Gait Analysis Accuracy Difference with Different Dimensions of Flexible Capacitance Sensors

Area of Science:

• Biomedical Engineering
• Neurology
• Rehabilitation Science

Background:

• Stroke frequently leads to neurological impairments, notably gait pathologies requiring accurate gait analysis.
• Current gait analysis methods face limitations in real-world application (in situ) and are susceptible to environmental interference.
• Flexible capacitance sensors offer a promising alternative for robust and portable gait assessment.

Purpose of the Study:

• To determine optimal dimensions for flexible capacitance sensors used in gait analysis.
• To address the lack of comparative performance data for different sensor sizes.
• To enhance the accuracy and practicality of gait analysis for neurological conditions.

Main Methods:

• Fabrication of seven flexible capacitance sensors with dimensions tailored to adult anthropometrics.
• Sensor characterization through 100 oscillation cycles to assess hysteresis error.
• Validation of sensor performance with four subjects walking on a treadmill at 3.6 km/h.
• Comparative analysis of sensor data against video-based kinematic analysis (Kinovea) to calculate Root Mean Square (RMS) error.

Main Results:

• Minimum hysteresis error of 8% was recorded during sensor characterization.
• The 49 × 8 mm sensor achieved the lowest RMS error of 3.13° when compared to ankle angle data.
• This specific sensor dimension exhibited the highest accuracy in gait analysis.

Conclusions:

• The study successfully identified optimal dimensions for flexible capacitance sensors for accurate gait analysis.
• The findings provide empirical evidence to guide the selection of sensor size for improved gait assessment post-stroke.
• These results facilitate the development of more effective and reliable gait analysis tools.