Spectrum analysis of physiological signals of human activities
This paper investigates the impact of physiological maneuvers on the frequency component of photoplethysmograpy signal. Here, we have taken four different physiological states of sitting, standing, jogging and laying. Two groups of 5 to 10 healthy volunteers males and females are formed. The PPG sig...
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iium-505062017-10-19T01:39:46Z http://irep.iium.edu.my/50506/ Spectrum analysis of physiological signals of human activities Kazmi, Syed Absar Khan, Sheroz Khalifa, Othman Omran Shah, Mansoor Hussain T10.5 Communication of technical information This paper investigates the impact of physiological maneuvers on the frequency component of photoplethysmograpy signal. Here, we have taken four different physiological states of sitting, standing, jogging and laying. Two groups of 5 to 10 healthy volunteers males and females are formed. The PPG signal acquisition is performed by Easy Pulse analyzer sensor module. Each sample for each state was taken for one-minute duration at stopwatch keeping the consolidated state of volunteer prior to fetching of PPG signal. The Easy pulse analyzer module implicates the pulse oximetry working principle and get the signal from the finger tip of subjects, which determines the oxygen saturation in blood and passes the signal by the optical sensor via a sequential high and low pass op-amp filters and ultimately produces the conditioned PPG signal. The interfacing between the easy pulse analyzer and computing machine was done with the help of Arduino processing board. The Kubios HRV software was utilized in order to execute and manipulate PPG data (numerical values) samples in required format. The report sheet was generated which pertains the frequency and time domain paradigms and was analyzed for respective PPG signal according to the physiological conditions. The results for each data set among four physical states define the co-relation between the physical state and corresponding PPG signal. Moreover, the variation in frequency components is observed during the change in physiological condition. IEEE 2015-12 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/50506/4/50506.pdf application/pdf en http://irep.iium.edu.my/50506/7/50506-Spectrum%20Analysis%20of%20Physiological%20Signals%20of_SCOPUS.pdf Kazmi, Syed Absar and Khan, Sheroz and Khalifa, Othman Omran and Shah, Mansoor Hussain (2015) Spectrum analysis of physiological signals of human activities. In: 2015 International Conference on Emerging Technologies (ICET), 19th-20th Dec. 2015, Peshawar, Pakistan. http://dx.doi.org/10.1109/ICET.2015.7389197 doi:10.1109/ICET.2015.7389197 |
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T10.5 Communication of technical information Kazmi, Syed Absar Khan, Sheroz Khalifa, Othman Omran Shah, Mansoor Hussain Spectrum analysis of physiological signals of human activities |
description |
This paper investigates the impact of physiological maneuvers on the frequency component of photoplethysmograpy signal. Here, we have taken four different physiological states of sitting, standing, jogging and laying. Two groups of 5 to 10 healthy volunteers males and females are formed. The PPG signal acquisition is performed by Easy Pulse analyzer sensor module. Each sample for each state was taken for one-minute duration at stopwatch keeping the consolidated state of volunteer prior to fetching of PPG signal. The Easy pulse analyzer module implicates the pulse oximetry working principle and get the signal from the finger tip of subjects, which determines the oxygen saturation in blood and passes the signal by the optical sensor via a sequential high and low pass op-amp filters and ultimately produces the conditioned PPG signal. The interfacing between the easy pulse analyzer and computing machine was done with the help of Arduino processing board. The Kubios HRV software was utilized in order to execute and manipulate PPG data (numerical values) samples in required format. The report sheet was generated which pertains the frequency and time domain paradigms and was analyzed for respective PPG signal according to the physiological conditions. The results for each data set among four physical states define the co-relation between the physical state and corresponding PPG signal. Moreover, the variation in frequency components is observed during the change in physiological condition. |
format |
Conference or Workshop Item |
author |
Kazmi, Syed Absar Khan, Sheroz Khalifa, Othman Omran Shah, Mansoor Hussain |
author_facet |
Kazmi, Syed Absar Khan, Sheroz Khalifa, Othman Omran Shah, Mansoor Hussain |
author_sort |
Kazmi, Syed Absar |
title |
Spectrum analysis of physiological signals of human activities |
title_short |
Spectrum analysis of physiological signals of human activities |
title_full |
Spectrum analysis of physiological signals of human activities |
title_fullStr |
Spectrum analysis of physiological signals of human activities |
title_full_unstemmed |
Spectrum analysis of physiological signals of human activities |
title_sort |
spectrum analysis of physiological signals of human activities |
publisher |
IEEE |
publishDate |
2015 |
url |
http://irep.iium.edu.my/50506/ http://irep.iium.edu.my/50506/ http://irep.iium.edu.my/50506/ http://irep.iium.edu.my/50506/4/50506.pdf http://irep.iium.edu.my/50506/7/50506-Spectrum%20Analysis%20of%20Physiological%20Signals%20of_SCOPUS.pdf |
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2023-09-18T21:11:23Z |
last_indexed |
2023-09-18T21:11:23Z |
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