AI Article Synopsis
- sEMG has been the go-to method for controlling upper-limb prostheses, but its signal variability poses challenges for intricate movements.
- The study explores the potential of using ultrasonography (US) as an alternative, utilizing a combined sensory module for comparison with sEMG.
- Results showed that US performed better in some classifications, suggesting it could provide a more stable control for prosthetics, though it might need stricter measures for accuracy due to sensitivity to external factors.
Article Abstract
Surface electromyography (sEMG) has dominated upper-limb prosthesis control for decades due to its simplicity and effectiveness [1-3]. However, the inherent variability of EMG signal hinders the flexible and accurate control of advanced multi-functional prosthesis. This study is an attempt to use ultrasonography (US) as an alternative for prosthetic hand control. A type of multi-sensory module, comprising a single-element ultrasound channel and one sEMG bipolar channel, is customised to ensure a fair comparison between these two modalities. Three machine-learning-oriented approaches were adopted to evaluate the performance in motion classification based on datasets captured from a trans-radial amputee. The experimental results demonstrated that the ultrasound outperformed the sEMG in random (98.9% vs 70.4%) and enhanced-trial-wise (74.10% vs 61.83%) cross-validation, but fell behind the sEMG in trial-wise (39.47% vs 58.04%) validation that is the closest comparison to a real life prosthetic control. This study preliminarily implies that 1) A-mode ultrasound signal can be more stable than the sEMG with minimum electrode shift, but more sensitive to external interference than the sEMG; and 2) to maintain high classification accuracy, US approach may require harsher electrode fixing mechanism or advanced on-line calibration approach.
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| http://dx.doi.org/10.1016/j.medengphy.2019.11.005 | DOI Listing |
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