Real-time kinematic-based detection of foot-strike during walking

Detection of foot-strike events is an integral part of gait analysis, as it allows the temporal registration of gait cycles. At the same time, it is necessary to register gait phases in real-time for applications such as wearable assistive devices and gait biofeedback that work synchronously with the human gait. Although many algorithms have been proposed for detecting foot-strikes with either wearable (e.g. Inertial Measurement Units (IMUs)) or non-wearable (e.g. force plates) sensors, there is a great need for real-time algorithms that rely only on recording the kinematics of the leg motion. This work proposes a novel and efficient kinematic algorithm, called the Foot VErtical & Sagittal Position Algorithm (F-VESPA), which has several advantages over existing methods. First, it accurately estimates foot-strike events using kinematic data without requiring access to future data points, hence achieving reduced latency during real-time implementation. Moreover, it does not require tuning of the utilized parameters, rendering it robust to different subjects and treadmill speeds. The algorithm is tested in a large set of subjects across various treadmill speeds, and it is shown to outperform even offline implementations of existing prominent kinematic algorithms. Using a 150 Hz data collection system, the FVESPA achieved a median of 33 ms for the total true errors in detecting foot-strike. The F-VESPA is a highly responsive kinematic algorithm that can detect foot-strike events in real-time, with high accuracy, robustness and reduced latency, enabling real-time temporal registration of gait cycles.

Automated summary

The study presents a novel kinematic algorithm, F-VESPA, which accurately detects foot-strike events in real-time without requiring access to future data points. It demonstrates high accuracy, robustness, and reduced latency, outperforming existing prominent kinematic algorithms even in offline implementations.