PMID- 26863681
OWN - NLM
STAT- MEDLINE
DCOM- 20171127
LR  - 20180206
IS  - 2168-2208 (Electronic)
IS  - 2168-2194 (Linking)
VI  - 21
IP  - 2
DP  - 2017 Mar
TI  - Motion Artifact Suppression in Impedance Pneumography Signal for Portable 
      Monitoring of Respiration: An Adaptive Approach.
PG  - 387-398
LID - 10.1109/JBHI.2016.2524646 [doi]
AB  - The focus of this paper is motion artifact (MA) reduction from the impedance 
      pneumography (IP) signal, which is widely used to monitor respiration. The 
      amplitude of the MA that contaminates the IP signal is often much larger than the 
      amplitude of the respiratory component of the signal. Moreover, the morphology 
      and frequency composition of the artifacts may be very similar to that of the 
      respiration, making it difficult to remove these artifacts. The proposed filter 
      uses a regularization term to ensure that the pattern of the filtered signal is 
      similar to that of respiration. It also ensures that the amplitude of the filter 
      output is within the expected range of the IP signal by imposing an epsilon-tube on the 
      filtered signal. The adaptive epsilon-tube filter is 100 times faster than the 
      previously proposed nonadaptive version and achieves higher accuracies. Moreover, 
      the experimental results, using several different performance measures, suggest 
      that the proposed method outperforms popular MA reduction methods such as 
      normalized least mean squares (NLMS) and recursive least squares (RLS) as well as 
      independent component analysis (ICA). When used to extract the respiratory rate, 
      the adaptive epsilon-tube achieves a mean error of 1.27 breaths per minute (BPM) 
      compared to 4.72 and 4.63 BPM for the NLMS and RLS filters, respectively. When 
      compared to the ICA algorithm, the proposed filter has an error of 1.06 BPM 
      compared to 3.47 BPM for ICA. The statistical analyses indicate that all of the 
      reported performance improvements are significant.
FAU - Ansari, Sardar
AU  - Ansari S
FAU - Ward, Kevin R
AU  - Ward KR
FAU - Najarian, Kayvan
AU  - Najarian K
LA  - eng
PT  - Journal Article
DEP - 20160203
PL  - United States
TA  - IEEE J Biomed Health Inform
JT  - IEEE journal of biomedical and health informatics
JID - 101604520
SB  - IM
MH  - *Artifacts
MH  - Electric Impedance/*therapeutic use
MH  - Electrodiagnosis/*methods
MH  - Humans
MH  - Lung/physiology
MH  - Monitoring, Physiologic/*methods
MH  - Motion
MH  - Respiratory Rate/*physiology
MH  - *Signal Processing, Computer-Assisted
EDAT- 2016/02/11 06:00
MHDA- 2017/11/29 06:00
CRDT- 2016/02/11 06:00
PHST- 2016/02/11 06:00 [pubmed]
PHST- 2017/11/29 06:00 [medline]
PHST- 2016/02/11 06:00 [entrez]
AID - 10.1109/JBHI.2016.2524646 [doi]
PST - ppublish
SO  - IEEE J Biomed Health Inform. 2017 Mar;21(2):387-398. doi: 
      10.1109/JBHI.2016.2524646. Epub 2016 Feb 3.