PMID- 35380978
OWN - NLM
STAT- MEDLINE
DCOM- 20220815
LR  - 20220824
IS  - 2168-2208 (Electronic)
IS  - 2168-2194 (Linking)
VI  - 26
IP  - 8
DP  - 2022 Aug
TI  - An Effective Photoplethysmography Heart Rate Estimation Framework Integrating 
      Two-Level Denoising Method and Heart Rate Tracking Algorithm Guided by Finite 
      State Machine.
PG  - 3731-3742
LID - 10.1109/JBHI.2022.3165071 [doi]
AB  - In order to achieve accurate heart rate (HR) estimation in complex scenes, this 
      paper presents an effective photoplethysmography (PPG) HR estimation framework 
      integrating two-level denoising method and HR tracking algorithm guided by finite 
      state machine (FSM). Aiming at solving the problems of low signal-to-noise ratio 
      and co-frequency (the noise frequency is close to the HR frequency) caused by 
      motion artifacts, the two-level denoising method consisting of the cascaded 
      adaptive filtering and the differential denoising guided by FSM are designed to 
      remove motion-related noises in PPG signals. In order to solve the problem of HR 
      tracking error caused by poor wrist contact, the HR tracking algorithm guided by 
      FSM is proposed to obtain the global optimization capability. The results of HR 
      estimation experiments conducted on the IEEE Signal Processing Cup database and 
      the WeData database created by ourselves show that the proposed framework can 
      effectively cope with the problems of low signal-to-noise ratio and co-frequency. 
      Even if tracking errors occur due to poor wristband contact, the proposed HR 
      tracking algorithm guided by FSM can correct them in time when the HR component 
      appears again. The average absolute error of HR estimation on the two databases 
      are 1.76 BPM (beats per minute) and 2.77 BPM, respectively, which is more 
      accurate compared to other algorithms.
FAU - Guo, Jingbin
AU  - Guo J
FAU - Chen, Xiang
AU  - Chen X
FAU - Zhao, Jiaqi
AU  - Zhao J
FAU - Zhang, Xu
AU  - Zhang X
FAU - Chen, Xun
AU  - Chen X
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220811
PL  - United States
TA  - IEEE J Biomed Health Inform
JT  - IEEE journal of biomedical and health informatics
JID - 101604520
SB  - IM
MH  - Algorithms
MH  - Artifacts
MH  - *Exercise/physiology
MH  - Heart Rate/physiology
MH  - Humans
MH  - *Photoplethysmography/methods
MH  - Signal Processing, Computer-Assisted
EDAT- 2022/04/06 06:00
MHDA- 2022/08/16 06:00
CRDT- 2022/04/05 17:10
PHST- 2022/04/06 06:00 [pubmed]
PHST- 2022/08/16 06:00 [medline]
PHST- 2022/04/05 17:10 [entrez]
AID - 10.1109/JBHI.2022.3165071 [doi]
PST - ppublish
SO  - IEEE J Biomed Health Inform. 2022 Aug;26(8):3731-3742. doi: 
      10.1109/JBHI.2022.3165071. Epub 2022 Aug 11.