Heart Rate Monitor Device Research Articles

Development of a wearable device for heart rate monitoring and fall detection using machine learning to analyze and detect early anomaly of cardiovascular conditions

Cardiovascular disease is the leading cause of death globally. This research implements a system for monitoring heart rate, electrocardiogram, and providing alerts for potential risks to patients based on data collected using the LSTM machine learning model. The wearable device is compact in size with a long battery life. The information collected from the device can be remotely monitored by doctors through a visual interface on a web server model, and patients can self-monitor their electrocardiogram status through an application on a mobile device. By integrating the LSTM model into the design, this study has addressed two issues: predicting the trend of the electrocardiogram signal and detecting abnormalities in the predicted signal. This allows users to self-monitor their personal status and doctors to better adjust the treatment method for the patient’s health.

Monitoring training, performance, biomarkers, and psychological state throughout a competitive season: a case study of a triathlete.

Ironman triathletes undergo high workloads during competition preparation which can result in nonfunctional overreaching or overtraining syndrome if not matched with adequate recovery. The purpose of this case study was to observe changes in physiological and psychological status over the course of a competitive season in a free-living triathlete. The subject was a 41-year-old triathlete competing in three 113.1-km events. Over the course of a 40-week period, the participant arrived at the laboratory every 4weeks and underwent body composition testing via air displacement plethysmography, a blood draw for analysis of various biomarkers, and a treadmill-based lactate threshold test. Workload during training and competitions was monitored via a wearable heart rate-monitoring device. Throughout the season, training volume remained high (12.5 ± 3.4h/week) and body mass and fat-free mass (FFM) continuously decreased, while biomarkers including cortisol, testosterone, and markers of immunological status exhibited minor changes. Laboratory performance remained relatively consistent, while competition performance continually improved. Following the completion of the competitive period, training volume decreased, FFM remained below baseline levels, free cortisol increased, and both free and total testosterone decreased. Workload and recovery seem to have been properly managed throughout the season, evidenced by minimal fluctuations in endocrine and immunological markers. The reason for changes observed in testosterone, cortisol, and body composition following the last competition is unclear, though it may be attributed to changes in stressors and recovery practices outside of training. It is recommended that athletes follow a structured plan during the transition period into the offseason to ensure recovery of physiological state and to set up a productive offseason.

Evaluation and patient experience of wireless noninvasive fetal heart rate monitoring devices.

In clinical practice, fetal heart rate monitoring is performed intermittently using Doppler ultrasound, typically for 30 minutes. In case of a non-reassuring heart rate pattern, monitoring is usually prolonged. Noninvasive fetal electrocardiography may be more suitable for prolonged monitoring due to improved patient comfort and signal quality. This study evaluates the performance and patient experience of four noninvasive electrocardiography devices to assess candidate devices for prolonged noninvasive fetal heart rate monitoring. Non-critically sick women with a singleton pregnancy from 24 weeks of gestation were eligible for inclusion. Fetal heart rate monitoring was performed during standard care with a Doppler ultrasound device (Philips Avalon-FM30) alone or with this Doppler ultrasound device simultaneously with one of four noninvasive electrocardiography devices (Nemo Fetal Monitoring System, Philips Avalon-Beltless, Demcon Dipha-16 and Dräger Infinity-M300). Performance was evaluated by: success rate, positive percent agreement, bias, 95% limits of agreement, regression line, root mean square error and visual agreement using FIGO guidelines. Patient experience was captured using a self-made questionnaire. A total of 10 women were included per device. For fetal heart rate, Nemo performed best (success rate: 99.4%, positive percent agreement: 94.2%, root mean square error 5.1 BPM, bias: 0.5 BPM, 95% limits of agreement: -9.7 - 10.7 BPM, regression line: y = -0.1x + 11.1) and the cardiotocography tracings obtained simultaneously by Nemo and Avalon-FM30 received the same FIGO classification. Comparable results were found with the Avalon-Beltless from 36 weeks of gestation, whereas the Dipha-16 and Infinity-M300 performed significantly worse. The Avalon-Beltless, Nemo and Infinity-M300 closely matched the performance of the Avalon-FM30 for maternal heart rate, whereas the performance of the Dipha-16 deviated more. Patient experience scores were higher for the noninvasive electrocardiography devices. Both Nemo and Avalon-Beltless are suitable devices for (prolonged) noninvasive fetal heart rate monitoring, taking their intended use into account. But outside its intended use limit of 36 weeks' gestation, the Avalon-Beltless performs less well, comparable to the Dipha-16 and Infinity-M300, making them currently unsuitable for (prolonged) noninvasive fetal heart rate monitoring. Noninvasive electrocardiography devices appear to be preferred due to greater comfort and mobility.

Willingness to use smart fetal heart rate monitoring devices among pregnant women: an extension of the technology acceptance model.

The purpose of this study was to assess the significant factors that impact pregnant women's willingness to use smart fetal heart-rate monitoring devices. We propose a research model that integrates technological factors (perceived compatibility and perceived credibility) and personal factors (health anxiety, personal physiological conditions, health consciousness, and health beliefs). The subjects of this study were Chinese women who were pregnant or had previously given birth. Data were collected and analyzed from 397 paper-and-pencil and electronic questionnaires. Our structural equation model indicated that perceived usefulness (β = 0.490, t = 7.591, p < 0.001), perceived ease of use (β = 0.352, t = 5.631, p < 0.001), health anxiety (β = 0.095, t = 2.664, p = 0.008), personal physiological conditions (β = 0.075, t = 2.142, p = 0.032), and health consciousness (β = 0.078, t = 2.110, p = 0.035) were the determinants of the intention to use smart fetal heart-rate monitoring devices, with perceived usefulness having the highest degree of influence. Furthermore, we discovered that the levels of perceived compatibility and perceived credibility did not have direct correlations with the intention to use these devices, but they did significantly influence the model. Perceived compatibility (β = 0.345, t = 6.601, p < 0.001) and perceived credibility (β = 0.519, t = 9.958, p < 0.001) significantly influences perceived ease of use. Perceived credibility (β = 0.421, t = 7.802, p < 0.001) significantly influences perceived usefulness. Based on these results, suggestions for future research are put forward.

Facile heart rate monitoring with multimodal capabilities

This paper presents the fabrication of a prototype with unique functionalities for monitoring human heart rate via simple insertion of fingertip on an infrared based sensor. The variation in the absorbance caused by the repeated pumping of oxygenated blood to various tissues within the body leads to distinct peaks and dips corresponding to the signal from the detector. Further, a MATLAB based Graphical User Interface (GUI) is developed to visualize this heart-beat signal as well as count the heart rate. In addition, the oxygen concentration can also be deciphered from the reported sensing scheme. The developed prototype seems to be in excellent match with standard heartrate monitoring device. It is believed that this multimodal prototype will pave way for more investigation towards development of sophisticated AI based analysis.

The regulatory properties of anger under different goal orientations: the effects of normative and outcome goals

BackgroundThe present study aimed to evaluate the self-regulatory properties of anger on the performance of individuals under various motivational dispositions using an experimental design.MethodsThe participants were 99 university students who participated in response to extra credit. The performance of the participants was evaluated using the Tower of Hanoi task. Their anger was measured using a facial expression recognition system and arousal was assessed using a heart-rate monitoring device. Two motivational dispositions were assessed: performance goals with normative evaluative standards and performance goals with a focus on outcomes.ResultsThe results indicated that a nonlinear function explained the relationship between anger, arousal, and achievement under different goal conditions. Specifically, the Cusp Catastrophe Model showed that anger levels beyond a critical point were associated with the unpredictability of performance during the normative goal condition, suggesting that anger disturbed the relationship between arousal and achievement. Interestingly, a linear model was relevant for explaining the same relationships during the outcome goal condition.ConclusionThus, this study concluded that anger plays a more salient role when coupled with the pressures arising from employing interpersonal evaluative standards.

Monte Carlo analysis of optical heart rate sensors in commercial wearables: the effect of skin tone and obesity on the photoplethysmography (PPG) signal.

Commercially available wearable devices have been used for fitness and health management and their demand has increased over the last ten years. These "general wellness" and heart-rate monitoring devices have been cleared by the Food and Drug Administration for over-the-counter use, yet anecdotal and more systematic reports seem to indicate that their error is higher when used by individuals with elevated skin tone and high body mass index (BMI). In this work, we used Monte Carlo modeling of a photoplethysmography (PPG) signal to study the theoretical limits of three different wearable devices (Apple Watch series 5, Fitbit Versa 2 and Polar M600) when used by individuals with a BMI range of 20 to 45 and a Fitzpatrick skin scale 1 to 6. Our work shows that increased BMI and skin tone can induce a relative loss of signal of up to 61.2% in Fitbit versa 2, 32% in Apple S5 and 32.9% in Polar M600 when considering the closest source-detector pair configuration in these devices.

Photoplethysmography Heart Rate Monitoring

Research conducted by the World Health Organisation (WHO) in 2018 demonstrated that the worldwide threat of cardiovascular diseases (CVDs) has increased compared to previous years. CVDs are very dangerous: if timely treatment is not performed, these conditions could become irreversible and lead to sudden death. Prescriptive measures include physical exercises and monitoring of the heart rate (HR). Despite the existence of various HR monitoring devices (or HMDs), a major challenge remains their availability, particularly to people in lower-income countries. Unfortunately, it is also this segment of the population that is the most vulnerable to CVDs. Accordingly, this led the authors to propose the design for an easily constructible state-of-the-art HMD that attempts to provide a highly accessible, lower-cost, and long-lasting solution that would be more affordable and accessible to these low-income communities.

A New Approach for Testing Fetal Heart Rate Monitors.

In this paper, a new approach for the periodical testing and the functionality evaluation of a fetal heart rate monitor device based on ultrasound principle is proposed. The design and realization of the device are presented, together with the description of its features and functioning tests. In the designed device, a relay element, driven by an electric signal that allows switching at two specific frequencies, is used to simulate the fetus and the mother’s heartbeat. The simulator was designed to be compliant with the standard requirements for accurate assessment and measurement of medical devices. The accuracy of the simulated signals was evaluated, and it resulted to be stable and reliable. The generated frequencies show an error of about 0.5% with respect to the nominal one while the accuracy of the test equipment was within ±3% of the test signal set frequency. This value complies with the technical standard for the accuracy of fetal heart rate monitor devices. Moreover, the performed tests and measurements show the correct functionality of the developed simulator. The proposed equipment and testing respect the technical requirements for medical devices. The features of the proposed device make it simple and quick in testing a fetal heart rate monitor, thus providing an efficient way to evaluate and test the correlation capabilities of commercial apparatuses.

Enhanced Brady-Tachy Heart Automotive (BT-Heartomotive) Device for Heart Rate Monitoring during Driving

Driving with brady-tachy syndrome is one of the main causes of car accidents. In order to prevent drivers from brady-tachy driving, there is a strong demand for driver monitoring systems. Other than problems in driving attitudes and skills, road accidents are also caused by uncontrollable factors such as medical conditions and drowsiness. These factors can be avoided by having early detection. Therefore, the brady-tachy heart automotive so-called BT-Heartomotive device is developed. This BT-Heartomotive device can detect early signs of drowsiness and health problems by measuring the heart rate of the drivers during driving. The device also could use the data to send an alert to the passengers that they’re in precaution. The device shows a good accuracy in the detection of the heart rate level. The device comprised three main components; wristband, monitor and integrated mobile applications. Heart rate measurement can reveal a lot about the physical conditions of an individual. The BT-Heartomotive device is simple, easy to use and automated.

Machine learning detection of Atrial Fibrillation using wearable technology.

BackgroundAtrial Fibrillation is the most common arrhythmia worldwide with a global age adjusted prevalence of 0.5% in 2010. Anticoagulation treatment using warfarin or direct oral anticoagulants is effective in reducing the risk of AF-related stroke by approximately two-thirds and can provide a 10% reduction in overall mortality. There has been increased interest in detecting AF due to its increased incidence and the possibility to prevent AF-related strokes. Inexpensive consumer devices which measure the ECG may have the potential to accurately detect AF but do not generally incorporate diagnostic algorithms. Machine learning algorithms have the potential to improve patient outcomes particularly where diagnoses are made from large volumes or complex patterns of data such as in AF.MethodsWe designed a novel AF detection algorithm using a de-correlated Lorenz plot of 60 consecutive RR intervals. In order to reduce the volume of data, the resulting images were compressed using a wavelet transformation (JPEG200 algorithm) and the compressed images were used as input data to a Support Vector Machine (SVM) classifier. We used the Massachusetts Institute of Technology (MIT)—Beth Israel Hospital (BIH) Atrial Fibrillation database and the MIT-BIH Arrhythmia database as training data and verified the algorithm performance using RR intervals collected using an inexpensive consumer heart rate monitor device (Polar-H7) in a case-control study.ResultsThe SVM algorithm yielded excellent discrimination in the training data with a sensitivity of 99.2% and a specificity of 99.5% for AF. In the validation data, the SVM algorithm correctly identified AF in 79/79 cases; sensitivity 100% (95% CI 95.4%-100%) and non-AF in 328/336 cases; specificity 97.6% (95% CI 95.4%-99.0%).ConclusionsAn inexpensive wearable heart rate monitor and machine learning algorithm can be used to detect AF with very high accuracy and has the capability to transmit ECG data which could be used to confirm AF. It could potentially be used for intermittent screening or continuously for prolonged periods to detect paroxysmal AF. Further work could lead to cost-effective and accurate estimation of AF burden and improved risk stratification in AF.

Design and Performance Analysis of an Infra Red Based Heart Rate Monitoring System

The rate of the human heartbeat is an indication of the health status of the heart and circulatory system and many humans are potential candidates of stress-related health conditions due to the non-availability of a heart rate measuring device that is both affordable and easy to operate. This paper presents a study on the design and performance analysis of an efficient infrared based heart rate monitoring (HRM) system that is economical and portable. The heart rate is measured by placing the finger on an Infra-Red (IR) sensor unit composed of the IR Light Emitting Diode (LED) and a photo-diode. The heart rate is detected from the blood flow through the finger and the pulse signals pass through some filtering and amplification to be detected by the microcontroller. The HRM system employs a microcontroller, PIC16F628A which serves as a central processing unit (CPU) to process and analyze the heart beats detected as electrical signals from the IR sensor unit and converts the measured heart rate to a numerical value which is displayed via a 3-digit seven segment display. The designed HRM device is portable, durable and cost-effective. It can be used to monitor the human heart rate in both clinical and non-clinical environments with the advantage of being operated by non-professionals. The HRM system was tested in the laboratory and 50 samples of heart rates was analyzed to determine its performance level. The accuracy test results of the HRM device showed that the average error rate is 1.85%, when compared with a Blood Pressure Monitor. Hence, the performance of the HRM device is high with negligible error rate.

Innovations in Heart Rate Monitoring Devices and Smart Applications: Physical Configuration Matters!

Bluetooth/ANT+ heart rate monitors and smart device applications have the potential to advance heart rate monitoring in non-clinical settings. New innovative applications allow for heart rate monitoring of multiple users simultaneously; however, preliminary attempts to use a particular commercially available model in a typical university gymnasium setting revealed persistent issues with signal interruption; thus, the trustworthiness of the data was limited. PURPOSE: To reduce the prevalence of signal interruption by determining the best physical configuration of components. METHODS: A quasi-experimental repeated measures design was utilized to determine the best configuration of the system components. Cluster and ANOVA analyses determined good, better, and best configurations. The dependent variable was signal interruption and the unit of analyses was the number of signal interruptions per two-minute session. The independent variables were height (1.8m, 3.6m, and 5.4m), angle (60°, 75°, and 90°), and location (left corner, middle, right corner) of the transmitter component. University students, male and female adults ages 19-25 with no apparent health problems, were recruited to participate during undergraduate physical education teacher education lab classes. Participants were monitored while participating in physical activities during normal class sessions. Classes were conducted in a typical indoor gymnasium slightly larger than a single standard collegiate-sized basketball court. RESULTS: Inspection of the graphs and ANOVA analyses revealed that the best configuration of the system was transmitter device placement at a height of 1.8m’ F(2, 1,052) = 54.86, p < .001, partial η2 = .09, at a 60°angle F(2, 1,052) = 12.50, p < .001, partial η2 = .02, and in the left corner location F(2, 1,052) = 24.28, p < .001, partial η2 = .04. CONCLUSIONS: The height, angle, and location of the transmitter component all played a significant role in reducing the prevalence of signal interruption. It was determined that the best results were found with the lowest height and smallest angle chosen. Therefore, random placement of transmitter height, angle and location will not yield the best heart rate monitoring results.

Continuous heart rate monitoring for automatic detection of atrial fibrillation with novel bio-sensing technology

BackgroundAsymptomatic atrial fibrillation [AF] is an important cause of fatal or disabling stroke. A continuous heart-rate monitoring device, comfortable enough to be worn continuously and reliable enough to detect AF, would allow for prompt initiation of anticoagulation therapy to prevent stroke. MethodsWe studied a new custom-made wearable photo-plethysmograph [PPG] wrist-watch sensor, specifically designed for continuous heart rate monitoring and incorporating contact and motion noise-filters. We tested its ability to automatically detect AF in patients undergoing elective cardioversion of AF, using simultaneously recorded electrocardiogram [ECG] as gold standard. ResultsA total of 18,608 consecutive R-R-interval measurements were recorded simultaneously with PPG and ECG in 20 patients, including 12,521 [67.3%] R-R-intervals during AF and 6087 [32.7%] R-R intervals during sinus rhythm. Scatter plots and Bland-Altman plots demonstrated that the PPG signals were highly correlated to the simultaneously recorded ECG [R = 0.980, p < 0.001], both during AF and during sinus rhythm. The automatic algorithm distinguished AF from sinus rhythm with a sensitivity of 100% and specificity of 93.1%. ConclusionsThis PPG-based wrist-watch sensor reliably detected AF in non-ambulatory patients.

Fetal heart rate monitoring device using condenser microphone sensor: Validation and comparison to standard devices

Fetal heart rate (FHR) monitoring device is highly demanded to assess the fetus health condition in home environments. Conventional standard devices such as ultrasonography and cardiotocography are expensive, bulky and uncomfortable and consequently not suitable for long-term monitoring. Herein, we report a device that can be used to measure fetal heart rate in clinical and home environments. The proposed device measures and displays the FHR on a screen liquid crystal display (LCD). The device consists of hardware that comprises condenser microphone sensor, signal conditioning, microcontroller and LCD, and software that involves the algorithm used for processing the conditioned fetal heart signal prior to FHR display. The device's performance is validated based on analysis of variance (ANOVA) test. FHR data was recorded from 22pregnant women during the 17th to 37th week of gestation using the developed device and two standard devices; AngelSounds and Electronic Stethoscope. The results show that F-value (1.5) is less than F𝑐𝑟𝑖𝑡, (3.1) and p-value (p> 0.05). Accordingly, there is no significant difference between the mean readings of the developed and existing devices. Hence, the developed device can be used for monitoring FHR in clinical and home environments.

Vital Sign Monitoring Using Capacitive Sensing.

Unobtrusive vital sign monitoring is essential for most wearable monitoring applications. This paper presents a new method for unobtrusive vital sign monitoring based on the change in capacitance of passive sensors in contact with the user's body. Unlike traditional capacitive coupling that is commonly used for elimination of the DC component of bioamplifiers, we propose monitoring of heart rate using galvanically isolated capacitive sensors. This paper presents the theory of operation and the implementation of a prototype device for heart rate monitoring. A prototype capacitive sensor was implemented using parallel coplanar plates in contact with the tip of the finger. Preliminary testing allowed us to observe changes in capacitance in the range of 0.1-0.3 pF per heartbeat, or 0.3-0.9% of the measured signal. The detected heart rate was validated using a PPG sensor positioned on the same hand. During a single recording session of 772 s, the detected heart rate was within 3 BPM 42% of the time. Proposed method is sensitive to motion artefacts; however, processing of signals collected from multiple contact points may facilitate removal of motion artifacts. Since many microcontrollers directly support high quality monitoring of capacitance on multiple I/O pins, the proposed method provides a promising solution for a low-power, low-cost, multi-contact monitoring.

Design of heart rate monitor based on piezoelectric sensor using an Arduino

Reading of result heart rate using an acoustic stethoscope needs a particular skill, quiet environment, and hearing sensitivity. This project had the purpose design of a user-friendly automatic heart rate monitor and especially in a noisy area which to eliminate problems and incorrect reading of result. The liquid crystal display shows a heart rate as a result of measurements. The design of the heart rate monitor has two main parts; the signal recorder that a piezoelectric sensor, a filter, and an amplifier as recorder. The second parts was Arduino microcontroller with reinforced. Besides, three supporting buttons provided as the manual switches, the ‘on’, the ‘start’, and ‘reset’ buttons. The values acquired from the heart rate monitor indicate that those were on the Vernier BPS-BTA value range. The measurement error factor of the heart rate monitor then compared to the Vernier BPS-BTA test device was 3.15%. Besides, the value of statistical independent-test indicates that there is no significant difference (P = 0.971) between the heart rate monitor device and the Vernier BPS-BTA. In conclusion, this device was ready to be used because it has almost the same accuracy with the standart device.

Heart-rate Monitoring System Design and Analysis Using a Nios II Soft-core Processor

Abstract The heart rate of a person is able to tell whether they are healthy. A heart-rate monitoring device is able to measure or record the heart rate of a person in real time, whether it is an electrocardiogram (ECG) or a photoplethysmogram (PPG). In this work, a microprocessor system loaded with a heart-rate monitoring algorithm is implemented. The microprocessor system is the Nios II processor system, which interfaces with an analogue-to-digital converter (ADC) and a pulse sensor. A beat-finding algorithm is used in the microprocessor system for heart rate measurement. An experiment is carried out to analyse the functionality of the microprocessor system loaded with the algorithm. The results show that the detected heart rate is in the range of the average human being’s heart rate. The signal flow within the microprocessor system is observed and analysed using SignalTap II from Quartus’ software. Based on a power analysis report, the proposed microprocessor system has a total power dissipation of around 218.26 mW.

Predicting physical activity energy expenditure in wheelchair users with a multisensor device

AimTo assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration...

Developing An Improved Heart Rate Monitor With Work-Out Training Android Application And Real Time Audio Coaching

TechnoHeart is a digital way of monitoring heart rate using a Heart Rate Monitor device and an android phone. Moreover, this is made more special through its work-out training which is designed to help users set and achieve their target heart rate and monitor at what training intensity they are during a strenuous exercise. The training is made more interactive as the application has its real-time audio coaching. The need for this application comes from three sources; First, some athletes, non-athletes and even doctors are still using the traditional way of getting the heart rate; Second, training intensity is not monitored and target heart rate is not achieved; Third, most mobile developments do not tailor the need of users who undergo work-out training. With the following needs, objectives were set; First, to connect an HRM (Heart Rate Monitoring) device to an android mobile device and display individual’s heart rate in digital form through mobile; Second, to create a work-out training program using the Karvonen Formula; Third, to enable users to know one’s target heart rate by using a Karvonen calculator; Fourth, to notify users in real-time with every sudden change and the needed action in order to keep an effective training exercise. The project is to explore this and other similar concepts to develop a design that optimally satisfies all of these objectives. The project addresses all of these objectives while meeting the constraints given. The project was deployed in three different sets of users: The University of Mindanao Athletes, The elderly users aging from 50-80 years old and the other users aging from 12-49 years old. The researchers recommend the use of TechnoHeart for athletes and non-athletes who are aiming for effective cardiovascular training. And for the next researchers, they can focus on the compatibility of the said application to other mobile platforms like iOS, Blackberry, Windows and etc. And also, they may upload the application on the internet such as in social networking sites or any features that would make this project more usable.