School of Informatics, The University of Edinburgh, Edinburgh EH8 9YL, UK.
School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
Sensors (Basel). 2021 Jan 24;21(3):763. doi: 10.3390/s21030763.
Understanding how upper-limb prostheses are used in daily life helps to improve the design and robustness of prosthesis control algorithms and prosthetic components. However, only a very small fraction of published research includes prosthesis use in community settings. The cost, limited battery life, and poor generalisation may be the main reasons limiting the implementation of home-based applications. In this work, we introduce the design of a cost-effective Arduino-based myoelectric control system with wearable electromyogram (EMG) sensors. The design considerations focused on home studies, so the robustness, user-friendly control adjustments, and user supports were the main concerns. Three control algorithms, namely, direct control, abstract control, and linear discriminant analysis (LDA) classification, were implemented in the system. In this paper, we will share our design principles and report the robustness of the system in continuous operation in the laboratory. In addition, we will show a first real-time implementation of the abstract decoder for prosthesis control with an able-bodied participant.
了解上肢假肢在日常生活中的使用情况有助于改进假肢控制算法和假肢组件的设计和稳健性。然而，只有很少一部分已发表的研究包括在社区环境中使用假肢。成本高、电池寿命有限以及推广效果不佳可能是限制基于家庭应用的主要原因。在这项工作中，我们介绍了一种基于成本效益高的 Arduino 的肌电控制系统的设计，该系统带有可穿戴肌电图 (EMG) 传感器。设计考虑因素主要集中在家庭研究上，因此稳健性、用户友好的控制调整和用户支持是主要关注点。该系统实现了三种控制算法，即直接控制、抽象控制和线性判别分析 (LDA) 分类。本文将分享我们的设计原则，并报告系统在实验室中连续运行的稳健性。此外，我们将展示一个健全参与者的假肢控制抽象解码器的实时实现。
