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

2020 ◽  
Vol 17 (1) ◽  
pp. 7599-7606
Author(s):  
M. A. H. Mohd Adib ◽  
N. H. M. Hasni
Keyword(s):  
Heart Rate ◽  
Mobile Applications ◽  
Good Accuracy ◽  
Rate Measurement ◽  
Road Accidents ◽  
Heart Rate Monitoring ◽  
Physical Conditions ◽  
Car Accidents ◽  
Heart Rate Level ◽  
Main Components

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.

scholarly journals Improved Heart-Rate Measurement from Mobile Face Videos

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 663 ◽  
Author(s):  
Jean-Pierre Lomaliza ◽  
Hanhoon Park
Keyword(s):  
Heart Rate ◽  
Motion Tracking ◽  
Accurate Method ◽  
Head Motion ◽  
Computation Method ◽  
Facial Features ◽  
Rate Measurement ◽  
Heart Rate Monitoring ◽  
Desktop Computer ◽  
Heart Rate Measurement

Newtonian reaction to blood influx into the head at each heartbeat causes subtle head motion at the same frequency as the heartbeats. Thus, this head motion can be used to estimate the heart rate. Several studies have shown that heart rates can be measured accurately by tracking head motion using a desktop computer with a static camera. However, implementation of vision-based head motion tracking on smartphones demonstrated limited accuracy due to the hand-shaking problem caused by the non-static camera. The hand-shaking problem could not be handled effectively with only the frontal camera images. It also required a more accurate method to measure the periodicity of noisy signals. Therefore, this study proposes an improved head-motion-based heart-rate monitoring system using smartphones. To address the hand-shaking problem, the proposed system leverages the front and rear cameras available in most smartphones and dedicates each camera to tracking facial features that correspond to head motion and background features that correspond to hand-shaking. Then, the locations of facial features are adjusted using the average point of the background features. In addition, a correlation-based signal periodicity computation method is proposed to accurately separate the true heart-rate-related component from the head motion signal. The proposed system demonstrates improved accuracy (i.e., lower mean errors in heart-rate measurement) compared to conventional head-motion-based systems, and the accuracy is sufficient for daily heart-rate monitoring.

scholarly journals Students Activity Recognition by Heart Rate Monitoring in Classroom using K-Means Classification

2020 ◽  
Vol 6 (1) ◽  
pp. 46
Author(s):  
Hadi Helmi Md Zuraini ◽  
Waidah Ismail ◽  
Rimuljo Hendradi ◽  
Army Justitia
Keyword(s):  
Heart Rate ◽  
Activity Recognition ◽  
Student Behavior ◽  
Exercise Heart Rate ◽  
Rate Measurement ◽  
Teaching Session ◽  
Heart Rate Monitoring ◽  
Student Reaction ◽  
Heart Rate Measurement

Background: Heartbeat playing the main roles in our life. With the heartbeat, the anxiety level can be known. Most of the heartbeat is used in the exercise. Heart rate measurement is unique and uncontrollable by any human being.Objective: This research aims to learn student’s actions by monitoring the heart rate. In this paper, we are measuring the student reaction and action in classroom can give impact on teacher’s way of delivery when in the teaching session. In monitoring, student’s behavior may give feedback whether the teaching session have positive or negative outcome.Methods: The method we use is K-Means algorithm. Firstly, we need to know the student’s normal heartbeat as benchmark. We used Hexiware for collecting data from students’ hear beat. We perform the classification where K is benchmark students’ heartbeat. K-Means algorithm performs classification of the heart rate measurement of students.Results: We did the testing for five students in different subjects. It shows that all students have anxiety during the testing and presentation. Its consistency because we tested 5 students with mixes activities in the classroom, where the student has quiz, presentation and only teaching.Conclusion: Heart rate during studying in the classroom can change the education world in improving the efficiency of knowledge transfer between student and teacher. This research may act as basic way in monitoring student behavior in the classroom. We have tested for 5 students. Three students have their anxiety in classroom during the exam, presentation, and question. Two students have normal rate during the seminar and lecturer. The drawback, Hexiware is capturing average of ten minutes and tested in different classes and students. In future, we need just measure one student for all the subjects and Hexiware need to configure in one minute. 

scholarly journals Heart rate monitoring mobile applications

mHealth ◽  
2016 ◽  
Vol 2 ◽  
pp. 17-17 ◽  
Author(s):  
Beenish Chaudhry
Keyword(s):  
Heart Rate ◽  
Mobile Applications ◽  
Heart Rate Monitoring

scholarly journals Extracting Heart Rate Variability: A Summary of Camera Based Photoplethysmograph

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Rejwana Islam ◽  
Mousumi Sarmin ◽  
Farzana Akter Dulia ◽  
Moinul Islam Sayed
Keyword(s):  
Heart Rate ◽  
Video Processing ◽  
Physiological State ◽  
Physical Contact ◽  
Rate Measurement ◽  
Heart Rate Monitoring ◽  
Monitoring Methods ◽  
Secondary Sources ◽  
Advantages And Disadvantages ◽  
Electrocardiogram Ecg

Heart rate is one of the major indicators of our physiological state. An irregular or rapid heartbeat, fainting, dizziness, chest pain or shortness of breath can be found by it. The traditional heart rate observing methods such as electrocardiogram (ECG) require physical contact in order to show the heart rate reading exactly but this is uncomfortable for regular monitoring. Techniques for measuring physiological parameters remotely from hospital, as well as monitoring patients continuously, have been one of the major concerns of the scholars. Many heart rate measurement methods using smartphone, webcam, commercial camera etc. have been proposed by many researchers. Image or video processing is the fundamental technique for measuring heart rate through smartphone. With the aim of exploring different heart rate monitoring methods and the advantages and disadvantages, the present study consulted secondary sources like published articles.

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