PMID- 35213304
OWN - NLM
STAT- MEDLINE
DCOM- 20220823
LR  - 20220929
IS  - 1558-2531 (Electronic)
IS  - 0018-9294 (Linking)
VI  - 69
IP  - 9
DP  - 2022 Sep
TI  - Finger Force Estimation Using Motor Unit Discharges Across Forearm Postures.
PG  - 2767-2775
LID - 10.1109/TBME.2022.3153448 [doi]
AB  - BACKGROUND: Myoelectric- based decoding has gained popularity in upper- limb 
      neural-machine interfaces. Motor unit (MU) firings decomposed from surface 
      electromyographic (EMG) signals can represent motor intent, but EMG properties at 
      different arm configurations can change due to electrode shift and differing 
      neuromuscular states. This study investigated whether isometric fingertip force 
      estimation using MU firings is robust to forearm rotations from a neutral to 
      either a fully pronated or supinated posture. METHODS: We extracted MU 
      information from high- density EMG of the extensor digitorum communis in two 
      ways: (1) Decomposed EMG in all three postures (MU-AllPost); and (2) Decomposed 
      EMG in neutral posture (MU-Neu), and extracted MUs (separation matrix) were 
      applied to other postures. Populational MU firing frequency estimated forces 
      scaled to subjects' maximum voluntary contraction (MVC) using a regression 
      analysis. The results were compared with the conventional EMG-amplitude method. 
      RESULTS: We found largely similar root-mean-square errors (RMSE) for the two 
      MU-methods, indicating that MU decomposition was robust to postural differences. 
      MU-methods demonstrated lower RMSE in the ring (EMG = 6.23, MU-AllPost = 5.72, 
      MU-Neu = 5.64% MVC) and pinky (EMG = 6.12, MU-AllPost = 4.95, MU-Neu = 5.36% MVC) 
      fingers, with mixed results in the middle finger (EMG = 5.47, MU-AllPost = 5.52, 
      MU-Neu = 6.19% MVC). CONCLUSION: Our results suggest that MU firings can be 
      extracted reliably with little influence from forearm posture, highlighting its 
      potential as an alternative decoding scheme for robust and continuous control of 
      assistive devices.
FAU - Rubin, Noah
AU  - Rubin N
FAU - Zheng, Yang
AU  - Zheng Y
FAU - Huang, He
AU  - Huang H
FAU - Hu, Xiaogang
AU  - Hu X
LA  - eng
PT  - Journal Article
PT  - Research Support, U.S. Gov't, Non-P.H.S.
DEP - 20220819
PL  - United States
TA  - IEEE Trans Biomed Eng
JT  - IEEE transactions on bio-medical engineering
JID - 0012737
SB  - IM
MH  - Electromyography/methods
MH  - *Fingers
MH  - *Forearm
MH  - Humans
MH  - Isometric Contraction
MH  - Muscle, Skeletal
MH  - Posture
MH  - Upper Extremity
EDAT- 2022/02/26 06:00
MHDA- 2022/08/24 06:00
CRDT- 2022/02/25 17:14
PHST- 2022/02/26 06:00 [pubmed]
PHST- 2022/08/24 06:00 [medline]
PHST- 2022/02/25 17:14 [entrez]
AID - 10.1109/TBME.2022.3153448 [doi]
PST - ppublish
SO  - IEEE Trans Biomed Eng. 2022 Sep;69(9):2767-2775. doi: 10.1109/TBME.2022.3153448. 
      Epub 2022 Aug 19.