A robust real-time gait event detection using wireless gyroscope and its application on normal and altered gaits

Area of Science:

• Biomechanics
• Biomedical Engineering
• Wearable Technology

Background:

• Gait event detection is crucial for clinical analysis and designing assistive devices like orthoses and functional electrical stimulation (FES) systems.
• Current gyroscope-based methods for detecting heel-strike (HS) and toe-off (TO) suffer from significant real-time delays.
• Reducing these delays is essential for practical applications in real-time gait monitoring.

Purpose of the Study:

• To propose and validate a novel algorithm for accurate and real-time detection of gait events (HS and TO).
• To address and minimize the time delays associated with existing gait event detection methods.
• To improve the performance of gait analysis for clinical and engineering applications.

Main Methods:

• A new algorithm combining heuristic approaches and the zero-crossing method was developed to identify heel-strike and toe-off events.
• Experiments were conducted with participants undergoing normal walking, walking with knee braces, and walking with ankle braces.
• Both overground and treadmill walking conditions were utilized to comprehensively validate the algorithm's performance.

Main Results:

• The proposed method demonstrated a comparable detection rate to established gait detection algorithms.
• A significant reduction in time delays was achieved, averaging 100 ms.
• The algorithm proved effective across various walking conditions, including those with assistive devices.

Conclusions:

• The developed algorithm offers a viable solution for real-time gait event detection with reduced time delays.
• This advancement has the potential to enhance the functionality and responsiveness of real-time gait monitoring devices, orthoses, and FES systems.
• The findings support the integration of this method into future biomedical engineering and clinical biomechanics research.