A Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Biomechanics

Background:

• Lower extremity amputees face mobility challenges impacting quality of life.
• Wearable sensors are key for assessing gait parameters and enabling prosthetic control.
• Accurate gait event detection is vital for effective lower limb prosthesis function.

Purpose of the Study:

• To present a real-time gait event detection system for lower limb amputees.
• To utilize a wireless gyroscope attached to the shank for detecting gait events.
• To validate the system's performance during level ground and ramp activities.

Main Methods:

• A wireless gyroscope was attached to the shank of participants (healthy, transtibial amputee, transfemoral amputee).
• Real-time detection of gait events, specifically Initial Contact (IC) and Toe Off (TO), was performed.
• Data was collected during level ground and ramp walking activities.

Main Results:

• The system achieved 100% detection rate for all activities across all subject groups.
• Time differences in detecting IC and TO events were larger for transfemoral amputees compared to controls and transtibial amputees.
• The observed time difference latency was within ±50 ms.

Conclusions:

• The proposed system accurately detects Initial Contact and Toe Off events in both healthy individuals and lower extremity amputees.
• This technology can be applied in clinical settings for rehabilitation and performance assessment of prosthesis users.
• Real-time gait event detection is feasible and beneficial for improving prosthetic control and user mobility.