title: Reduced Daily Recalibration of Myoelectric Prosthesis Classifiers Based on Domain Adaptation.
abstract: Control scheme design based on surface electromyography (sEMG) pattern recognition has been the focus of much research on a myoelectric prosthesis (MP) technology. Due to inherent nonstationarity in sEMG signals, prosthesis systems may need to be recalibrated day after day in daily use applications; thereby, hindering MP usability. In order to reduce the recalibration time in the subsequent days following the initial training, we propose a domain adaptation (DA) framework, which automatically reuses the models trained in earlier days as input for two baseline classifiers: a polynomial classifier (PC) and a linear discriminant analysis (LDA). Two novel algorithms of DA are introduced, one for PC and the other one for LDA. Five intact-limbed subjects and two transradial-amputee subjects participated in an experiment lasting ten days, to simulate the application of a MP over multiple days. The experiment results of four methods were compared: PC-DA (PC with DA), PC-BL (baseline PC), LDA-DA (LDA with DA), and LDA-BL (baseline LDA). In a new day, the DA methods reuse nine pretrained models, which were calibrated by 40 s training data per class in nine previous days. We show that the proposed DA methods significantly outperform nonadaptive baseline methods. The improvement in classification accuracy ranges from 5.49% to 28.48%, when the recording time per class is 2 s. For example, the average classification rates of PC-BL and PC-DA are 83.70% and 92.99%, respectively, for intact-limbed subjects with a nine-motions classification task. These results indicate that DA has the potential to improve the usability of MPs based on pattern recognition, by reducing the calibration time.
authors.forename: Jianwei
authors.initials: J
authors.lastname: Liu
authors.forename: Xinjun
authors.initials: X
authors.lastname: Sheng
authors.forename: Dingguo
authors.initials: D
authors.lastname: Zhang
authors.forename: Jiayuan
authors.initials: J
authors.lastname: He
authors.forename: Xiangyang
authors.initials: X
authors.lastname: Zhu
mesh_terms: D000674:Amputees; D001186:Artificial Limbs; D002138:Calibration; D016002:Discriminant Analysis; D004576:Electromyography / Q000379:methods* / Q000592:standards*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*