Academic literature on the topic 'Heart rate detection'

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Journal articles on the topic "Heart rate detection"

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Boudet, G., and A. Chamoux. "Heart Rate Monitors And Abnormal Heart Rhythm Detection." Archives of Physiology and Biochemistry 108, no. 4 (January 2000): 371–79. http://dx.doi.org/10.1076/apab.108.4.371.4304.

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PEARSON, MICHAEL, and OLIVER FAUST. "HEART-RATE BASED SLEEP APNEA DETECTION USING ARDUINO." Journal of Mechanics in Medicine and Biology 19, no. 01 (February 2019): 1940006. http://dx.doi.org/10.1142/s0219519419400062.

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The purpose of this study was to investigate the use of a cost-effective heart rate monitor sensor and Arduino Uno configuration to accurately detect simulated sleep apnea, through the use of the inter-beat interval (R-R interval). Three separate 30[Formula: see text]min heart rate recordings were taken, each with six simulated sleep apnea events ranging from 20 to 40[Formula: see text]s. The results were gathered and processed to identify the simulated sleep apnea events. In each of the recordings, the simulated sleep apnea events were visible and the key characteristics, surrounding the events, could be recognized. The heart rate monitor sensor and Arduino Uno configuration successfully detected the simulated sleep apnea events through the analysis and processing of the hearts R-R interval.
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., S. Thulasi Prasad. "HEART RATE DETECTION USING HILBERT TRANSFORM." International Journal of Research in Engineering and Technology 02, no. 11 (November 25, 2013): 508–13. http://dx.doi.org/10.15623/ijret.2013.0211076.

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Bulckaert, Arnoud, Vasileios Exadaktylos, Guido De Bruyne, Bart Haex, Elke De Valck, Johan Wuyts, Johan Verbraecken, and Daniel Berckmans. "Heart rate-based nighttime awakening detection." European Journal of Applied Physiology 109, no. 2 (January 23, 2010): 317–22. http://dx.doi.org/10.1007/s00421-010-1359-0.

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Vicente, José, Pablo Laguna, Ariadna Bartra, and Raquel Bailón. "Drowsiness detection using heart rate variability." Medical & Biological Engineering & Computing 54, no. 6 (January 16, 2016): 927–37. http://dx.doi.org/10.1007/s11517-015-1448-7.

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Piotrowski, Z., and K. Różanowski. "Robust Algorithm for Heart Rate (HR) Detection and Heart Rate Variability (HRV) Estimation." Acta Physica Polonica A 118, no. 1 (July 2010): 131–35. http://dx.doi.org/10.12693/aphyspola.118.131.

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Patial, Payal, and Kawaldeep Singh. "Heart Rate Variability Analysis and Pathological Detection." International Journal of Computer Applications 70, no. 6 (May 17, 2013): 42–49. http://dx.doi.org/10.5120/11970-7825.

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Zhao, Yudan, and Chaoyu Wang. "Heart Rate Detection Based on Facial Video." Journal of Information Hiding and Privacy Protection 3, no. 3 (2021): 121–30. http://dx.doi.org/10.32604/jihpp.2021.026380.

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Mitsukura, Yasue, Koichi Fukunaga, Masato Yasui, and Masaru Mimura. "Sleep stage detection using only heart rate." Health Informatics Journal 26, no. 1 (February 19, 2019): 376–87. http://dx.doi.org/10.1177/1460458219827349.

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Getting enough quality sleep plays a vital role in protecting our mental health, physical health, and quality of life. Sleep deprivation can make it difficult to concentrate on daily activities, and lower sleep quality is associated with hypertension, hyperglycemia, and hyperlipidemia. The amount of sleep we get is important, but in recent years, quality sleep has also been deemed significant. Polysomnography, which has been the gold standard in assessing sleep quality based on stages, requires that the subject be attached to electrodes, which can disrupt sleep. An easier method to objectively measure sleep is therefore needed. The aim of this study was to construct an easy and objective sleep stage monitoring method. A cross-sectional study for healthy subjects has been done in our research. A new easy model for monitoring the sleep stages is built on only heart rate calculated by the electrocardiogram. This enabled us to easily assess the sleep quality based on five stages. This experiment included a total of 50 subjects. The overall accuracy in determining the five sleep stages was 66.0 percent. Four stages for sleep are identified accurately compared with other conventional methods. Despite there are no five sleep stage separation method using only heart rate, our method achieved the five separation for sleep with a relatively good accuracy. This study represents a great contribution to the field of sleep science. Because sleep stages can be recognized by the heart rate alone, sleep can be noninvasively assessed with any heart rate meter. This method will make it easier to determine sleep stages and diagnose sleep disorders.
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Gonzalez-Landaeta, R., O. Casas, and R. Pallas-Areny. "Heart Rate Detection From Plantar Bioimpedance Measurements." IEEE Transactions on Biomedical Engineering 55, no. 3 (March 2008): 1163–67. http://dx.doi.org/10.1109/tbme.2007.906516.

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Dissertations / Theses on the topic "Heart rate detection"

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Magnusson, Karolina. "Mechanical heart rate detection using cardiogenic impedance - a morphology approach." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119381.

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The objective of this thesis is to examine the possibility to determine the mechanical heart rate using intracardiac impedance in the time domain. Deducing the mechanical heartrate from the impedance could help improve the performance of implanted devices that today depend on the measurement of the heart’s electrical activity. Cardiogenic – also known as intracardiac – impedance is based on the difference in conductivity between heart muscle tissue and blood, making the impedance vary as the heart is filled and emptied. The data used in this thesis was acquired from three previous studies performed by St Jude Medical, two clinical and one preclinical. Two impedance measurement configurations were chosen from these studies, one bipolar and one quadropolar. To deduce the heart rate from the intracardiac impedance six algorithms were evaluated. Three using continuous peak detection and three evaluating small frames of the impedance signal.The peak detection algorithms were peak detection on the impedance signal itself, on its derivative  and on its integral. The three others were an Auto Correlation Function (ACF), an Average Magnutide Difference Function (AMDF) and an Average Wave Comparison Function (AWCF). In order to assess the heart rates deduced from the intracardiac impedance by the algorithms, these rates were compared to both the IEGM or the ECG (depending on which study was at hand) and the blood pressure. Several issues affected the performance of the algorithms. Impedance morphology can vary between patients. Some display so called “double peaks”, making it hard to decide whether a patient has for example a pulse of 80 bpm or of 160 bpm. The impedance morphology was also affected by amplitude modulation with the respiration frequency which in some patients cause difficulties to analyze the impedance signal. The results show that the two impedance measurement configurations perform equally well and that the ACF method was the overall best performing algorithm. They also show that individual patient impedance morphology has a large influence on the results and for future studies it should therefore be interesting to calibrate the algorithms for each patient, as this should improve performance.
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Danielsson, Fanny. "NON-CONTACT BASED PERSON’S SLEEPINESS DETECTION USING HEART RATE VARIABILITY." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44620.

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Today many strategies of monitoring health status and well-being are done through measurementmethods that are connected to the body, e.g. sensors or electrodes. These are often complicatedand requires personal assistance in order to use, because of advanced hardware and attachmentissues. This paper proposes a new method of making it possible for a user to self-monitoring theirwell-being and health status over time by using a non-contact camera system. The camera systemextracts physiological parameters (e.g. Heart Rate (HR), Respiration Rate (RR), Inter-bit-Interval(IBI)) based on facial color variations, due to blood circulation in facial skin. By examining anindividual’s physiological parameters, one can extract measurements that can be used in order tomonitor their well-being. The measurements used in this paper is features of heart rate variability(HRV) that are calculated from the physiological parameter IBI. The HRV features included andtested in this paper is SDNN, RMSSD, NN50 and pNN50 from Time Domain and VLF, LF andLF/HF from Frequency Domain. Machine Learning classification is done in order to classifyan individual’s sleepiness from the given features. The Machine Learning classification modelwhich gave the best results, in forms of accuracy, were Support Vector Machines (SVM). The bestmean accuracy achieved was 84,16% for the training set and 81,67% for the test set for sleepinessdetection with SVM. This paper has great potential for personal health care monitoring and can befurther extended to detect other factors that could help a user to monitor their well-being, such asmeasuring stress level
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Aguilar, Pelaez Eduardo. "Real-time algorithms for acoustic heart rate detection and respiratory rate extraction for use in miniature wearable breathing and heart monitor." Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/39384.

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This thesis presents novel research for real time heart sound detection, heart rate extraction and acoustic respiratory rate extraction algorithms. This was done based on signals obtained with a novel in-house developed wireless acoustic breathing and heart rate monitor. The core aim of this work is to enable additional features with respect to which physiological parameters can be measured by acoustic means with the above- mentioned sensor in the hospital bed environment. The performance evaluation was done with data collected from clinical trials carried out at Queens Square hospital - UCL Institute of Neurology - in London, UK. The respiratory rate extraction algorithm presented achieved a value difference bias of 0.07 and standard deviation of 1.55 breaths per minute with respect to the counted respiratory oscillations on the polysomnography device signals of the flow sensor as well as the abdominal and thoracic band evaluated on more than 21 hours of data from 13 different subjects during sleep. Similarly the novel heart rate extraction algorithm for processing the acoustic signals achieves a performance of 90.20% and 90.26% agreement with respect to heart rate value provided by the Konica-Minolta and SomnoMedics devices respec- tively evaluated on more than 57 hours of data acquired from 13 different subjects during sleep in the clinical trials. This is the largest dataset for acoustic heart sound classification and heart rate extraction in the literature to date. Overall, these results represent: a clear proof of concept for heart rate monitoring with the in-house developed wireless acoustic monitoring system; the addition of two very important monitoring capabilities to the wireless acoustic monitoring system; as well as significant contributions to the field of signal processing for both acoustic respiratory rate and heart rate monitoring.
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Uggla, Lingvall Kristoffer. "Remote heart rate estimation by evaluating measurements from multiple signals." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210303.

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Heart rate can say a lot about a person's health. While most conventional methods for heart rate measurement require contact with the subject, these are not always applicable. In this thesis, a non-invasive method for pulse detection is implemented and analyzed. Different signals from the color of the forehead—including the green channel, the hue channel and different ICA and PCA components—are inspected, and their resulted heart rates are weighted together according to the significance of their FFT peaks. The system is tested on videos with different difficulties regarding the amount of movement and setting of the scene. The results show that the approach of weighting measurements from different signals together has great potential. The system in this thesis, however, does not perform very well on videos with a lot of movement because of motion noise. Though, with better, less noisy signals, good results can be expected.
En människas puls säger en hel del om dennes hälsa. För att mäta pulsenanvänds vanligtvis metoder som vidrör människan, vilket iblandär en nackdel. I det här examensarbetet tas en metod för pulsmätningpå avstånd fram, som endast använder klipp från en vanlig videokamera. Färgen i pannan mäts och utifrån den genereras flera signalersom analyseras, vilket resulterar i olika mätvärden för pulsen. Genomatt värdera dessa mätvärden med avseende på hur tydliga signalernaär, beräknas ett viktat medelvärde som ett slutgiltigt estimat på medelpulsen. Metoden testas på videoklipp med varierande svårighetsgrad,beroende på hur mycket rörelser som förekommer och på vilketavstånd från kameran försökspersonen står. Resultaten visar att metodenhar mycket god potential och att man kan man förvänta sig finaresultat med bättre, mindre brusiga signaler.
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Häggmark, Sören. "Detection of myocardial ischemia : clinical and experimental studies with focus on vectorcardiography, heart rate and perioperative conditions /." Umeå : Kirurgisk och perioperativ vetenskap, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-598.

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Häggmark, Sören. "Detection of myocardial ischemia : clinical and experimental studies with focus on vectorcardiography, heart rate and perioperative conditions." Doctoral thesis, Umeå universitet, Anestesiologi och intensivvård, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-598.

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Introduction. Multiple clinical methods for detecting myocardial ischemia are utilised in the hospital setting each day, but there is uncertainty about their diagnostic accuracy. In the operating room, multiple methods may be employed, while in the CCU advanced electrophysiological (ECG) techniques for myocardial ischemia detection, and in particular, ST segment analysis, are common. Vectorcardiography (VCG) is one form of ECG. Several conditions other than ischemia may cause marked ST changes, which can impair the process of diagnosis of clinical ischemia. Elevated HR is one of these factors, which is studied here. The hypotheses were about concordance of different methods to detect ischemia, and relation of ECG ST levels to HR with and without myocardial ischemia. Methods. Study I. Anesthetised vascular surgical patients with coronary artery disease were studied during the start of anesthesia and surgery: ECG, hemodynamic, mechanical, and metabolic parameters were measured and categorised as positive or negative with reference to a specific definition of myocardial ischemia. Study II. Awake patients with no ischemic heart disease were paced in graded steps, and VCG ST analyses were performed. Study III. Anesthetised pigs were studied for local metabolic and VCG ST changes related to controlled HR levels and transient coronary occlusion. Study IV. Thirty five anesthetised coronary artery disease (CAD) patients and ten non-CAD patients were paced at controlled levels, and great coronary artery vein (GCV) lactate measurement was used to determine presence or absence of myocardial ischemia. The CAD patients were paced up to HR levels where myocardial ischemia could be confirmed. The relation of HR-related VCG ST levels to presence or absence of ischemia was analysed. In Studies II,, III, and IV the ST vector magnitude (ST-VM), the change from baseline in ST-VM (STC-VM), and the vector angle change from baseline (STC-VA) were analysed for each step. Results. Study I. Poor concordance was demonstrated for positive events (presumed myocardial ischemia) between the hemodynamic, ECG, mechanical, and metabolic detection methods. Study II. STC-VM but not ST-VM levels demonstrated HR-related increases in the presumed absence of myocardial ischemia in 18 awake subjects. J point time to ST measurement did not affect the response of VCG ST to HR. Study III. STC-VM levels showed HR-related increases in the absence of ischemia (tested by local metabolic observations). VCG ST parameters responded positively to transient regional ischemia. Study IV. CAD patients, which demonstrated a clear pattern of onset and progress of ischemia during pacing, were further analysed for the relation of VCG ST level to ischemia. Sensitivity and specificity of STC-VM levels were described by ROC analysis for a range of STC-VM levels. Conclusions. Concordance of different measures for detection of onset of myocardial ischemia is difficult to assess in the absence of a very reliable reference method. The contribution of HR and ischemia to VCG ST levels were estimated in study subjects. HR-related increases in STC-VM occur in the absence of ischemia. HR levels need to be considered when interpreting STC-VM as a diagnostic test for ischemia. Further study is needed to establish criteria that take into account multiple clinical factors in order to improve the predictive value of our tests for myocardial ischemia.
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Syed, Shah Nemath Farhan. "IMPLEMENTATION OF INTERACTIVE REMOTE PHYSIOLOGICAL MONITORING AND FEEDBACK TRAINING SYSTEM." University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1164666232.

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Raymondi, Luis Guillermo Antezana, Fabricio Eduardo Aguirre Guzman, Jimmy Armas-Aguirre, and Paola Agonzalez. "Technological solution for the identification and reduction of stress level using wearables." IEEE Computer Society, 2020. http://hdl.handle.net/10757/656578.

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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
In this article, a technological solution is proposed to identify and reduce the level of mental stress of a person through a wearable device. The proposal identifies a physiological variable: Heart rate, through the integration between a wearable and a mobile application through text recognition using the back camera of a smartphone. As part of the process, the technological solution shows a list of guidelines depending on the level of stress obtained in a given time. Once completed, it can be measured again in order to confirm the evolution of your stress level. This proposal allows the patient to keep his stress level under control in an effective and accessible way in real time. The proposal consists of four phases: 1. Collection of parameters through the wearable; 2. Data reception by the mobile application; 3. Data storage in a cloud environment and 4. Data collection and processing; this last phase is divided into 4 sub-phases: 4.1. Stress level analysis, 4.2. Recommendations to decrease the level obtained, 4.3. Comparison between measurements and 4.4. Measurement history per day. The proposal was validated in a workplace with people from 20 to 35 years old located in Lima, Peru. Preliminary results showed that 80% of patients managed to reduce their stress level with the proposed solution.
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Vykoupil, Pavel. "Použití analýzy HRV pro automatickou detekci ischemie u izolovaného zvířecího srdce." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220564.

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This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
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Doyen, Matthieu. "Méthodes probabilistes pour le monitoring cardio-respiratoire des nouveau-nés prématurés." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S049/document.

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La surveillance des nouveau-nés prématurés placés en unité de soins intensifs a conduit à la notion de monitoring et à l'acquisition de nombreux signaux physiologiques. Si ces informations sont bien utilisées pour le diagnostic et la prévention des situations d'urgence, force est de constater qu'à ce jour, elles le sont beaucoup moins dans un objectif prédictif. La difficulté d'extraction d'informations fiables en temps réel, sans aucun contrôle visuel, à partir de signaux non stationnaires, en est vraisemblablement la cause. Ce mémoire vise donc à proposer des méthodes robustes, adaptées au contexte des unités de soins intensifs néonatals et du temps réel. Pour cela, un ensemble de méthodes génériques appliquées à la variabilité cardiaque, mais capable d'être adaptées à d'autres constantes physiologiques telles que la respiration, ont été développées et testées en contexte clinique. Quatre grandes parties illustrent notre propos : - La proposition d'une méthode originale de détection temps réel probabiliste multicaractéristique permettant de répondre à une problématique d'extraction robuste d'événements d'intérêt à partir de signaux physiologiques bruités. Générique, cette solution est appliquée à la détection robuste du QRS d'un signal ECG. Elle est basée sur le calcul temps réel de plusieurs probabilités a posteriori, concernant les propriétés du signal, qui sont ensuite fusionnées au sein d'un nœud de décision reposant sur l'utilisation pondérée de la divergence de Kullback-Leibler. Comparée à deux méthodes classiques de la littérature sur deux bases de données bruitées, elle obtient un taux d'erreur de détection inférieur (20.91% vs 29.02% (ondelettes) et 33.08% (Pan-Tompkins) sur la base de test). - La proposition d'une méthode impliquant plusieurs modèles semi-markoviens cachés, visant la segmentation de périodes au sein desquelles le détecteur temps réel probabiliste multicaractéristique fournit les détections d'évènements les plus fiables. En comparaison à deux méthodes de la littérature, la solution proposée obtient de meilleures performances, le critère d‘erreur obtenu est significativement plus faible (entre -21.37% et -74.98% selon la base et l'approche évaluée). - La sélection d'un détecteur optimal pour le monitoring d'événements d'apnée-bradycardie, en termes de fiabilité et précocité, à partir de données ECG obtenues chez le nouveau-né. Les performances du détecteur retenu seront comparées aux alarmes générées par un dispositif industriel de suivi continu classiquement utilisé en service de néonatalogie (moniteur Philips IntelliVue). La méthode basée sur le changement abrupt de la moyenne des RR obtient les meilleurs résultats au regard du délai (3.99 s vs 11.53 s pour le moniteur IntelliVue) et de la fiabilité (critère d'erreur de 43.60% vs 80.40%). - La conception et le développement d'une plateforme logicielle SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) permettant l'acquisition de divers signaux physiologiques en très grande quantité, et de façon non invasive, au sein des unités de soins. La conception modulaire de cette plateforme, ainsi que ses propriétés temps réel, permettent l'intégration simple et rapide de méthodes de traitement du signal complexes. Son intérêt translationnel est montré dans le dépouillement d'une base de données cherchant à étudier l'impact de la bilirubine sur la variabilité cardiaque
The surveillance of premature newborns placed in intensive care units led to the notion of monitoring and the acquisition of many physiological signals. While this information is well used for the diagnosis and prevention of emergency situations, it must be acknowledged that, to date, it is less the case for predictive purposes. This is mainly due to the difficulty of extracting reliable information in real time, without any visual control, from non-stationary signals. This thesis aims to propose robust methods, adapted to the context of neonatal intensive care units and real time. For this purpose, a set of generic methods applied to cardiac variability, but capable of being adapted to other physiological constants such as respiration, have been developed and tested in clinical context. Four main parts illustrate these points : - The proposal of an original multicharacteristic probabilistic real time detection method for robust detection of interest events of noisy physiological signals. Generic, this solution is applied to the robust QRS complex detection of the ECG signals. It is based on the real time calculation of several posterior probabilities of the signal properties before merging them into a decision node using the weighted Kullback-Leibler divergence. Compared to two classic methods from the literature on two noisy databases, it has a lower detection error rate (20.91% vs. 29.02% (wavelets) and 33.08% (Pan-Tompkins) on the test database). - The proposal of using hidden semi-markovian models for the segmentation of temporal periods with most reliable event detections. Compared to two methods from the literature, the proposed solution achieves better performance, the error criterion obtained is significantly lower (between -21.37% and -74.98% depending on the basis and approach evaluated). - The selection of an optimal detector for the monitoring of apnea-bradycardia events, in terms of reliability and precocity, based on ECG data obtained from newborns. The performance of the selected detector will be compared to the alarms generated by an industrial continuous monitoring device traditionally used in neonatology service (Philips IntelliVue monitor). The method based on the abrupt change of the RR average achieves the best results in terms of time (3.99 s vs. 11.53 s for the IntelliVue monitor) and reliability (error criterion of 43.60% vs. 80.40%). - The design and development of SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) software platform for the acquisition of various physiological signals in large quantities, and in a non-invasive way, within the care units. The modular design of this platform, as well as its real time properties, allows simple and fast integration of complex signal processing methods. Its translational interest is shown in the analysis of a database in order to study the impact of bilirubin on cardiac variability
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Books on the topic "Heart rate detection"

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Imam, Siddique Zafar. Detection of abnormalities in fetuses and diabetic patients through the use of heart rate variability. [s.l: The Author], 1997.

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United States. National Aeronautics and Space Administration., ed. A portable fetal heart monitor and its adaption to the detection of certain abnormalities: Final report for the period ended October 31, 1993. Norfolk, Va: Dept. of Electrical & Computer Engineering, College of Engineering & Technology, Old Dominion University, 1994.

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Gandhi, Sanjay, and William R. Lewis. ECG monitoring in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0129.

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Electrocardiographic (ECG) monitoring is routinely used in hospitals for patients with a wide range of cardiac and non-cardiac diagnoses. Besides simple monitoring of heart rate and detection of life-threatening arrhythmias, the goals of ECG monitoring include detection of myocardial ischaemia, diagnosis of complex arrhythmia, and identification of a prolonged QT interval. The ECG remains a cornerstone in diagnosis and management of patients with coronary ischaemia. Over the past decade, there has been an increase in the number and complexity of electrophysiological interventions, including complex ablations, biventricular pacing, and insertion of implantable defibrillators. ECG monitoring in these patients can serve both a protective and diagnostic purpose. They detect life-threatening arrhythmias and double up as in-patient Holter monitors. Unfortunately, there are no randomized controlled trials of in-hospital cardiac monitoring—expert opinions based on clinical experience and published research in the field of electrocardiography form the basis of current guidelines.
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Hagendorff, Andreas. Cardiac involvement in systemic diseases. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199599639.003.0020.

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Systemic diseases are generally an interdisciplinary challenge in clinical practice. Systemic diseases are able to induce tissue damage in different organs with ongoing duration of the illness. The heart and the circulation are important targets in systemic diseases. The cardiac involvement in systemic diseases normally introduces a chronic process of alterations in cardiac tissue, which causes cardiac failure in the end stage of the diseases or causes dangerous and life-threatening problems by induced acute cardiac events, such as myocardial infarction due to coronary thrombosis. Thus, diagnostic methods—especially imaging techniques—are required, which can be used for screening as well as for the detection of early stages of the diseases. Two-dimensional echocardiography is the predominant diagnostic technique in cardiology for the detection of injuries in cardiac tissue—e.g. the myocardium, endocardium, and the pericardium—due to the overall availability of the non-invasive procedure.The quality of the echocardiography and the success rate of detecting cardiac pathologies in patients with primary non-cardiac problems depend on the competence and expertise of the investigator. Especially in this scenario clinical knowledge about the influence of the systemic disease on cardiac anatomy and physiology is essential for central diagnostic problem. Therefore the primary echocardiography in these patients should be performed by an experienced clinician or investigator. It is possible to detect changes of cardiac morphology and function at different stages of systemic diseases as well as complications of the systemic diseases by echocardiography.The different parts of this chapter will show proposals for qualified transthoracic echocardiography focusing on cardiac structures which are mainly involved in different systemic diseases.
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Taillefer, Raymond, and Frans J. Th Wackers. Kinetics of Conventional and New Cardiac Radiotracers. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199392094.003.0004.

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The kinetics of radiotracers, that is the mode of uptake, retention and release from the myocardium, are relevant for designing and implementing optimized nuclear cardiac imaging protocols. This chapter addresses the kinetics of commonly used radiotracers for imaging myocardial perfusion, sympathetic neuronal function and cardiac metabolism, both with SPECT and PET cardiac imaging. The optimal timing of imaging after injection either at stress or at rest is determined by rate of uptake in the heart and adjacent organs, as well as the residence time of radiotracers within the myocytes. The efficiency of myocardial extraction over a wide range myocardial blood flows is relevant for reliable detection of obstructive coronary artery disease and absolute quantification of regional myocardial blood flow. For each cardiac imaging agent the cellular mechanism of uptake and its release or retention are discussed with an emphasis on the clinical impact of these parameters.
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Andrade, Maria João, and Albert Varga. Stress echocardiography: methodology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198726012.003.0012.

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Stress echocardiography is the combination of echocardiography with a physical, pharmacological, or electrical stress. Good quality images are absolutely necessary and a quad-screen format should be applied for comparative analysis. Different stress echo protocols can be used in different pathologies. Exercise echocardiography has the advantages of its wide availability, low cost, and versatility for the assessment of various cardiac conditions. The most usual pathologies are suspected or known ischaemic heart disease, mitral and aortic valve diseases, hypertrophic cardiomyopathy, and pulmonary hypertension. Among exercise-independent stresses, dobutamine and dipyridamole are the most frequently used. Dobutamine is widely accepted for the evaluation of myocardial viability. The two tests have comparable accuracy for the detection of coronary artery disease. Ergonovine echo is highly feasible, accurate, and safe for the diagnosis of coronary vasospasm. High-rate pacing is especially appropriate in patients with a permanent pacemaker because non-invasive diagnosis of coronary artery disease in these patients is an extremely difficult task.
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Griffin, Laura. Flight: A heart-pounding, race-against-the-clock romantic thriller. Headline Eternal, 2021.

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Hastings, Anastasia, Peter Blauner, Juan Gómez-Jurado, Alex Finlay, and Stacy Willingham. Minotaur Sampler, Volume 7: New Books to Make Your Heart Race. St. Martin's Press, 2022.

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Red Lotus: A Rare Beauty - A Fierce Heart - A Destiny She Must Resist. Little, Brown Book Group Limited, 2009.

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Red Lotus: A Rare Beauty. A Fierce Heart. A Destiny She Must Resist. Little, Brown Book Group Limited, 2009.

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Book chapters on the topic "Heart rate detection"

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Shkilniuk, Yurii, Maksym Gaiduk, and Ralf Seepold. "Unobtrusive Accelerometer-Based Heart Rate Detection." In Lecture Notes in Electrical Engineering, 49–54. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66729-0_6.

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Hernandez-Ortega, Javier, Ruben Tolosana, Julian Fierrez, and Aythami Morales. "DeepFakes Detection Based on Heart Rate Estimation: Single- and Multi-frame." In Handbook of Digital Face Manipulation and Detection, 255–73. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87664-7_12.

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AbstractThis chapter describes a DeepFake detection framework based on physiological measurement. In particular, we consider information related to the heart rate using remote photoplethysmography (rPPG). rPPG methods analyze video sequences looking for subtle color changes in the human skin, revealing the presence of human blood under the tissues. This chapter explores to what extent rPPG is useful for the detection of DeepFake videos. We analyze the recent fake detector named DeepFakesON-Phys that is based on a Convolutional Attention Network (CAN), which extracts spatial and temporal information from video frames, analyzing and combining both sources to better detect fake videos. DeepFakesON-Phys has been experimentally evaluated using the latest public databases in the field: Celeb-DF v2 and DFDC. The results achieved for DeepFake detection based on a single frame are over 98% AUC (Area Under the Curve) on both databases, proving the success of fake detectors based on physiological measurement to detect the latest DeepFake videos. In this chapter, we also propose and study heuristical and statistical approaches for performing continuous DeepFake detection by combining scores from consecutive frames with low latency and high accuracy (100% on the Celeb-DF v2 evaluation dataset). We show that combining scores extracted from short-time video sequences can improve the discrimination power of DeepFakesON-Phys.
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He, Chenguang, Yuwei Cui, and Shouming Wei. "Research on Non-contact Heart Rate Detection Algorithm." In Machine Learning and Intelligent Communications, 316–25. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73447-7_35.

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Deng, Yunbin. "Remote Liveness and Heart Rate Detection from Video." In Pattern Recognition. ICPR International Workshops and Challenges, 89–105. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68793-9_7.

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Haque, Emad, Tanishka Gupta, Vinayak Singh, Kaustubh Nene, and Akhil Masurkar. "Detection and Classification of Fetal Heart Rate (FHR)." In Lecture Notes in Electrical Engineering, 437–47. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8542-2_35.

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Lima, A. T. M., D. B. Gusmão, and M. V. C. Costa. "Remote Detection of Heart Beat and Heart Rate from Video Sequences." In XXVI Brazilian Congress on Biomedical Engineering, 437–40. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-2517-5_66.

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Chang, Chuan-Yu, and Hsiang-Chi Liu. "Heart Rate Detection Based on Facial Feature Points Tracking." In Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing, 287–93. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03748-2_35.

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Chen, Chien-Hung, Cheng-Yu Chen, Min-Wei Huang, and Kuo-Sheng Cheng. "The Alcohol Detection Using Heart Rate Variability and Bioimpedance." In 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006, 598–601. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-68017-8_150.

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Rätzer, Sebastian, Maksym Gaiduk, and Ralf Seepold. "Heart Rate Detection Using a Non-obtrusive Ballistocardiography Signal." In Intelligent Decision Technologies, 405–16. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3444-5_35.

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Chowdhury, Tamal, Sukalpa Chanda, Saumik Bhattacharya, Soma Biswas, and Umapada Pal. "Contact-Less Heart Rate Detection in Low Light Videos." In Lecture Notes in Computer Science, 77–91. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02375-0_6.

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Conference papers on the topic "Heart rate detection"

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Paliwal, Sukriti, C. Vasantha Lakshmi, and C. Patvardhan. "Real time heart rate detection and heart rate variability calculation." In 2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). IEEE, 2016. http://dx.doi.org/10.1109/r10-htc.2016.7906818.

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Tjiharjadi, Semuil, and Aufar Fajar. "Human Heart Rate Detection Application." In 2017 International Conference on Soft Computing, Intelligent System and Information Technology (ICSIIT). IEEE, 2017. http://dx.doi.org/10.1109/icsiit.2017.12.

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Tripathi, Avinash, and Shahanaz Ayub. "Heart Rate Variability Detection in Arrhythmia." In 2015 International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2015. http://dx.doi.org/10.1109/cicn.2015.77.

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Shi, Cong, Xiaohua Liu, Lingqin Kong, Jizhe Wu, Ming Liu, Liquan Dong, Mei Hui, and Yuejin Zhao. "Wearable sensor for heart rate detection." In International Conference on Optical Instruments and Technology 2015, edited by Xuping Zhang, David Erickson, Xudong Fan, and Zhongping Chen. SPIE, 2015. http://dx.doi.org/10.1117/12.2193129.

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Warrick, Philip, and Emily Hamilton. "Antenatal Fetal Heart Rate Acceleration Detection." In 2016 Computing in Cardiology Conference. Computing in Cardiology, 2016. http://dx.doi.org/10.22489/cinc.2016.259-501.

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Zhang, Xiaoqing, Lishuang Feng, and Jiqiang Wang. "Digital heart rate measurement based on Atmega16L." In International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, edited by Liwei Zhou. SPIE, 2008. http://dx.doi.org/10.1117/12.790767.

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Tsai, Tzung-Min, Hsing-Chen Lin, Shuenn-Yuh Lee, and Soon-Jyh Chang. "Heart rate detection through bone-conduction headset." In 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2014. http://dx.doi.org/10.1109/biocas.2014.6981646.

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Lauteslager, Timo, Mathias Tommer, Kristian G. Kjelgard, Tor S. Lande, and Timothy G. Constandinou. "Intracranial heart rate detection using UWB radar." In 2016 IEEE Biomedical Circuits and Systems Conference (BioCAS). IEEE, 2016. http://dx.doi.org/10.1109/biocas.2016.7833739.

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Zhu, Jianhuai, Ying Shi, and Mingdong Yang. "Heart Rate Detection Based on Computer Vision." In 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS). IEEE, 2018. http://dx.doi.org/10.1109/ccis.2018.8691178.

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Shamim, Gulezar, Yusuf Uzzaman Khan, Mohammad Sarfraz, and Omar Farooq. "Epileptic seizure detection using heart rate variability." In 2016 International Conference on Signal Processing and Communication (ICSC). IEEE, 2016. http://dx.doi.org/10.1109/icspcom.2016.7980585.

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Reports on the topic "Heart rate detection"

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Clausen, Jay, Michael Musty, Anna Wagner, Susan Frankenstein, and Jason Dorvee. Modeling of a multi-month thermal IR study. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41060.

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Inconsistent and unacceptable probability of detection (PD) and false alarm rates (FAR) due to varying environmental conditions hamper buried object detection. A 4-month study evaluated the environmental parameters impacting standoff thermal infra-red(IR) detection of buried objects. Field observations were integrated into a model depicting the temporal and spatial thermal changes through a 1-week period utilizing a 15-minute time-step interval. The model illustrates the surface thermal observations obtained with a thermal IR camera contemporaneously with a 3-d presentation of subsurface soil temperatures obtained with 156 buried thermocouples. Precipitation events and subsequent soil moisture responses synchronized to the temperature data are also included in the model simulation. The simulation shows the temperature response of buried objects due to changes in incoming solar radiation, air/surface soil temperature changes, latent heat exchange between the objects and surrounding soil, and impacts due to precipitation/changes in soil moisture. Differences are noted between the thermal response of plastic and metal objects as well as depth of burial below the ground surface. Nearly identical environmental conditions on different days did not always elicit the same spatial thermal response.
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Wolfenson, David, William W. Thatcher, Rina Meidan, Charles R. Staples, and Israel Flamenbaum. Hormonal and Nutritional Stretegies to Optimize Reproductive Function and Improve Fertility of Dairy Cattle during Heat Stress in Summer. United States Department of Agriculture, August 1994. http://dx.doi.org/10.32747/1994.7568773.bard.

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The BARD program includes two main parts. In the first, experiments were conducted to complete our understanding of the mechanisms responsible for the impairment of reproductive functions under heat stress. Experiments focused on follicular development and function, since results obtained in our previous BARD project indicate that the preovulatory follicle is susceptible to heat stress. The theca cells, sensitive to thermal stress, produced less androgen during the summer, as well as during the autumn. Similarly, luteinized theca cells obtained from cows in summer produced much less progesterone than in winter. Granulosa cells and luteinized granulosa cells were less susceptible to heat stress. A delayed effect of heat stress on follicular development, on suppression of dominance and on steroid production by theca and granulosa cells was noted. This may be related to the low fertility of cows during the cool months of autumn. In the second part, experiments were conducted aiming to improve fertility in summer. The timed AI program was developed using two injections of GnRH coupled with PGF2a. It was found effective in improving reproductive performance in lactating cows. Limitations induced by heat stress on estrus detection were eliminated with the timed AI management program. Replacing the second injection of GnRH with hCG instead of GnRH agonist increased plasma progesterone levels post ovulation but did not improve fertility. Use of the timed AI program in summer, shortened days open and increased the net revenue per cow, however, it did not protect the embryo fiom temperature-induced embryonic mortality. Incorporation of a GnRH-agonist implant into the timed AJ program was examined. The implant increased plasma progesterone and LH concentrations and altered follicular dynamics. The use of a GnRH-implant enhanced pregnancy rate in cows with low body conditions. In a timed embryo transfer experiment, the use of fresh or frozen in vitro produced embryos was compared in the summer to improve fertility. The use of flesh embryos (but not frozen ones) improved pregnancy rate, however, substantial embryonic death occurred between 21 and 45 days. The timed AI program, which is now being used commercially, shortened days open, and increased pregnancy rate during summer. Other approaches which were found to improve fertility in small-scale studies, need to be tested again in large-scale field trials.
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Weinschenk, Craig, Daniel Madrzykowski, and Paul Courtney. Impact of Flashover Fire Conditions on Exposed Energized Electrical Cords and Cables. UL Firefighter Safety Research Institute, October 2019. http://dx.doi.org/10.54206/102376/hdmn5904.

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A set of experiments was conducted to expose different types of energized electrical cords for lamps, office equipment, and appliances to a developing room fire exposure. All of the cords were positioned on the floor and arranged in a manner to receive a similar thermal exposure. Six types of cords commonly used as power supply cords, extension cords, and as part of residential electrical wiring systems were chosen for the experiments. The non-metallic sheathed cables (NMB) typically found in residential electrical branch wiring were included to provide a link to previous research. The basic test design was to expose the six different types of cords, on the floor of a compartment to a growing fire to determine the conditions under which the cord would trip the circuit breaker and/or undergo an arc fault. All of the cords would be energized and installed on a non-combustible surface. Six cord types (18-2 SPT1, 16-3 SJTW, 12-2 NM-B, 12-3 NM-B, 18-3 SVT, 18-2 NISPT-2) and three types of circuit protection (Molded case circuit breaker (MCCB), combination Arc-fault circuit interrupter (AFCI), Ground-fault circuit interrupter (GFCI)) were exposed to six room-scale fires. The circuit protection was remote from the thermal exposure. The six room fires consisted of three replicate fires with two sofas as the main fuel source, two replicate fires with one sofa as the main fuel source and one fire with two sofas and MDF paneling on three walls in the room. Each fuel package was sufficient to support flashover conditions in the room and as a result, the impact on the cords and circuit protection was not significantly different. The average peak heat release rate of the sofa fueled compartment fires with gypsum board ceiling and walls was 6.8 MW. The addition of vinyl covered MDF wall paneling on three of the compartment walls increased the peak heat release rate to 12 MW, although most of the increased energy release occurred outside of the compartment opening. In each experiment during post flashover exposure, the insulation on the cords ignited and burned through, exposing bare conductor. During this period the circuits faulted. The circuit protection devices are not designed to provide thermal protection, and, thus, were installed remote from the fire. The devices operated as designed in all experiments. All of the circuit faults resulted in either a magnetic trip of the conventional circuit breaker or a ground-fault trip in the GFCI or AFCI capable circuit protection devices. Though not required by UL 1699, Standard for Safety for Arc-Fault Circuit-Interrupters as the solution for detection methodology, the AFCIs used had differential current detection. Examination of signal data showed that the only cord types that tripped with a fault to ground were the insulated conductors in non-metallic sheathed cables (12-2 NM-B and 12-3 NM-B). This was expected due to the bare grounding conductor present. Assessments of both the thermal exposure and physical damage to the cords did not reveal any correlation between the thermal exposure, cord damage, and trip type.
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Treadwell, Jonathan R., James T. Reston, Benjamin Rouse, Joann Fontanarosa, Neha Patel, and Nikhil K. Mull. Automated-Entry Patient-Generated Health Data for Chronic Conditions: The Evidence on Health Outcomes. Agency for Healthcare Research and Quality (AHRQ), March 2021. http://dx.doi.org/10.23970/ahrqepctb38.

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Background. Automated-entry consumer devices that collect and transmit patient-generated health data (PGHD) are being evaluated as potential tools to aid in the management of chronic diseases. The need exists to evaluate the evidence regarding consumer PGHD technologies, particularly for devices that have not gone through Food and Drug Administration evaluation. Purpose. To summarize the research related to automated-entry consumer health technologies that provide PGHD for the prevention or management of 11 chronic diseases. Methods. The project scope was determined through discussions with Key Informants. We searched MEDLINE and EMBASE (via EMBASE.com), In-Process MEDLINE and PubMed unique content (via PubMed.gov), and the Cochrane Database of Systematic Reviews for systematic reviews or controlled trials. We also searched ClinicalTrials.gov for ongoing studies. We assessed risk of bias and extracted data on health outcomes, surrogate outcomes, usability, sustainability, cost-effectiveness outcomes (quantifying the tradeoffs between health effects and cost), process outcomes, and other characteristics related to PGHD technologies. For isolated effects on health outcomes, we classified the results in one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. When we categorized the data as “unclear” based solely on health outcomes, we then examined and classified surrogate outcomes for that particular clinical condition. Findings. We identified 114 unique studies that met inclusion criteria. The largest number of studies addressed patients with hypertension (51 studies) and obesity (43 studies). Eighty-four trials used a single PGHD device, 23 used 2 PGHD devices, and the other 7 used 3 or more PGHD devices. Pedometers, blood pressure (BP) monitors, and scales were commonly used in the same studies. Overall, we found a “possible positive effect” of PGHD interventions on health outcomes for coronary artery disease, heart failure, and asthma. For obesity, we rated the health outcomes as unclear, and the surrogate outcomes (body mass index/weight) as likely no effect. For hypertension, we rated the health outcomes as unclear, and the surrogate outcomes (systolic BP/diastolic BP) as possible positive effect. For cardiac arrhythmias or conduction abnormalities we rated the health outcomes as unclear and the surrogate outcome (time to arrhythmia detection) as likely positive effect. The findings were “unclear” regarding PGHD interventions for diabetes prevention, sleep apnea, stroke, Parkinson’s disease, and chronic obstructive pulmonary disease. Most studies did not report harms related to PGHD interventions; the relatively few harms reported were minor and transient, with event rates usually comparable to harms in the control groups. Few studies reported cost-effectiveness analyses, and only for PGHD interventions for hypertension, coronary artery disease, and chronic obstructive pulmonary disease; the findings were variable across different chronic conditions and devices. Patient adherence to PGHD interventions was highly variable across studies, but patient acceptance/satisfaction and usability was generally fair to good. However, device engineers independently evaluated consumer wearable and handheld BP monitors and considered the user experience to be poor, while their assessment of smartphone-based electrocardiogram monitors found the user experience to be good. Student volunteers involved in device usability testing of the Weight Watchers Online app found it well-designed and relatively easy to use. Implications. Multiple randomized controlled trials (RCTs) have evaluated some PGHD technologies (e.g., pedometers, scales, BP monitors), particularly for obesity and hypertension, but health outcomes were generally underreported. We found evidence suggesting a possible positive effect of PGHD interventions on health outcomes for four chronic conditions. Lack of reporting of health outcomes and insufficient statistical power to assess these outcomes were the main reasons for “unclear” ratings. The majority of studies on PGHD technologies still focus on non-health-related outcomes. Future RCTs should focus on measurement of health outcomes. Furthermore, future RCTs should be designed to isolate the effect of the PGHD intervention from other components in a multicomponent intervention.
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