EMG Based Muscle Force Estimation using Motor Unit Twitch Model and Convolution Kernel Compensation

被引：0

作者：

Istenic, R. ^{[1
]}

Holobar, A. ^{[1
,2
]}

Merletti, R. ^{[2
]}

Zazula, D. ^{[1
]}

机构：

[1] Univ Maribor, Fac Elect Engn & Comp Sci, Smetanova 17, SLO-2000 Maribor, Slovenia

[2] Dept Elect, LISIN, Politecn Torino, Turin, Italy

来源：

11TH MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2007, VOLS 1 AND 2 | 2007年 / 16卷 / 1-2期

关键词：

muscle force estimation; EMG force relation; twitch; convolution kernel compensation;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper we introduce a new method for muscle force estimation from multi-channel surface electromyograms. The method combines a motor unit twitch model with motor unit innervation pulse trains, which are estimated from multi-channel surface electromyograms. The motor unit twitches are then aligned to the innervation pulse trains and summed up to obtain the total muscle force. The method was tested on real surface EMG signals acquired during force ramp contractions of abductor pollicis brevis muscle in 8 male subjects. With 22 +/- 5 (mean +/- std. dev.) motor units identified per subject, the force estimation error of our method was 16 4% RMS. These results were compared to the method which uses the EMG amplitude processing to estimate muscle force. The results of our new concept proved to be completely comparable to those of EMG amplitude processing.

引用

页码：114 / +

页数：2

共 50 条

[21] Estimation Biting Force Based Using EMG Signals and Laguerre Estimation Technique
Goharian, Nazanin
Moghimi, Sahar
Kalani, Hadi
[J]. 2015 23RD IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2015, : 50 - 55
[22] Optimal Feature Selection for EMG-Based Finger Force Estimation Using LightGBM Model
Ye, Yuhang
Liu, Chao
Zemiti, Nabil
Yang, Chenguang
[J]. 2019 28TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN), 2019,
[23] Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition
Na, Youngjin
Kim, Jung
[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2017, 25 (09) : 1431 - 1439
[24] Voluntary EMG-to-force estimation with a multi-scale physiological muscle model
Hayashibe, Mitsuhiro
Guiraud, David
[J]. BIOMEDICAL ENGINEERING ONLINE, 2013, 12
[25] Voluntary EMG-to-force estimation with a multi-scale physiological muscle model
Mitsuhiro Hayashibe
David Guiraud
[J]. BioMedical Engineering OnLine, 12
[26] A motor unit-based model of muscle fatigue
Potvin, Jim R.
Fuglevand, Andrew J.
[J]. PLOS COMPUTATIONAL BIOLOGY, 2017, 13 (06)
[27] A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG
Potocnik, Bozidar
Holobar, Ales
[J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2017, 83 : 59 - 68
[28] Muscle Force Estimation with Surface EMG during Dynamic Muscle Contractions: A Wavelet and ANN based Approach
Bai, Fengjun
Chew, Chee-Meng
[J]. 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 4589 - 4592
[29] A model of the rat medial gastrocnemius muscle based on inputs to motoneurons and on an algorithm for prediction of the motor unit force
Raikova, R.
Celichowski, J.
Angelova, S.
Krutki, P.
[J]. JOURNAL OF NEUROPHYSIOLOGY, 2018, 120 (04) : 1973 - 1987
[30] SURFACE EMG AND MUSCLE FORCE AT LOW FORCE LEVELS - A MODEL BASED THEORETICAL-STUDY
POLLAK, V
[J]. AMERICAN JOURNAL OF PHYSICAL MEDICINE & REHABILITATION, 1980, 59 (03) : 126 - 141

← 1 2 3 4 5 →