PMID- 32708473
OWN - NLM
STAT- MEDLINE
DCOM- 20210324
LR  - 20210324
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 20
IP  - 14
DP  - 2020 Jul 18
TI  - A Real Time QRS Detection Algorithm Based on ET and PD Controlled Threshold 
      Strategy.
LID - 10.3390/s20144003 [doi]
LID - 4003
AB  - As one of the important components of electrocardiogram (ECG) signals, QRS signal 
      represents the basic characteristics of ECG signals. The detection of QRS waves 
      is also an essential step for ECG signal analysis. In order to further meet the 
      clinical needs for the accuracy and real-time detection of QRS waves, a simple, 
      fast, reliable, and hardware-friendly algorithm for real-time QRS detection is 
      proposed. The exponential transform (ET) and proportional-derivative (PD) 
      control-based adaptive threshold are designed to detect QRS-complex. The proposed 
      ET can effectively narrow the magnitude difference of QRS peaks, and the PD 
      control-based method can adaptively adjust the current threshold for QRS 
      detection according to thresholds of previous two windows and predefined minimal 
      threshold. The ECG signals from MIT-BIH databases are used to evaluate the 
      performance of the proposed algorithm. The overall sensitivity, positive 
      predictivity, and accuracy for QRS detection are 99.90%, 99.92%, and 99.82%, 
      respectively. It is also implemented on Altera Cyclone V 5CSEMA5F31C6 Field 
      Programmable Gate Array (FPGA). The time consumed for a 30-min ECG record is 
      approximately 1.3 s. It indicates that the proposed algorithm can be used for 
      wearable heart rate monitoring and automatic ECG analysis.
FAU - Chen, Aiyun
AU  - Chen A
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Zhang, Yidan
AU  - Zhang Y
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Zhang, Mengxin
AU  - Zhang M
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Liu, Wenhan
AU  - Liu W
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Chang, Sheng
AU  - Chang S
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Wang, Hao
AU  - Wang H
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - He, Jin
AU  - He J
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
FAU - Huang, Qijun
AU  - Huang Q
AUID- ORCID: 0000-0001-9679-5191
AD  - School of Physics and Technology, Wuhan University, Wuhan 430072, China.
LA  - eng
GR  - 81971702, 61874079, 61574102 and 61774113/the National Natural Science Foundation 
      of China/
GR  - 2042017gf0052 and 2042018gf0045/the Fundamental Research Fund for the Central 
      Universities, Wuhan University/
GR  - 2017CFB660/the Natural Science Foundation of Hubei Province, China/
PT  - Journal Article
DEP - 20200718
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - *Algorithms
MH  - Databases, Factual
MH  - *Electrocardiography
MH  - Humans
MH  - *Signal Processing, Computer-Assisted
PMC - PMC7412314
OTO - NOTNLM
OT  - PD-control
OT  - QRS detection
OT  - electrocardiogram (ECG)
OT  - exponential transform (ET)
OT  - real-time
COIS- The authors declare no conflicts of interest.
EDAT- 2020/07/28 06:00
MHDA- 2021/03/25 06:00
PMCR- 2020/07/01
CRDT- 2020/07/26 06:00
PHST- 2020/06/19 00:00 [received]
PHST- 2020/07/12 00:00 [revised]
PHST- 2020/07/13 00:00 [accepted]
PHST- 2020/07/26 06:00 [entrez]
PHST- 2020/07/28 06:00 [pubmed]
PHST- 2021/03/25 06:00 [medline]
PHST- 2020/07/01 00:00 [pmc-release]
AID - s20144003 [pii]
AID - sensors-20-04003 [pii]
AID - 10.3390/s20144003 [doi]
PST - epublish
SO  - Sensors (Basel). 2020 Jul 18;20(14):4003. doi: 10.3390/s20144003.