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...

Full description

Bibliographic Details
Main Authors: Kazmi, Syed Absar, Khan, Sheroz, Khalifa, Othman Omran, Shah, Mansoor Hussain
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2015
Subjects:
Online Access: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
Description
Summary: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.