Ajiboye Abidemi Bolu, Weir Richard F ff
Department of Biomedical Engineering, Rehabilitation Engineering Research Center and Prosthetic Research Laboratory, Northwestern University, Chicago, IL 60611, USA.
IEEE Trans Neural Syst Rehabil Eng. 2005 Sep;13(3):280-91. doi: 10.1109/TNSRE.2005.847357.
This paper presents a heuristic fuzzy logic approach to multiple electromyogram (EMG) pattern recognition for multifunctional prosthesis control. Basic signal statistics (mean and standard deviation) are used for membership function construction, and fuzzy c-means (FCMs) data clustering is used to automate the construction of a simple amplitude-driven inference rule base. The result is a system that is transparent to, and easily "tweaked" by, the prosthetist/clinician. Other algorithms in current literature assume a longer period of unperceivable delay, while the system we present has an update rate of 45.7 ms with little postprocessing time, making it suitable for real-time application. Five subjects were investigated (three with intact limbs, one with a unilateral transradial amputation, and one with a unilateral transradial limb-deficiency from birth). Four subjects were used for system offline analysis, and the remaining intact-limbed subject was used for system real-time analysis. We discriminated between four EMG patterns for subjects with intact limbs, and between three patterns for limb-deficient subjects. Overall classification rates ranged from 94% to 99%. The fuzzy algorithm also demonstrated success in real-time classification, both during steady state motions and motion state transitioning. This functionality allows for seamless control of multiple degrees-of-freedom in a multifunctional prosthesis.
本文提出了一种启发式模糊逻辑方法，用于多功能假肢控制中的多肌电图（EMG）模式识别。基本信号统计量（均值和标准差）用于构建隶属函数，模糊c均值（FCM）数据聚类用于自动构建简单的幅度驱动推理规则库。结果是一个对假肢技师/临床医生透明且易于“调整”的系统。当前文献中的其他算法假设存在较长的不可感知延迟，而我们提出的系统更新率为45.7毫秒，后处理时间很少，适用于实时应用。对五名受试者进行了研究（三名肢体健全者、一名单侧经桡骨截肢者和一名先天性单侧经桡骨肢体缺损者）。四名受试者用于系统离线分析，其余肢体健全的受试者用于系统实时分析。我们区分了肢体健全受试者的四种EMG模式和肢体缺损受试者的三种模式。总体分类率在94%至99%之间。模糊算法在稳态运动和运动状态转换期间的实时分类中也取得了成功。此功能允许对多功能假肢中的多个自由度进行无缝控制。
