تقرير
User Training with Error Augmentation for Electromyogram-based Gesture Classification
| العنوان: | User Training with Error Augmentation for Electromyogram-based Gesture Classification |
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| المؤلفون: | Bicer, Yunus, Smedemark-Margulies, Niklas, Celik, Basak, Sunger, Elifnur, Orendorff, Ryan, Naufel, Stephanie, Imbiriba, Tales, Erdoğmuş, Deniz, Tunik, Eugene, Yarossi, Mathew |
| المصدر: | in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 32, pp. 1187-1197, 2024 |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Human-Computer Interaction, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | We designed and tested a system for real-time control of a user interface by extracting surface electromyographic (sEMG) activity from eight electrodes in a wrist-band configuration. sEMG data were streamed into a machine-learning algorithm that classified hand gestures in real-time. After an initial model calibration, participants were presented with one of three types of feedback during a human-learning stage: veridical feedback, in which predicted probabilities from the gesture classification algorithm were displayed without alteration, modified feedback, in which we applied a hidden augmentation of error to these probabilities, and no feedback. User performance was then evaluated in a series of minigames, in which subjects were required to use eight gestures to manipulate their game avatar to complete a task. Experimental results indicated that, relative to baseline, the modified feedback condition led to significantly improved accuracy and improved gesture class separation. These findings suggest that real-time feedback in a gamified user interface with manipulation of feedback may enable intuitive, rapid, and accurate task acquisition for sEMG-based gesture recognition applications. Comment: 10 pages, 10 figures. V2: Fix latex characters in author name. V3: Add published DOI and Copyright notice |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1109/TNSRE.2024.3372512 |
| URL الوصول: | http://arxiv.org/abs/2309.07289 |
| رقم الأكسشن: | edsarx.2309.07289 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1109/TNSRE.2024.3372512 |
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