| Title |
Breathing Information Extraction Algorithm from PPG Signal for the Development of Respiratory Biofeedback App |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.6.794 |
| Keywords |
Photoplethysmography (PPG) ; Respiration (RSP) ; Biofeedback ; Stress |
| Abstract |
There is a growing need for a care system that can continuously monitor, manage and effectively relieve stress for modern people. In recent years, mobile healthcare devices capable of measuring heart rate have become popular, and many stress monitoring techniques using heart rate variability analysis have been actively proposed and commercialized. In addition, respiratory biofeedback methods are used to provide stress relieving services in environments using mobile healthcare devices. In this case, breathing information should be measured well to assess whether the user is doing well in biofeedback training. In this study, we extracted the heart beat interval signal from the PPG and used the oscillator based notch filter based on the IIR band pass filter to track the strongest frequency in the heart beat interval signal. The respiration signal was then estimated by filtering the heart beat interval signal with this frequency as the center frequency. Experimental results showed that the number of breathing could be measured accurately when the subject was guided to take a deep breath. Also, in the timeing measurement of inspiration and expiration, a time delay of about 1 second occurred. It is expected that this will provide a respiratory biofeedback service that can assess whether or not breathing exercise are performed well. |