Predicting manual wheelchair initiation movement with EMG activity during over ground propulsion

被引:1
|
作者
Chikh, Soufien [1 ,2 ]
Boudet, Samuel [3 ,4 ]
Pinti, Antonio [5 ,6 ]
Garnier, Cyril [5 ,7 ,8 ]
El Hage, Rawad [9 ]
Azaiez, Fairouz [10 ]
Watelain, Eric [2 ]
机构
[1] Univ Sfax, Inst Super Sport & Educ Phys Sfax, Lab Rech Educ Motricite Sport & Sante, EMSS LR19JS01, Sfax, Tunisia
[2] Univ Toulon & Var, Lab IAPS, UR 201723207F, Toulon, France
[3] Univ Nord France, F-59000 Lille, France
[4] Univ Catholique Lille, Unite Traitement Signaux Biomed, Fac Med & Maieut, Lille, France
[5] Univ Lille Nord France, F-59000 Lille, France
[6] CHRO, I3MTO, EA 4708, 1 Rue Porte Madeleine, F-45032 Orleans, France
[7] UVHC, LAMIH Dptm SHV, F-59313 Valenciennes, France
[8] CNRS, UMR 8201, F-59313 Valenciennes, France
[9] Univ Balamand, Fac Arts & Social Sci, Dept Phys Educ, Balamand, El Koura, Lebanon
[10] Univ Sfax, Inst Super Sport & Educ Phys Sfax, Sfax, Tunisia
来源
JOURNAL OF SPINAL CORD MEDICINE | 2022年 / 45卷 / 02期
关键词
Prediction; EMG; Logistic regression; Manual wheelchairs; Initiation; SPINAL-CORD-INJURY; PARAMETERS; LEVEL;
D O I
10.1080/10790268.2020.1778352
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Context/Objective:This is a preliminary study of movement finalities prediction in manual wheelchairs (MWCs) from electromyography (EMG) data. MWC users suffer from musculoskeletal disorders and need assistance while moving. The purpose of this work is to predict the direction and speed of movement in MWCs from EMG data prior to movement initiation. This prediction could be used by MWC to assist users in their displacement by doing a smart electrical assistance based on displacement prediction. Design:Experimental study. Setting:Trained Subject LAMIH Laboratory. Participants:Eight healthy subjects trained to move in manual wheelchairs. Interventions:Subjects initiated the movement in three directions (front, right and left) and with two speeds (maximum speed and spontaneous speed) from two hand positions (on the thighs or on the handrim). A total of 96 movements was studied. Activation of 14 muscles was recorded bilaterally at the deltoid anterior, deltoid posterior, biceps brachii, pectoralis major, rectus abdominis, obliquus externus and erector spinae. Outcome Measures:Prior amplitude, prior time and anticipatory postural adjustments were measured. A hierarchical multi-class classification using logistic regression was used to create a cascade of prediction models. We performed a stepwise (forward-backward) selection of variables using the Bayesian information criterion. Percentages of well-classified movements have been measured through the means of a cross-validation. Results:Prediction is possible using the EMG parameters and allows to discriminate the direction / speed combination with 95% correct classification on the 6 possible classes (3 directions * 2 speeds). Conclusion:Action planning in the static position showed significant adaptability to the forthcoming parameters displacement. The percentages of prediction presented in this work make it possible to envision an intuitive assistance to the initiation of the MWC displacement adapted to the user's intentions.
引用
收藏
页码:262 / 269
页数:8
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