Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA.
IEEE Trans Neural Syst Rehabil Eng. 2011 Oct;19(5):567-77. doi: 10.1109/TNSRE.2011.2161888. Epub 2011 Aug 18.
Recent advances in design of powered artificial legs have led to increased potential to allow lower limb amputees to actively recover from stumbles. To achieve this goal, promptly and accurately identifying stumbles is essential. This study aimed to 1) select potential stumble detection data sources that react reliably and quickly to stumbles and can be measured from a prosthesis, and 2) investigate two different approaches based on selected data sources to detect stumbles and classify stumble types in patients with transfemoral (TF) amputations during ambulation. In the experiments, the normal gait of TF amputees was perturbed by a controllable treadmill or when they walked on an obstacle course. The results showed that the acceleration of prosthetic foot can accurately detect the tested stumbling events 140-240 ms before the critical timing of falling and precisely classify the stumble type. However, the detector based on foot acceleration produced high false alarm rates, which challenged its real application. Combining electromyographic (EMG) signals recorded from the residual limb with the foot acceleration significantly reduced the false alarm rate but sacrificed the detection response time. The results of this study may lead to design of a stumble detection system for instrumented, powered artificial legs; however, continued engineering efforts are required to improve the detection performance and resolve the challenges that remain for implementing the stumble detector on prosthetic legs.
近年来，动力人工假腿的设计取得了进展，这使得下肢截肢者更有可能主动从跌倒中恢复。为了实现这一目标，及时、准确地识别跌倒至关重要。本研究旨在：1）选择潜在的跌倒检测数据源，这些数据源对跌倒反应可靠且迅速，并可从假肢上测量；2）根据选定的数据源，研究两种不同的方法，以检测和分类在跑步机或障碍物课程上行走的 TF 截肢患者的跌倒类型。实验中，TF 截肢者的正常步态通过可控跑步机或障碍物课程被扰乱。结果表明，假肢脚的加速度可以在跌倒的关键时刻前 140-240ms 准确检测到测试的跌倒事件，并准确分类跌倒类型。然而，基于脚加速度的检测器产生了较高的误报率，这对其实际应用提出了挑战。结合从残肢记录的肌电图（EMG）信号和脚加速度，可以显著降低误报率，但牺牲了检测响应时间。本研究的结果可能会导致为带仪器的动力人工假腿设计跌倒检测系统，但仍需要继续进行工程努力，以提高检测性能并解决在假肢上实施跌倒检测器仍存在的挑战。
