ProRuka: A highly efficient HMI algorithm for controlling a novel prosthetic hand with 6-DOF using sonomyography
<|reference_start|>ProRuka: A highly efficient HMI algorithm for controlling a novel prosthetic hand with 6-DOF using sonomyography: Sonomyography (SMG) is a novel human-machine interface that controls upper-limb prostheses by monitoring forearm muscle activity using ultrasonic imaging. SMG has been investigated for controlling upper-limb prostheses during the last two decades. The results show that this method, in combination with artificial intelligence, can classify different hand gestures with an accuracy of more than 90%, making it a great alternative control system compared to electromyography (EMG). However, up to now there are few reports of a system integrating SMG together with a prosthesis for testing on amputee subjects to demonstrate its capability in relation to daily activities. In this study, we developed ProRuka, a novel low-cost 6-degree-of-freedom prosthetic hand integrated with the control provided by a SMG system with a wearable ultrasound imaging probe. The classification of hand gestures using different machine learning classification/regression algorithms including KNN, nearest neighbor regression, random forest, decision tree classifier, decision tree regression, support vector regression and support vector machine in combination with a transfer learning model (VGG16) was first evaluated off-line to determine its reliability and precision. Additionally, the developed controlling system were evaluated on two amputees, in real-time experiments using a variety of hand function test kits. The results from an off-line study including ten healthy participants indicated that nine different hand motions can be classified with a success rate of 100%. In addition, the hand function test in real time (using 4 different hand gestures) confirmed that the designed prosthesis with the SMG controlling system can assist amputees to perform a variety of hand movements needed in daily activities.<|reference_end|>
@article{nazari2024proruka:,
    title={ProRuka: A highly efficient HMI algorithm for controlling a novel
  prosthetic hand with 6-DOF using sonomyography},
    author={Vaheh Nazari, Yong-Ping Zheng},
    journal={arXiv preprint arXiv:2407.19859},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.19859},
    primaryClass={eess.SY cs.SY}
}