Adaptive cancellation of motion artifact in wearable biosensors.
The performance of wearable biosensors is highly influenced by motion artifact. In this paper, a model is proposed for analysis of motion artifact in wearable photoplethysmography (PPG) sensors. Using this model, we proposed a robust real-time technique to estimate fundamental frequency and generate a noise reference signal. A Least Mean Square (LMS) adaptive noise canceler is then designed and validated using our synthetic noise generator. The analysis and results on proposed technique for noise cancellation shows promising performance.
Quality of Life Technology Laboratory The University of Texas at Dallas, Richardson, TX 75080, USA. r.yousefi@utdallas.edu
Rasoul
R
Yousefi
Mehrdad
M
Nourani
Issa
I
Panahi
D000465:Algorithms; D016477:Artifacts; D015374:Biosensing Techniques / Q000295:instrumentation*; D003198:Computer Simulation; D006801:Humans; D009038:Motion; D017156:Photoplethysmography / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted; D013057:Spectrum Analysis