Photoplethysmographic based heart rate variability for different physiological conditions

This paper investigates the feasibility of using photoplethysmographic (PPG) signal for heart rate variability (HRV) using different physiological conditions. In this paper, we have analyzed four physiological conditions i.e.; sitting, standing, laying and jogging. The Easy Pulse sensor module was...

Full description

Bibliographic Details
Main Authors:	Shah, Mansoor Hussain, Kazmi, Syed Absar, Sidek, Khairul Azami, Khan, Sheroz, Iqbal, Fatema-tuz-Zohra
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2014
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/41620/ http://irep.iium.edu.my/41620/ http://irep.iium.edu.my/41620/1/41620.pdf http://irep.iium.edu.my/41620/4/41620_Photoplethysmographic%20based%20heart%20rate.SCOPUS.pdf

id	iium-41620
recordtype	eprints
spelling	iium-416202018-05-17T02:02:41Z http://irep.iium.edu.my/41620/ Photoplethysmographic based heart rate variability for different physiological conditions Shah, Mansoor Hussain Kazmi, Syed Absar Sidek, Khairul Azami Khan, Sheroz Iqbal, Fatema-tuz-Zohra TK7885 Computer engineering This paper investigates the feasibility of using photoplethysmographic (PPG) signal for heart rate variability (HRV) using different physiological conditions. In this paper, we have analyzed four physiological conditions i.e.; sitting, standing, laying and jogging. The Easy Pulse sensor module was used to pass the signal sensed by the optical sensor through a series of high and low pass filters which later generates a conditioned PPG signal at its output. The Arduino processing module was used for the digitization and processing of the PPG signals. The Arduino program was then developed to capture the PPG data and waveforms. The Kubios HRV software was used to process the PPG data and manipulate it into a HRV format. The PPG signal was then analyzed in time and frequency domain parameters. Later, report sheets were generated based on these analyses. The results showed that the PPG signal as well as HRV changes depending upon the physiological conditions. It was also examined that the low and high frequency components of PPG signal also varied according to the change in physiological condition. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/41620/1/41620.pdf application/pdf en http://irep.iium.edu.my/41620/4/41620_Photoplethysmographic%20based%20heart%20rate.SCOPUS.pdf Shah, Mansoor Hussain and Kazmi, Syed Absar and Sidek, Khairul Azami and Khan, Sheroz and Iqbal, Fatema-tuz-Zohra (2014) Photoplethysmographic based heart rate variability for different physiological conditions. In: 2014 IEEE Student Conference on Research and Development (SCOReD), 16-17 December 2014, Park Royal, Batu Feringghi, Penang. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7072998
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Shah, Mansoor Hussain Kazmi, Syed Absar Sidek, Khairul Azami Khan, Sheroz Iqbal, Fatema-tuz-Zohra Photoplethysmographic based heart rate variability for different physiological conditions
description	This paper investigates the feasibility of using photoplethysmographic (PPG) signal for heart rate variability (HRV) using different physiological conditions. In this paper, we have analyzed four physiological conditions i.e.; sitting, standing, laying and jogging. The Easy Pulse sensor module was used to pass the signal sensed by the optical sensor through a series of high and low pass filters which later generates a conditioned PPG signal at its output. The Arduino processing module was used for the digitization and processing of the PPG signals. The Arduino program was then developed to capture the PPG data and waveforms. The Kubios HRV software was used to process the PPG data and manipulate it into a HRV format. The PPG signal was then analyzed in time and frequency domain parameters. Later, report sheets were generated based on these analyses. The results showed that the PPG signal as well as HRV changes depending upon the physiological conditions. It was also examined that the low and high frequency components of PPG signal also varied according to the change in physiological condition.
format	Conference or Workshop Item
author	Shah, Mansoor Hussain Kazmi, Syed Absar Sidek, Khairul Azami Khan, Sheroz Iqbal, Fatema-tuz-Zohra
author_facet	Shah, Mansoor Hussain Kazmi, Syed Absar Sidek, Khairul Azami Khan, Sheroz Iqbal, Fatema-tuz-Zohra
author_sort	Shah, Mansoor Hussain
title	Photoplethysmographic based heart rate variability for different physiological conditions
title_short	Photoplethysmographic based heart rate variability for different physiological conditions
title_full	Photoplethysmographic based heart rate variability for different physiological conditions
title_fullStr	Photoplethysmographic based heart rate variability for different physiological conditions
title_full_unstemmed	Photoplethysmographic based heart rate variability for different physiological conditions
title_sort	photoplethysmographic based heart rate variability for different physiological conditions
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2014
url	http://irep.iium.edu.my/41620/ http://irep.iium.edu.my/41620/ http://irep.iium.edu.my/41620/1/41620.pdf http://irep.iium.edu.my/41620/4/41620_Photoplethysmographic%20based%20heart%20rate.SCOPUS.pdf
first_indexed	2023-09-18T20:59:33Z
last_indexed	2023-09-18T20:59:33Z
_version_	1777410531624222720

Photoplethysmographic based heart rate variability for different physiological conditions

Similar Items