Development and Preliminary Validation of Heart Rate and Breathing Rate Detection Using a Passive, Ballistocardiography-Based Sleep Monitoring System

2009 ◽  
Vol 13 (1) ◽  
pp. 111-120 ◽  
Author(s):  
D.C. Mack ◽  
D.C. Mack ◽  
J.T. Patrie ◽  
P.M. Suratt ◽  
R.A. Felder ◽  
...  
Keyword(s):  
Heart Rate ◽  
Monitoring System ◽  
Breathing Rate ◽  
Sleep Monitoring ◽  
Preliminary Validation

scholarly journals Sensor Based Automatic Neonate Respiration Monitoring System

2019 ◽  
Vol 9 (2) ◽  
pp. 1296-1299
Keyword(s):  
Heart Rate ◽  
Internet Of Things ◽  
Monitoring System ◽  
Respiratory System ◽  
Medical Information ◽  
Low Cost ◽  
Research Work ◽  
Breathing Rate ◽  
Flow Sensors ◽  
Respiration Monitoring

This research work aims to create awareness and monitor the breath rate of a neonate using the air flow sensors and to reduce the number of infants’ death. It is designed based on the Arduino which is open-source electronics platform for hardware and software use. This prototype is developed for reliable and efficient baby monitoring system and play as infant care and monitoring system.A cardio respiratory system is used to monitor the infant’s heart rate, rhythm, breathing rate and other relevant and useful medical information using Electro Cardio Graph (ECG) and other IoT (Internet of Things) devices.This research work proved that the respiration monitoring system for infants can be implemented at low cost and also can prevent the respiration failure deaths.

scholarly journals LI-Care: A LabVIEW and IoT Based eHealth Monitoring System

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3137
Author(s):  
Kunjabihari Swain ◽  
Murthy Cherukuri ◽  
Sunil Kumar Mishra ◽  
Bhargav Appasani ◽  
Suprava Patnaik ◽  
...  
Keyword(s):  
Heart Rate ◽  
Monitoring System ◽  
Virtual Instrument ◽  
Diastolic Pressure ◽  
Systolic Pressure ◽  
Attractive Alternative ◽  
Breathing Rate ◽  
Oxygen Level ◽  
Web Based ◽  
Rms Errors

This paper presents a Laboratory Virtual Instrument Engineering Workbench (LabVIEW) and Internet of Things (IoT)-based eHealth monitoring system called LI-Care to facilitate the diagnosis of the health condition cost-effectively. The system measures the heart rate, body temperature, blood pressure, oxygen level, and breathing rate, and provides an electrocardiogram (ECG). The required sensors are integrated on a web-based application that keeps track of the essential parameters and gives an alarm indication if one or more physiological parameters go beyond the safe level. It also employs a webcam to obtain the patient view at any time. LabVIEW enables the effortless interfacing of various biomedical sensors with the computer and provides high-speed data acquisition and interactive visualizations. It also provides a web publishing tool to access the interactive window remotely through a web browser. The web-based application is accessible to doctors who are experts in that particular field. They can obtain the real-time reading and directly perform a diagnosis. The parameters measured by the proposed system were validated using the traditional measurement systems, and the Root Mean Square (RMS) errors were obtained for the various parameters. The maximum RMS error as a percentage was 0.159%, which was found in the temperature measurement, and its power consumption is 1 Watt/h. The other RMS errors were 0.05% in measurement of systolic pressure, 0.029% in measurement of diastolic pressure, 0.059% in measurement of breathing rate, 0.002% in measurement of heart rate, 0.076% in measurement of oxygen level, and 0.015% in measurement of ECG. The low RMS errors and ease of deployment make it an attractive alternative for traditional monitoring systems. The proposed system has potential applications in hospitals, nursing homes, remote monitoring of the elderly, non-contact monitoring, etc.

scholarly journals Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5651
Author(s):  
Gaëlle Prigent ◽  
Kamiar Aminian ◽  
Tiago Rodrigues ◽  
Jean-Marc Vesin ◽  
Grégoire P. Millet ◽  
...  
Keyword(s):  
Heart Rate ◽  
Fourier Transform ◽  
Monitoring System ◽  
Breathing Rate ◽  
Harmonic Frequency ◽  
Short Term ◽  
Rr Intervals ◽  
Frequency Tracking ◽  
Wide Range ◽  
Band Pass

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.

IOT based Heart Attack Detection & Heart Rate Monitoring System

2020 ◽  
Author(s):  
Suchitra Giri ◽  
Ujjwal Kumar ◽  
Varsha Sharma ◽  
Satish Kumar ◽  
Sikha Kumari ◽  
...  
Keyword(s):  
Heart Rate ◽  
Monitoring System ◽  
Heart Attack ◽  
Attack Detection ◽  
Heart Rate Monitoring

scholarly journals Noncontact Sleep Monitoring System under a Mattress

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Xu Jiao ◽  
Xiaosha Wang ◽  
Xiaohang Wang ◽  
Zipeng Liu
Keyword(s):  
Monitoring System ◽  
Sleep Monitoring

Changes in Blood Pressure, Heart Rate and Breathing Rate During Moderate Swimming Activity in Rainbow Trout

1967 ◽  
Vol 46 (2) ◽  
pp. 307-315 ◽  
Author(s):  
E. DON STEVENS ◽  
D. J. RANDALL
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Rainbow Trout ◽  
Venous Blood ◽  
The Body ◽  
Swimming Activity ◽  
Breathing Rate ◽  
Blood Pressures ◽  
Ventral Aorta ◽  
Pressure Changes

1. Changes in blood pressure in the dorsal aorta, ventral aorta and subintestinal vein, as well as changes in heart rate and breathing rate during moderate swimming activity in the rainbow trout are reported. 2. Blood pressures both afferent and efferent to the gills increased during swimming and then returned to normal levels within 30 min. after exercise. 3. Venous blood pressure was characterized by periodic increases during swimming. The pressure changes were not in phase with the body movements. 4. Although total venous return to the heart increased during swimming, a decreased blood flow was recorded in the subintestinal vein. 5. Heart rate and breathing rate increased during swimming and then decreased when swimming ceased. 6. Some possible mechanisms regulating heart and breathing rates are discussed.

INFLUENCE OF THE AGE ON BAROREFLEX SYNCHRONIZATION OF ARTERIAL PRESSURE AND HEART RATE DURING THE PASSIVE STANDING TEST

2021 ◽  
Vol 55 (1) ◽  
pp. 46-50
Author(s):  
Е.А. Orlova ◽  
◽  
О.S. Tarasova ◽  
V.D. Son'kin ◽  
А.S. Borovik ◽  
...  
Keyword(s):  
Heart Rate ◽  
Phase Synchronization ◽  
Tilt Test ◽  
Breathing Rate ◽  
Age Related ◽  
Head Up Tilt ◽  
Wave Range ◽  
Standing Test ◽  
Head Up Tilt Test ◽  
Over 40 Years

Age-related changes in phase synchronization of spontaneous blood pressure (BP) and heart rate (HR) fluctuations within the baroreflex wave range (about 0.1 Hz) were studied in 66 subjects aged 20 to 52 years. Measurements performed during the head-up tilt test included continuous BP monitoring using the volume-compensation method, ECG recording for ensuing HR calculation, and breathing rate recording. The phase synchronization index (PSI) was used for evaluation of BP-HR coupling. In supine position, phase synchronization in the subjects over 40 years was higher as compared with their counterparts at the age of 20 to 24 years. Along with that, less pronounced PSI increase in people over 40 in response to the tilt test suggests a decline of the baroreflex activity with aging.

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