Abstract

Amputees suffer from the weight, insufficient power, and uncomfortable control methods of their prostheses. Recent studies have introduced many ideas for both hardware and software to tackle these problems. In this letter, the authors introduce a preliminary platform of a robotic prosthetic hand system called the MSC hand that integrates effective mechanical mechanisms and intuitive control methods. The hand adopts mode-switchable twisted string actuators to provide a wide range of grasping speed (closing speed of 0.8 s) and grasping force (pinch force of 45 N) with a light weight of 390 g. All the fingers and the thumb flex and extend actively, and the thumb is also able to abduct and adduct passively. The active fingers are controlled by surface electromyographic signals, and a learning-based neurophysiologic model is used to estimate human intention for each finger. The model provides independent intentions for each finger, so the simultaneous and proportional control of multiple fingers is possible in real time. The performance of the MSC hand was verified through standardized experiments such as online simulation and the box and block test. In addition, a demonstration of gripping various objects was performed. The results showed rapid and precise gripping and intuitive control over the tasks.

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