Motion artifact reduction in electrocardiogram using adaptive filtering based on half cell potential monitoring.
The electrocardiogram (ECG) is the main measurement parameter for effectively diagnosing chronic disease and guiding cardio-fitness therapy. ECGs contaminated by noise or artifacts disrupt the normal functioning of the automatic analysis algorithm. The objective of this study is to evaluate a method of measuring the HCP variation in motion artifacts through direct monitoring. The proposed wearable sensing device has two channels. One channel is used to measure the ECG through a differential amplifier. The other is for monitoring motion artifacts using the modified electrode and the same differential amplifier. Noise reduction was performed using adaptive filtering, based on a reference signal highly correlated with it. Direct measurement of HCP variations can eliminate the need for additional sensors.
Future IT Research Center, Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd., Yongin, Republic of Korea. byunghoon.ko@samsung.com
Byung-hoon
BH
Ko
Takhyung
T
Lee
Changmok
C
Choi
Youn-ho
YH
Kim
Gunguk
G
Park
KyoungHo
K
Kang
Sang Kon
SK
Bae
Kunsoo
K
Shin
D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D015716:Electrocardiography, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D004566:Electrodes; D006801:Humans; D009068:Movement / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio