Walking Distance Estimation Using Walking Canes with Inertial Sensors.

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Sensor Technology

Background:

• Cane users often require accurate mobility monitoring for rehabilitation and daily living.
• Existing methods for tracking cane user gait can be complex or inaccurate.
• Inertial sensor units offer a potential solution for unobtrusive gait analysis.

Purpose of the Study:

• To develop and validate a novel walking distance estimation algorithm for cane users.
• To adapt the algorithm for different types of canes (quadripod and standard).
• To assess the impact of sensor placement on algorithm performance.

Main Methods:

• An inertial navigation algorithm with an indirect Kalman filter was employed for velocity and position updates.
• A zero-velocity measurement-updating method was used for quadripod canes.
• An inverted pendulum model-based velocity-updating method was developed for standard canes.
• Experiments involved three walking trials with two cane types and varied sensor positions.

Main Results:

• The proposed algorithm demonstrated effective walking distance estimation for cane users.
• Different updating methods were successfully applied to quadripod and standard canes.
• Sensor placement variations were investigated, providing insights into optimal positioning.

Conclusions:

• The developed algorithm provides a viable solution for estimating walking distance in cane users.
• The adapted methods cater to the specific dynamics of different cane types.
• This research contributes to the advancement of assistive technology for mobility assessment.