Ultrasonography and electromyography based hand motion intention recognition for a trans-radial amputee: A case study
| Autor: | Christophe Cointet, Dalin Zhou, Kairu Li, Yinfeng Fang, Zheng Wang, Honghai Liu |
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| Rok vydání: | 2020 |
| Předmět: |
Channel (digital image)
Computer science Movement medicine.medical_treatment 0206 medical engineering Biomedical Engineering Biophysics Hand motion Prosthesis 02 engineering and technology Electromyography Upper-limb amputee Signal 03 medical and health sciences 0302 clinical medicine Amputees Interference (communication) medicine Humans Computer vision Electrodes Ultrasonography medicine.diagnostic_test business.industry Ultrasound Hand 020601 biomedical engineering Radius Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | Wang, Z, Fang, Y, Zhou, D, Li, K, Cointet, C & Liu, H 2020, ' Ultrasonography and electromyography based hand motion intention recognition for a trans-radial amputee : a case study ', Medical Engineering and Physics, vol. 75, pp. 45-48 . https://doi.org/10.1016/j.medengphy.2019.11.005 |
| ISSN: | 1350-4533 |
| Popis: | Surface electromyography (sEMG) has dominated upper-limb prosthesis control for decades due to its simplicity and effectiveness [1] , [2] , [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. |
| Databáze: | OpenAIRE |
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