Design and Clinical Evaluation of a Non-Contact Heart Rate Variability Measuring Device

The object of the proposed paper is to design and analyze the performance of a non-contact heart rate variability (HRV) measuring device based on ultrasound transducers. The rationale behind non-contact HRV measurement is the goal of obtaining a means of long term monitoring of a patient’s heart performance. Due to its complexity as a non-contact measuring device, influential physical quantities, error source and other perturbations were thoroughly investigated. For medical purposes it is of utmost importance to define the target uncertainty of a measuring method from the side of physicians, while it is the role of scientists to realistically evaluate all uncertainty contributions. Within this paper we present a novelty method of non-contact HRV measurement based on ultrasound transducers operating at two frequencies simultaneously. We report laboratory results and clinical evaluations are given for healthy subjects as well as patients with known heart conditions. Furthermore, laboratory tests were conducted on subjects during a relaxation period, and after 1 min physical activity

[1]  Andrew E. Kilding,et al.  Training Adaptation and Heart Rate Variability in Elite Endurance Athletes: Opening the Door to Effective Monitoring , 2013, Sports Medicine.

[2]  Noah S. Philip,et al.  Heart Rate Variability Responses to a Standardized Virtual Reality Exposure in Veterans with PTSD , 2017, Current Treatment Options in Psychiatry.

[3]  P. Laguna,et al.  Detection of driver's drowsiness by means of HRV analysis , 2011, 2011 Computing in Cardiology.

[4]  M. Munih,et al.  Psychophysiological Responses to Robotic Rehabilitation Tasks in Stroke , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[5]  A. Enis Cetin,et al.  Resting heart rate estimation using PIR sensors , 2017 .

[6]  U. Rajendra Acharya,et al.  Heart rate variability: a review , 2006, Medical and Biological Engineering and Computing.

[7]  Janko Drnovsek,et al.  Non-contact heart rate and heart rate variability measurements: A review , 2014, Biomed. Signal Process. Control..

[8]  Ludger Grote,et al.  Finger plethysmography—a method for monitoring finger blood flow during sleep disordered breathing , 2003, Respiratory Physiology & Neurobiology.

[9]  Tzyy-Ping Jung,et al.  Dry-Contact and Noncontact Biopotential Electrodes: Methodological Review , 2010, IEEE Reviews in Biomedical Engineering.

[10]  M. Shea,et al.  670. Heart Rate Variability Responses to a Standardized Virtual Reality Exposure in Veterans with PTSD , 2017, Biological Psychiatry.

[11]  Colin H. Hansen,et al.  A Review of Current Ultrasound Exposure Limits , 2004 .

[12]  A. Tomar,et al.  A Review Paper on Analysis ofElectrocardiograph (ECG) Signal for theDetection of Arrhythmia Abnormalities , 2014 .

[13]  Interim guidelines on limits of human exposure to airborne ultrasound. International Non-Ionizing Radiation Committee of the International Radiation Protection Association. , 1984, Health physics.

[14]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[15]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[16]  Massimo Pagani,et al.  Heart rate variability to monitor performance in elite athletes: Criticalities and avoidable pitfalls. , 2017, International journal of cardiology.

[17]  A. Aubert,et al.  Heart Rate Variability in Athletes , 2003, Sports medicine.

[18]  Janko Drnovsek,et al.  Novel Methods for Noncontact Heart Rate Measurement: A Feasibility Study , 2014, IEEE Transactions on Instrumentation and Measurement.

[19]  Kathleen R. Bell,et al.  Improvement in Heart Rate Variability during Mild Cognitive Task Following Concussion , 2017 .

[20]  Xiaopei Wu,et al.  Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions , 2017, BioMedical Engineering OnLine.

[21]  Ethan B. Blackford,et al.  Measuring pulse rate variability using long-range, non-contact imaging photoplethysmography , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[22]  Pierre-Emmanuel Calmel,et al.  An audio processing , 2011 .

[23]  Guohua Lu,et al.  Limitations of Oximetry to Measure Heart Rate Variability Measures , 2009, Cardiovascular engineering.

[24]  Peter Rossiter,et al.  Applying neural network analysis on heart rate variability data to assess driver fatigue , 2011, Expert Syst. Appl..

[25]  A. Aubert,et al.  Wavelet decomposition analysis of heart rate variability in aerobic athletes , 2001, Autonomic Neuroscience.

[26]  Mirza Mansoor Baig,et al.  A comprehensive survey of wearable and wireless ECG monitoring systems for older adults , 2013, Medical & Biological Engineering & Computing.

[27]  C. Colleta,et al.  Autonomic nervous system and subjective ratings of strain in air-traffic control , 2008 .

[28]  Ghaïs El Zein,et al.  Multitunable microwave system for touchless heartbeat detection and heart rate variability extraction , 2010 .

[29]  J. Sztajzel.  Heart rate variability: a noninvasive electrocardiographic method to measure the autonomic nervous system. , 2004, Swiss medical weekly.