001), 95% CI (0.35-0.68) within the group of attendings. Overall Kappa value was 0.417 (p&lt;0.001), 95% CI (0.34-0.49), indicating a significantly important moderate level of agreement (p&lt;0.001). Conclusion To the best of our knowledge, this is the first study showing how accurately clinicians can interpret the recording of SVTs with wearable devices such as smart watches, whose definitive diagnosis was made invasively by electrophysiological study. As presented in our study, induced, and subsequently recorded SVTs were predicted with high sensitivity and a moderate reliability rate. Adoption of smartwatches could significantly limit the delays in diagnosis and treatment of patients admitted to the hospitals with complaints of palpitations that cannot be documented.Statistics

Abstract Introduction Wrist-worn fitness and heart rate (HR) monitors are increasingly popular. Previous studies in healthy participants with sinus rhythm (SR) have yielded variable results depending on HR, activity levels and device tested. A paucity of data exists on their accuracy in atrial fibrillation (AF) in ambulatory patients. Purpose We sought to assess the HR accuracy of 2 commercially available smart watches (Fitbit Charge HR [FB] and Apple Watch Series 3 [AW]) compared with Holter monitoring in an ambulant patient cohort. Methods Patients aged >18 years referred for 24-hour Holter monitoring were prospectively recruited. The Holter monitor was the criterion measure. Each patient was randomly allocated to either a FB or AW along with their Holter monitor. The study protocol was approved by the institutional review board. Statistical analysis: Pearson (r) correlation coefficients and Bland-Altman comparison with 95% limits of agreement (LoA) were evaluated to assess criterion validity and agreement between the smart watch and Holter ECG-HR. Bias was the calculated mean difference between the smart watch and ECG-HR. A ± 10-beat different between Holter-HR and SW-HR was used as a clinically relevant range to establish the accuracy of HR estimation by SW. Results Across all devices, 53,288 hear rate values were recorded from 32 patients. Twenty six patients were in persistent AF and six were in SR. Twelve patients wore the FB while 20 wore the AW. In the FB arm, nice patient were in persistent AF and three in SR. In the AW arm, persistent AF was the rhythm in seventeen and SR in three. Patients in SR demonstrated overall strong agreement compared to Holter monitoring (Mean Bias <1 beat, LoA −11 to 11 beats) and a correlation coefficient of 0.87 (p<0.001). In AF, both devices underestimated HR measurements (Overall Bias −9 beats, LoA −41 to 23, r=0.60, p<0.001). The AW had lower bias and narrower LoA compared to FB (−5 beats vs −13 beats, LoA −31 to 21 beats vs −50 to 22 beats). Using a ± 10-beat range against ECG-HR for clinical accuracy, both the AW and FB performed satisfactorily in SR with 95.2% of AW and 92.2% of FB HR readings considered valid. In AF, however, the AW-HR readings were within the ± 10-beat threshold in 76.5% of the time compared with only 56.1% of FB readings. Conclusion In ambulatory patients, smart watches were accurate in HR estimation when compared to Holter monitor in SR; however tended to underestimate HR in AF. Further improvements in device technology are needed before the widespread consumer adoption of this nascent technology for chronotropic assessment in arrhythmias.

In present days’ women harassment is increasing and women’s life is at high risk. To overcome this problem, this paper approaches the IOT concept such as measuring the body temperature by temperature sensor, heart beat rates using pulse sensors to monitor their conditions and it alerts the mobile numbers which has been stored as emergency contact before. Since, there are already some web and mobile applications for women safety and for emergencies purposes, it does not adhere at all situations. Women cannot always be vigilant and carry huge devices with them. Instead, she could be monitored by wearing smart watches and other wearable devices, etc. It could be accessed and monitored by wireless technologies like GPS, GSM, GPRS for better results.

Wearable Technology is such advice which can be worn by people and they can help to measure certain important parameters of human body such as heart beat, rhythm, quality of sleep per day and also they can identify some disease like heart disease, diabetes and cancer. Smart shirts are used for the purpose of monitoring the health and wellbeing of patients and feedback the obtained information to hub station at real-time. These are quite sensitive to pick up and record electro-signals like heart beats and movements of muscles and finally sent to healthcare providers which can monitor the vitals of the users remotely for necessary actions to be taken by the appropriate body. It can create through devices better understanding of daily activities. Piezo resistive and ferroelectric sensors have been studied for various types of wearable and flexible electronics sensors. With controlled setting wearable technologies are very useful tools for assessment of individuals. Digital inter activity can interact by smart glasses delivery system as close as the wearer’s nose. The peculiarity of the technology is that the system based on hard-free gadgets with practical uses, powered by microprocessors for enhancing the ability to send and receive data through internet. Smart phone is best known wearable has emerged and continue to emerge today as proposed by APPLE watch. For humanity wearable devices with electronics present a unique interface of technology.

AbstractNew mobile applications need to estimate user activities by using sensor data provided by smart wearable devices and deliver context-aware solutions to users living in smart environments. We propose a novel hybrid data fusion method to estimate three types of daily user activities (being in a meeting, walking, and driving with a motorized vehicle) using the accelerometer and gyroscope data acquired from a smart watch using a mobile phone. The approach is based on the matrix time series method for feature fusion, and the modified Better-than-the-Best Fusion (BB-Fus) method with a stochastic gradient descent algorithm for construction of optimal decision trees for classification. For the estimation of user activities, we adopted a statistical pattern recognition approach and used the k-Nearest Neighbor (kNN) and Support Vector Machine (SVM) classifiers. We acquired and used our own dataset of 354 min of data from 20 subjects for this study. We report a classification performance of 98.32 % for SVM and 97.42 % for kNN.

Abstract Detection of atrial fibrillation (AF) from a wrist watch photoplethysmogram (PPG) signal is important because the wrist watch form factor enables long term continuous monitoring of arrhythmia in an easy and non-invasive manner. We have developed a novel method not only to detect AF from a smart wrist watch PPG signal, but also to determine whether the recorded PPG signal is corrupted by motion artifacts or not. We detect motion and noise artifacts based on the accelerometer signal and variable frequency complex demodulation based time-frequency analysis of the PPG signal. After that, we use the root mean square of successive differences and sample entropy, calculated from the beat-to-beat intervals of the PPG signal, to distinguish AF from normal rhythm. We then use a premature atrial contraction detection algorithm to have more accurate AF identification and to reduce false alarms. Two separate datasets have been used in this study to test the efficacy of the proposed method, which shows a combined sensitivity, specificity and accuracy of 98.18%, 97.43% and 97.54% across the datasets.

One of the main causes of sudden infant death syndrome (SIDS) is causes of newborn deaths while they are sleeping. We matched several devices to the infants to increase their safety. emerging fields of study for the creation of Infant Night Watch. The Wearable IoT Device, the Gateway, and Medical Interface make up this Smart Wearable System (SWS). Body temperature, heart and breathing rates, and blood oxygen level all be monitored by the Wearable IoT Device, which is a wireless sensor node built into a chest belt. This collection of data is delivered to the Gateway using wifi technology, which the user can access via the H Medical Interface. In the event of a critical occurrence, the patient’s mobile will sound an alarm that is audible. The Baby Night Watch is a crucial tool for medical research since it enables the viewing of historical physiological data and its export to various dataset types. The SWS has the capacity to recognise circumstances that could pose a life-threatening hazard to a child, according to experimental experiments. Key words – Body Temperature, Heart rate, breathing rates, blood oxygen level, smart wearable system.

AbstractThis investigation examined the association between on‐water rowing stroke‐rate (SR), velocity and heart‐rate (HR) in highly trained rowers (n = 8 male; n = 8 female and 19.3 ± 1.1 year) over a 4‐month real‐world (i.e., variable environment and boat class) training period. On‐water SR, prognostic velocity (percent of world's best velocity) and HR were captured for 1453 sessions via smart‐watch and chest‐strap HR monitor. Data was filtered and smoothed with individual HR training zones identified (T1–T5). Linear mixed modeling and an overlapping index () were used to assess differences in SR and prognostic velocity between HR zones. Correlation coefficient (r) was used to assess the SR and prognostic velocity relationship and progression of prognostic velocity at a SR of 20spm over time. There were significant differences in SR and prognostic velocity between HR zones (T1>T2>T3>T4>T5, p < 0.001); however, data overlap between adjacent zones was substantial for both variables ( = 0.69–0.85; prognostic velocity: = 0.46–0.86). A significant, positive correlation (r = 0.50 and p < 0.001) between SR and prognostic velocity was found. Progression of prognostic velocity at SR 20spm over the study duration was trivial (r = −0.01 and p = 0.71). Variables commonly used to prescribe and describe on‐water rowing training showed large variability in a real‐world training environment impacting the ability to accurately monitor training performance and progression.

Failing is an important issue for businesses. Embracing it moves markets, insures consumer safety, and spares unnecessary investment. Are the aviation and nuclear power industries the only industries to truly embrace it and share learnings to fortify standards and best practices? Can healthcare do the same? Telehealth and Medicine Today (THMT) is pleased to spotlight the critical necessity to face failure personally and professionally. Do we place too much emphasis on failure avoidance vs. failure recovery? Risk management hallmarks prioritize protecting the “brand” over sharing the experience. What are the principles for succeeding at failure? What models can we use? How does this impact burnout, workforce turnover, leadership vulnerability, and conducting meaningful retrospectives? Join our distinguished speakers representing health system, research community, and enterprise in this thoughtful and reflective discussion. THMT would like to continue discussions on this pivotal theme with experts in the field. Reach out to offer your learnings by emailing info@partnersiindigitalhealth.com. Alternatively, submit your research, opinion, or perspective to the journal here. Resources Episode 564: How to Succeed at Failing, Part 4: Extreme Resiliency, Theresa MacPhail, Stevens Institute of Technology, https://freakonomics.com/podcast/how-to-succeed-at-failing-part-4-extreme-resiliency/ Illuminating ‘the ugly side of science’: fresh incentives for reporting negative results, https://www.nature.com/articles/d41586-024-01389-7 Open Access Publisher Responds to White House with NO APC for Negative Research Management Lessons from Mayo Clinic: Inside One of the World's Most Admired Service Organizations Haru Urara: Japan’s Lovable Loser Trust in Radical Truth and Radical Transparency, Ray Dalio What Is Psychological Safety?, HBR Museum of Failure The Daily Stoic Humble Inquiry, Edgar Shien The Power of Regret, Daniel Pink Watch Bad Surgeon: Love Under the Knife, Netflix The Bizarre Story of ‘Vasa,’ the Ship That Keeps On Giving https://www.smithsonianmag.com/smart-news/bizarre-story-vasa-ship-keeps-giving-180964328/ The History of Fika: Swedish Coffee Break, https://food52.com/blog/9499-the-history-of-fika-swedish-coffee-break