Sport and Exercise Sciences Research Institute, University of Ulster, School of Sports Studies, Jordanstown, Co. Antrim, Northern Ireland.
Gait Posture. 2009 Nov;30(4):523-7. doi: 10.1016/j.gaitpost.2009.07.128. Epub 2009 Sep 3.
Real-time gait event detection is a requirement for functional electrical stimulation and gait biofeedback. This gait event detection should ideally be achieved using an ambulatory system of durable, lightweight, low-cost sensors. Previous research has reported issues with durability in footswitch systems. Therefore, this study describes the development and assessment of novel detection algorithms using footswitch and accelerometer sensors on 12 healthy individuals. Subjects were equipped with one force sensitive resistor on the heel, one accelerometer at the foot, and one accelerometer at the knee. Subjects performed 10, 8-m walking trials in each of three conditions: normal, slow, and altered (reduced knee ROM) walking. Data from a subset of four subjects were used to develop prediction algorithms for initial contact (IC). Subsequently, these algorithms were tested on the remaining eight subjects against standard forceplate IC data (threshold of 5 N on a rising edge). The footswitch force threshold algorithm was most accurate for IC detection (mean absolute error of 2.4+/-2.1 ms) and was significantly more accurate (p<0.001) than the optimal accelerometer algorithm (mean absolute error of 9.5+/-9.0 ms). The optimal accelerometer algorithm used data from both accelerometers, with IC determined from the second derivative of foot fore-aft acceleration. The error results for footswitch and accelerometer algorithms are lower (approximately 60%) than in previous research on ambulatory real-time gait event detection systems. Currently, footswitch systems must be recommended over accelerometer systems for accurate detection of IC, however, further research into accelerometer algorithms is merited due to its advantages as a durable, low-cost sensor.
实时步态事件检测是功能性电刺激和步态生物反馈的要求。这种步态事件检测理想情况下应使用耐用、轻便、低成本传感器的可移动系统来实现。先前的研究报告了脚踏开关系统耐用性方面的问题。因此，本研究描述了使用脚踏开关和加速度计传感器在 12 名健康个体上开发和评估新型检测算法的情况。受试者的脚跟配备了一个力敏电阻器，脚部安装了一个加速度计，膝盖处安装了一个加速度计。受试者在正常、缓慢和改变（减少膝关节 ROM）三种条件下分别进行了 10 次、8 米步行试验。从四名受试者的数据中选择了一部分，用于开发初始接触（IC）的预测算法。随后，针对标准测力板 IC 数据（上升沿 5 N 的阈值）对其余 8 名受试者测试了这些算法。脚踏开关力阈值算法在 IC 检测方面最准确（平均绝对误差为 2.4+/-2.1 ms），明显比最佳加速度计算法（平均绝对误差为 9.5+/-9.0 ms）更准确（p<0.001）。最佳加速度计算法同时使用了两个加速度计的数据，IC 由足部前后加速度的二阶导数确定。脚踏开关和加速度计算法的误差结果（约 60%）低于之前对可移动实时步态事件检测系统的研究。目前，由于脚踏开关系统能够准确检测 IC，因此必须推荐使用脚踏开关系统，而不是加速度计系统，但由于其作为耐用、低成本传感器的优势，对加速度计算法进行进一步研究是值得的。
