Toward cyborg exploring long-term clinical outcomes of a multi-degree-of-freedom myoelectric prosthetic hand
image: The BIT-UEC-Hand developed in this study consists of a hand, a controller, an EMG sensor, a battery, and a socket. The hand was developed in a joint research project between the University of Electro-Communications (UEC) and the Beijing Institute of Technology (BIT). The BIT-UEC-Hand developed in collaborative research is equipped with a controller developed in the Yokoi Laboratory of the UEC. The controller can communicate with the tablet application to check the myoelectric signal information and acquire teacher data for pattern recognition control.
Credit: Yuki Kuroda, University of Electro-Communications.
The research into multi-degree-of-freedom (DOF) myoelectric prosthetic hands (MPHs) has advanced with improvements in robotics and sensor technologies, allowing MPHs to simulate complex hand movements. However, despite technological advancements, practical application remains challenging, particularly in terms of control precision and stability. In the case of 5-finger MPHs, while pattern recognition-based control systems have been applied, these systems show instability in real users, and the reliability of motion control decreases as task complexity increases. “To overcome these limitations, we developed a 5-finger-driven MPH with a pattern recognition function and applied it to individuals with upper limb deficiencies over the long term. This MPH is lightweight and has a mechanism to release external forces on the fingers, preventing damage and ensuring safe use.” said the author Yuki Kuroda, a researcher at University of Electro-Communications, “The results showed that the MPH expanded the range of tasks users could perform. This study provides valuable insights into the clinical use of multi-DOF MPHs and suggests further optimization of control systems for better outcomes.”
The BIT-UEC-Hand developed in this study is a five-finger-driven myoelectric prosthetic hand with pattern recognition capabilities. Its design emphasizes multi-degree-of-freedom (DOF) control while ensuring the prosthetic is lightweight and comfortable. The hand is primarily made of nylon, with aluminum alloy at the joints and rubber at the fingertips, weighing approximately 330 grams, which is 100 to 200 grams lighter than most commercial five-finger prosthetics, thus reducing user strain. It features 11 joints in total, with 5 active DOFs and passive adjustments for the thumb and wrist. The design includes mechanisms to release external forces at the finger joints, ensuring safety during daily use. Equipped with EMG sensors and a recognition stabilization filter, the hand improves signal stability and compensates for computing limitations. Controlled by EMG-based pattern recognition, the hand offers precise motion control, enhancing performance in tasks, especially in workplaces or environments requiring multiple tasks. The BIT-UEC-Hand is designed to enhance task execution, offering better adaptability to various motion patterns.
The experimental results revealed that the BIT-UEC-Hand significantly impacted both task performance and subjective disability levels over the long term. While the participants (A and B) showed improvements in task feasibility, the reliability of control decreased with the increased variety of motion patterns. Nevertheless, increasing the variety of motion patterns enhanced task performance. Questionnaire evaluations indicated that the MPH was more effective in alleviating workplace-related disability than improving everyday life activities. Specifically, Participant A, who had prior experience with pattern-recognition-controlled MPHs, surpassed the performance of traditional MPH users after approximately 80 days of home use, suggesting that extensive training is not necessary. Additionally, the survey results indicated that the pattern recognition control significantly reduced disability in the workplace, but its effect on daily life activities was less pronounced. The study also highlighted challenges with pattern recognition stability, where the number of motion patterns used (up to 4) affected control reliability and speed.
Overall, the long-term clinical application of the BIT-UEC-Hand multi-degree-of-freedom electromyography prosthetic hand is commendable. Survey results indicate that MPH excels in improving disability in the workplace compared to its application in daily life, particularly in work environments requiring bilateral hand coordination, where MPH's effectiveness is even more pronounced. However, it is essential to note the study’s limitations, including the inclusion of only 2 participants and differences in evaluation centers due to varying participant residences. Consequently, there were periods when it was not possible to conduct evaluations using the same assessment methods at the same time points. “Therefore, our future research will employ a consistent method for evaluation at the same time point during the evaluation period, enabling more detailed comparisons.” said Yuki Kuroda.
Authors of the paper include Yuki Kuroda, Yusuke Yamanoi, Hai Jiang, Yoshiko Yabuki, Yuki Inoue, Dianchun Bai, Yinlai Jiang, Jinying Zhu, and Hiroshi Yokoi.
This work was supported by JSPS KAKENHI (Grant Numbers JP23H00166, JP23H03785, and JP21K14125), JST SPRING (Grant Number JPMJSP2131), JKA through its Promotion funds from Keirin RACE, and the New Energy and Industrial Technology Development Organization (NEDO).
The paper, “Toward Cyborg Exploring Long-Term Clinical Outcomes of a Multi-Degree-of-Freedom Myoelectric Prosthetic Hand” was published in the journal Cyborg and Bionic Systems on Mar 18, 2025, at DOI: 10.34133/cbsystems.0195.