Relevant bibliographies by topics / Smartwatch visualization

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Smartwatch visualization'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Smartwatch visualization"

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Cui, Zhe, Shivalik Sen, Sriram Karthik Badam, and Niklas Elmqvist. "VisHive: Supporting web-based visualization through ad hoc computational clusters of mobile devices." Information Visualization 18, no. 2 (January 23, 2018): 195–210. http://dx.doi.org/10.1177/1473871617752910.

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Current web-based visualizations are designed for single computers and cannot make use of additional devices on the client side, even if today’s users often have access to several, such as a tablet, a smartphone, and a smartwatch. We present a framework for ad hoc computational clusters that leverage these local devices for visualization computations. Furthermore, we present an instantiating JavaScript toolkit called VisHive for constructing web-based visualization applications that can transparently connect multiple devices—called cells—into such ad hoc clusters—called a hive—for local computation. Hives are formed either using a matchmaking service or through manual configuration. Cells are organized into a master–slave architecture, where the master provides the visual interface to the user and controls the slaves and the slaves perform computation. VisHive is built entirely using current web technologies, runs in the native browser of each cell, and requires no specific software to be downloaded on the involved devices. We demonstrate VisHive using four distributed examples: a text analytics visualization, a database query for exploratory visualization, a density-based spatial clustering of applications with noise clustering running on multiple nodes, and a principal component analysis implementation.
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Dey, Bijoy Kumar, Ritika Khan, and Mainak Kunai. "Analysis of Fitness Based on Smart Watch Data." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 02 (February 3, 2024): 1–10. http://dx.doi.org/10.55041/ijsrem28514.

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Smart watch, a new trend to many young as well as aged persons now a days, can serve as a fitness tracker and be far more accurate than a phone. Besides many technological advantages, a smartwatch can easily collect the data related to fitness and other movements also. Smart watch provides such an organized human health and activities dataset so that by this dataset a human activities analysis can be performed and by this analysis a conclusion can be drawn about their health. Accordingly, our Project aim is to analyze the data and examine whether the data collected through smart watches can describe the physical fitness of individuals on the basis of some of the factors related to daily activities. Keywords— Data Visualization, Correlation plot, Scatter plot, MANOVA, Fisher Exact Test, P-value
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Hidayaturrohman, Qisthi Alhazmi, M. Arifudin Lukmana, and Akhmad Nidhomuz Zaman. "Design of human heartbeat monitoring system based on wireless sensor networks." Techné : Jurnal Ilmiah Elektroteknika 22, no. 2 (December 5, 2023): 207–16. http://dx.doi.org/10.31358/techne.v22i2.354.

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The IoT technology plays an important role in Industry 4.0 revolution. The IoT technology has potential to be implemented in the medical industry, especially for the development of telemedicine system. IoT able to send the medical sensor data wirelessly to the nearest medical facility like hospital. In this research, the author designed the heart beat monitoring system by using 802.11 communication protocol and simple web interface. The pulse sensor that used in this research was able to read the pulse rate of the human and convert it to BPM (beat per minute). It has 98.89% accuracy and 1.11% error compared to the smartwatch result. In the other hand, ESP-32 also implemented as the microcontroller as well as the sensor node of the system. It was able to send the data wirelessly from sensor node to the coordinator node. The coordinator node was also able to fetch the sensor data into the database using POST and GET method and then visualize the sensor data over web interface so the other users are able to see the visualization of the sensor data.
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Blascheck, Tanja, Lonni Besancon, Anastasia Bezerianos, Bongshin Lee, and Petra Isenberg. "Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (January 2019): 630–40. http://dx.doi.org/10.1109/tvcg.2018.2865142.

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Santhanavanich, T., S. Schneider, P. Rodrigues, and V. Coors. "INTEGRATION AND VISUALIZATION OF HETEROGENEOUS SENSOR DATA AND GEOSPATIAL INFORMATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W7 (September 20, 2018): 115–22. http://dx.doi.org/10.5194/isprs-annals-iv-4-w7-115-2018.

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<p><strong>Abstract.</strong> According to the advances in Information &amp; Communication Technology (ICT), nowadays, the use of Internet of Things (IoT) has become a normal part of daily life. It allows interconnections among a wide variety of devices and sensors such as smartphones, smartwatches, automobiles, or any object with a built-in sensor. However, these devices and sensors are developed by numerous different manufacturers which leads to technology lock-in in terms of data formats and protocols. In order of address this heterogeneity, an interoperable sensor protocol is the need of the hour. To address this, we propose a sensor data management system for monitoring <i>pedelec</i> usage and user fitness level. Using a proof-of-concept prototype the study is carried out in downtown of Stuttgart city. The result of the integrated analyzed data is visualized in 3D digital globe CESIUM.</p>
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Hashimoto, Yoshiki, Daisaku Arita, Atsushi Shimada, Takashi Yoshinaga, Takashi Okayasu, Hideaki Uchiyama, and Rin-Ichiro Taniguchi. "Yield Visualization Based on Farm Work Information Measured by Smart Devices." Sensors 18, no. 11 (November 13, 2018): 3906. http://dx.doi.org/10.3390/s18113906.

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This paper proposes a new approach to visualizing spatial variation of plant status in a tomato greenhouse based on farm work information operated by laborers. Farm work information consists of a farm laborer’s position and action. A farm laborer’s position is estimated based on radio wave strength measured by using a smartphone carried by the farm laborer and Bluetooth beacons placed in the greenhouse. A farm laborer’s action is recognized based on motion data measured by using smartwatches worn on both wrists of the farm laborer. As experiment, harvesting information operated by one farm laborer in a part of a tomato greenhouse is obtained, and the spatial distribution of yields in the experimental field, called a harvesting map, is visualized. The mean absolute error of the number of harvested tomatoes in each small section of the experimental field is 0.35. An interview with the farm manager shows that the harvesting map is useful for intuitively grasping the states of the greenhouse.
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Chong-White, Nicky, Joseph Tagudin, and Jorge Mejia. "Advancing hearing research with the NAL ecologically momentary assessment platform for real-world insights." Journal of the Acoustical Society of America 154, no. 4_supplement (October 1, 2023): A206—A207. http://dx.doi.org/10.1121/10.0023293.

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Ecological Momentary Assessment (EMA) is an invaluable tool for assessing people's behaviours and experiences in their natural surroundings. We have developed a smartphone-based EMA tool, called NEMA, that has contributed to over 10 research studies by providing meaningful real-world insights into how individuals with hearing loss interact with various hearing device technologies. By providing real-world perspectives that complement traditional lab-based tests, NEMA offers a more comprehensive understanding of everyday hearing and communication challenges. Its advanced features include cloud-connectivity, customisable surveys, cross-device acoustic feature measurements from the environment, and a back-end platform enabling real-time data monitoring and visualization. To derive vital insights from this rich data stream, advanced analytical methodologies are applied. However, there exist limitations with smartphone-based EMAs that can influence their overall effectiveness. We identify these constraints and discuss strategies to alleviate participant burden and increase task relevance. These initiatives aim to enhance compliance and diversify data collected. Current work involves integrating smartwatches and additional sensor technology into our next generation NEMA platform. This progression aims to facilitate a more comprehensive capture of diverse data sets, ultimately leading to a deeper understanding of individual auditory experiences.
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Shandhi, Md Mobashir Hasan, Jennifer C. Goldsack, Kyle Ryan, Alexandra Bennion, Aditya V. Kotla, Alina Feng, Yihang Jiang, et al. "Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review." Journal of Medical Internet Research 23, no. 9 (September 15, 2021): e29875. http://dx.doi.org/10.2196/29875.

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Background Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. Objective We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. Methods We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. Results The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. Conclusions Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.
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Ankrah, Elizabeth A., Franceli L. Cibrian, Lucas M. Silva, Arya Tavakoulnia, Jesus A. Beltran, Sabrina E. B. Schuck, Kimberley D. Lakes, and Gillian R. Hayes. "Me, My Health, and My Watch: How Children with ADHD Understand Smartwatch Health Data." ACM Transactions on Computer-Human Interaction, December 20, 2022. http://dx.doi.org/10.1145/3577008.

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Children with ADHD can experience a wide variety of challenges related to self-regulation, which can lead to poor educational, health, and wellness outcomes. Technological interventions, such as mobile and wearable health systems, can support data collection and reflection about health status. However, little is known about how ADHD children interpret such data. We conducted a deployment study with 10 children, aged 10 to 15, for six weeks, during which they used a smartwatch in their homes. Results from observations and interviews during this study indicate that children with ADHD can interpret their own health data, particularly in the moment. However, as ADHD children develop more autonomy, smartwatch systems may require alternatives for data reflection that are interpretable and actionable for them. This work contributes to the scholarly discourse around health data visualization, particularly in considering implications for the design of health technologies for children with ADHD.
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Dong, Miaomiao. "Investigating the Users’ Preferences of Heart Rate Data Types and Visualizations on a Smartwatch." International Journal of Human–Computer Interaction, July 18, 2023, 1–22. http://dx.doi.org/10.1080/10447318.2023.2233130.

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Dissertations / Theses on the topic "Smartwatch visualization"

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Islam, Mohammad Alaul. "Visualizations for Smartwatches and Fitness Trackers." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG018.

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Cette thèse porte sur la recherche sur la conception et l'utilisation de micro-visualisations pour l'exploration de données mobiles et pervasives sur des smartwatches et des trackers de fitness. Les gens portent de plus en plus de smartwatches qui peuvent suivre et afficher une grande variété de données. Mon travail est motivé par les avantages potentiels des visualisations de données sur les petits appareils mobiles tels que les brassards de suivi de la condition physique et les smartwatches. Je me concentre sur les situations dans lesquelles les visualisations soutiennent des tâches spécifiques liées aux données sur des smartwatches interactives. Mon principal objectif de recherche dans ce domaine est de comprendre plus largement comment concevoir des visualisations à petite échelle pour les trackers de fitness. Ici, j'explore : (i) les contraintes de conception dans le petit espace par le biais d'un atelier d'idéation ; (ii) le type de visualisations que les gens voient actuellement sur le visage de leur montre ; (iii) une revue de conception et l'espace de conception des visualisations à petite échelle ; (iv) et la lisibilité des micro-visualisations en considérant l'impact de la taille et du rapport d'aspect dans le contexte du suivi du sommeil. Les principaux résultats de la thèse sont, premièrement, un ensemble de besoins de données concernant un contexte d'utilisation touristique dans lequel ces besoins de données ont été satisfaits avec une richesse de conceptions de visualisation dédiées qui vont au-delà de celles couramment vues sur les affichages des montres. Deuxièmement, un affichage prédominant des données de santé et de forme physique, les icônes accompagnant le texte étant le type de représentation le plus fréquent sur les faces actuelles des smartwatchs. Troisièmement, un espace de conception pour les visualisations sur les faces de smartwatch qui met en évidence les considérations les plus importantes pour les nouveaux affichages de données sur les faces de smartwatch et autres petits écrans. Enfin, dans le contexte du suivi du sommeil, nous avons constaté que les gens effectuaient des tâches simples de manière efficace, même avec une visualisation complexe, à la fois sur les écrans de la smartwatch et du bracelet de fitness, mais que les tâches plus complexes bénéficiaient de la taille plus grande de la smartwatch. Dans la thèse, je souligne les opportunités ouvertes importantes pour les futures recherches sur la visualisation des smartwatchs, telles que l'évolutivité (par exemple, plus de données, une taille plus petite et plus de visualisations), le rôle du contexte et du mouvement du porteur, les types d'affichage des smartwatchs et l'interactivité. En résumé, cette thèse contribue à la compréhension des visualisations sur les smartwatches et met en évidence les opportunités ouvertes pour la recherche en visualisation sur les smartwatches
This thesis covers research on how to design and use micro-visualizations for pervasive and mobile data exploration on smartwatches and fitness trackers. People increasingly wear smartwatches that can track and show a wide variety of data. My work is motivated by the potential benefits of data visualizations on small mobile devices such as fitness monitoring armbands and smartwatches. I focus on situations in which visualizations support dedicated data-related tasks on interactive smartwatches. My main research goal in this space is to understand more broadly how to design small-scale visualizations for fitness trackers. Here, I explore: (i) design constraints in the small space through an ideation workshop; (ii) what kind of visualizations people currently see on their watch faces; (iii) a design review and design space of small-scale visualizations; (iv) and readability of micro-visualizations considering the impact of size and aspect ratio in the context of sleep tracking. The main findings of the thesis are, first, a set of data needs concerning a sightseeing usage context in which these data needs were met with a wealth of dedicated visualization designs that go beyond those commonly seen on watch displays. Second, a predominant display of health & fitness data, with icons accompanying the text being the most frequent representation type on current smartwatch faces. Third, a design space for smartwatch face visualizations which highlights the most important considerations for new data displays for smartwatch faces and other small displays. Last, in the context of sleep tracking, we saw that people performed simple tasks effectively, even with complex visualization, on both smartwatch and fitness band displays; but more complex tasks benefited from the larger smartwatch size. Finally, I point out important open opportunities for future smartwatch visualization research, such as scalability (e.g., more data, smaller size, and more visualizations), the role of context and wearer's movement, smartwatch display types, and interactivity. In summary, this thesis contributes to the understanding of visualizations on smartwatches and highlights open opportunities for smartwatch visualization research
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Book chapters on the topic "Smartwatch visualization"

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Bathelt, Franziska, Ines Reinecke, Brita Sedlmayr, Sepp Höhne, Christian Gierschner, and Martin Sedlmayr. "Visualization of Medical Wearable-Data Using SMART-on-FHIR – A Concept for an Interdisciplinary Complex Practical Course." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220908.

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For the success of digital applications, especially AI applications, it is essential that both developers and medical professionals are enabled to understand each other’s perspective. For this reason, a new concept for an interdisciplinary complex practical course was developed for the master’s program in computer science at a German university, based on online learning nuggets and a hackathon on site. The core of the concept is a real-world medical application task: extracting ECG patient data from a smartwatch to support primary care physicians in making decisions regarding an action. The concept was developed based on the so-called constructive alignment concept. An initial application of the concept showed that it was rated as very positive in terms of learning experience and working atmosphere.
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Conference papers on the topic "Smartwatch visualization"

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Islam, Alaul, Anastasia Bezerianos, Bongshin Lee, Tanja Blascheck, and Petra Isenberg. "Visualizing Information on Watch Faces: A Survey with Smartwatch Users." In 2020 IEEE Visualization Conference (VIS). IEEE, 2020. http://dx.doi.org/10.1109/vis47514.2020.00038.

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Blascheck, Tanja, Lonni Besançon, Anastasia Bezerianos, Bongshin Lee, Alaul Islam, Tingying He, and Petra Isenberg. "Studies of Part-to-Whole Glanceable Visualizations on Smartwatch Faces." In 2023 IEEE 16th Pacific Visualization Symposium (PacificVis). IEEE, 2023. http://dx.doi.org/10.1109/pacificvis56936.2023.00028.

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Grioui, Fairouz, and Tanja Blascheck. "Heart Rate Visualizations on a Virtual Smartwatch to Monitor Physical Activity Intensity." In 14th International Conference on Information Visualization Theory and Applications. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0011665500003417.

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Wu, Ko-Chiu, Chun-Ching Chen, Tzu-Heng Chiu, and I.-Jen Chiang. "Transform children's library into a mixed-reality learning environment: Using smartwatch navigation and information visualization interfaces." In 2017 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC). IEEE, 2017. http://dx.doi.org/10.23919/pnc.2017.8203526.

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Grioui, Fairouz, and Tanja Blascheck. "Study of Heart Rate Visualizations on a Virtual Smartwatch." In VRST '21: 27th ACM Symposium on Virtual Reality Software and Technology. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3489849.3489913.

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Schiewe, Alexander, Andrey Krekhov, Frederic Kerber, Florian Daiber, and Jens Krüger. "A Study on Real-Time Visualizations During Sports Activities on Smartwatches." In MUM 2020: 19th International Conference on Mobile and Ubiquitous Multimedia. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3428361.3428409.

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Islam, Alaul, Ranjini Aravind, Tanja Blascheck, Anastasia Bezerianos, and Petra Isenberg. "Preferences and Effectiveness of Sleep Data Visualizations for Smartwatches and Fitness Bands." In CHI '22: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3491102.3501921.

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