scholarly journals Blood Volume Pulse Extraction for Non-Contact Heart Rate Measurement by Digital Camera Using Singular Value Decomposition and Burg Algorithm

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1076 ◽  
Author(s):  
Iman Tayibnapis ◽  
Yeon-Mo Yang ◽  
Ki Lim
Keyword(s):  
Heart Rate ◽  
Singular Value Decomposition ◽  
Blood Volume ◽  
Digital Camera ◽  
Singular Value ◽  
Rate Measurement ◽  
Value Decomposition ◽  
Pulse Extraction ◽  
Volume Pulse ◽  
Blood Volume Pulse

scholarly journals High Accuracy Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition and Matched Filter

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi
Keyword(s):  
Heart Rate ◽  
Singular Value Decomposition ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Matched Filter ◽  
Singular Value ◽  
Home Healthcare ◽  
Body Motion ◽  
Sitting Posture ◽  
Value Decomposition

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.

Artifact Removal from Data Generated by Nonlinear Systems: Heart Rate Estimation from Blood Volume Pulse Signal

2019 ◽  
Vol 59 (6) ◽  
pp. 2318-2327 ◽  
Author(s):  
Mohammad Reza Askari ◽  
Mudassir Rashid ◽  
Mert Sevil ◽  
Iman Hajizadeh ◽  
Rachel Brandt ◽  
...  
Keyword(s):  
Heart Rate ◽  
Nonlinear Systems ◽  
Blood Volume ◽  
Pulse Signal ◽  
Artifact Removal ◽  
Rate Estimation ◽  
Volume Pulse ◽  
Heart Rate Estimation ◽  
Blood Volume Pulse

A Simple and Novel Integrated Opto-Electronic System for Blood Volume Pulse Sensing and Heart Rate Monitoring

2007 ◽  
Vol 1 (4) ◽  
pp. 392-403 ◽  
Author(s):  
Vadakke Kadangote Jayasree ◽  
Palackappillil Jacob Shaija ◽  
Vadakkedathu Parameswaran Narayanan Nampoori ◽  
Chakkalakkal Pavothil Girijavallabhan ◽  
Padmanabhan Radhakrishnan
Keyword(s):  
Heart Rate ◽  
Blood Volume ◽  
Electronic System ◽  
Heart Rate Monitoring ◽  
Volume Pulse ◽  
Blood Volume Pulse

325 Stress-Induced Physiological Profiles Among Different Phenotype Insomniacs

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A130-A130
Author(s):  
Ya-Chuan Huang ◽  
Hsin-Chien Lee ◽  
Chien-Ming Yang
Keyword(s):  
Heart Rate ◽  
Body Temperature ◽  
Sleep Duration ◽  
Blood Volume ◽  
Respiration Rate ◽  
Skin Conductance ◽  
Resting State ◽  
Short Sleep Duration ◽  
Volume Pulse ◽  
Blood Volume Pulse

Abstract Introduction Stress reactivity and autonomic nervous system (ANS) dysregulation have been suggested to be the pathophysiology of insomnia. Based on the finding PSG-measured short sleep duration was associated with higher morbidity of metabolic and cardiovascular disease. Vgontzas and Fernandez-Mandoza (2013) proposed that objective sleep duration is a biomarker for insomnia phenotypes. The phenotype with short objective sleep duration is associated with increased stress-related physiological hyperarousal. The present study aims to test this hypothesis by comparing the stress-induced cardiovascular reactivity between insomnia patients with short and long objective sleep durations. Methods 27 insomnia patients (age mean 34.48 ±12.87, Male: Female= 6:21) without comorbidity of psychiatric, medical or sleep disorders participated in this study. They went through one night of 8-hour PSG recording and were divided into two groups by their total sleep time with a cutoff of 6 hours. Nine participants were in short sleep duration group and 18 in longer sleep duration group. Psychophysiological reactivity profile, as recorded with EKG, skin conductance (SC), body temperature (BT), blood volume pulse (BVP), respiration rate (RR), was measured under three conditions: baseline resting state, arithmetic word problems solving, and recovery resting state. Results Both groups showed similar stress physiological response with increased heart rate (HR) and SC, nearly equivalent BT and BVP, and decreased RR when solving arithmetic problems, and opposite reaction during recovery resting state. Mann-Whitney U test comparing the changes from baseline resting state on all the psychophysiological measures between two phenotypes of insomnia showed no significant differences: stress-induced heart-rate (U=106, p=.119.) recovery heart-rate (U=44, p=.095), stress-induced skin conductance (U=104.5, p=.132),recovery skin conductance (U=51.5, p=.198), stress-induced body temperature (U=79, p=.897),recovery body temperature (U=60.5, p=.418), stress-induced blood volume pulse amplitude (U=77, p=1.0), and recovery blood volume pulse amplitude (U=69, p=.735), stress-induced respiration rate (U=76, p =.696), and recovery respiration rate (U=85, p=.658). Conclusion Our results indicate that the insomnia phenotypes with short and long objective sleep duration are not different in their stress-induced physiological responses. Future studies are needed to confirm these results and to explore other mechanisms for the increased metabolic and cardiovascular disease risk in insomnia patients with short objective sleep duration. Support (if any):

Garbage In; Garbage Out—Identify Blood Volume Pulse (BVP) Artifacts Before Analyzing and Interpreting BVP, Blood Volume Pulse Amplitude, and Heart Rate/Respiratory Sinus Arrhythmia Data

Biofeedback ◽  
2010 ◽  
Vol 38 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Erik Peper ◽  
Fred Shaffer ◽  
I-Mei Lin
Keyword(s):  
Heart Rate ◽  
Blood Volume ◽  
Pulse Signal ◽  
Pulse Amplitude ◽  
Peripheral Blood Flow ◽  
Close Inspection ◽  
Sinus Arrhythmia ◽  
Popular Method ◽  
Volume Pulse ◽  
Blood Volume Pulse

Abstract Blood volume pulse is a popular method for monitoring the relative changes in peripheral blood flow, heart rate, and heart rate variability. This article stresses the danger of blindly interpreting measures like heart rate, which are derived from blood volume pulse, without close inspection of the raw blood volume pulse signal. The authors identify common sources of signal contamination and recommend practical precautions and treatment of artifacts.

Reliability of Psychophysiological Responses Across Multiple Motion Sickness Stimulation Tests

1995 ◽  
Vol 5 (1) ◽  
pp. 25-33
Author(s):  
Cynthia S. Stout ◽  
William B. Toscano ◽  
Patricia S. Cowings
Keyword(s):  
Heart Rate ◽  
Motion Sickness ◽  
Blood Volume ◽  
Respiration Rate ◽  
Autonomic Response ◽  
Test Duration ◽  
Autonomic Responses ◽  
Symptom Level ◽  
Volume Pulse ◽  
Blood Volume Pulse

Although there is general agreement that a high degree of variability exists between subjects in their autonomic nervous system responses to motion sickness stimulation, very little evidence exists that examines the reproducibility of autonomic responses within subjects during motion sickness stimulation. Our objectives were to examine the reliability of autonomic responses and symptom levels across five testing occasions using the (1) final minute of testing, (2) change in autonomic response and the change in symptom level, and (3) strength of the relationship between the change in symptom level and the change in autonomic responses across the entire motion sickness test. The results indicate that, based on the final minute of testing, the autonomic responses of heart rate, blood volume pulse, and respiration rate are moderately stable across multiple tests. Changes in heart rate, blood volume pulse, respiration rate, and symptoms throughout the test duration are less stable across the tests. Finally, autonomic responses and symptom levels are significantly related across the entire motion sickness lest.

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