User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use.

User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use.
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DOI:
10.1109/tnsre.2022.3221558
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发表时间:
2023
期刊:
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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随着更先进的假肢越来越多的可用性与经桡截肢的个人现在可以适合单到多自由度的手。这些多握手的可靠和准确控制仍然具有挑战性。这是第一个多用户的研究,调查在家里的控制和使用多握手假肢模式识别和直接控制。经桡动脉截肢的患者安装并接受使用OSSUR i-Limb Ultra Revolution和Coapt COMPUTER CONTROL系统的培训。他们参加了两个为期8周的家庭试验,使用肌电直接和模式识别控制下的手在随机顺序。而在家里,参与者表现出更广泛的使用握模式识别相比,直接控制。在家庭试验后,与直接控制相比,使用模式识别控制时,他们在肌电控制能力评估(ACMC)结果测量方面表现出显着改善;其他结果测量显示控制风格之间没有差异。此外,这项研究提供了一个独特的机会,以评估肌电图信号在家庭使用。对校准数据的离线分析显示,用户在三到五次抓握的范围内准确率为81.5% [7.1]。尽管在某些校准过程中识别出EMG信号噪声,但总体EMG质量足以为用户提供等于或优于直接控制的控制性能。
With the increasing availability of more advanced prostheses individuals with a transradial amputation can now be fit with single to multi-degree of freedom hands. Reliable and accurate control of these multi-grip hands still remains challenging. This is the first multi-user study to investigate at-home control and use of a multi-grip hand prosthesis under pattern recognition and direct control. Individuals with a transradial amputation were fitted with and trained to use an OSSUR i-Limb Ultra Revolution with Coapt COMPLETE CONTROL system. They participated in two 8-week home trials using the hand under myoelectric direct and pattern recognition control in a randomized order. While at home, participants demonstrated broader usage of grips in pattern recognition compared to direct control. After the home trial, they showed significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control; other outcome measures showed no differences between control styles. Additionally, this study provided a unique opportunity to evaluate EMG signals during home use. Offline analysis of calibration data showed that users were 81.5% [7.1] accurate across a range of three to five grips. Although EMG signal noise was identified during some calibrations, overall EMG quality was sufficient to provide users with control performance at or better than direct control.