A Novel Mobile Device-Based Approach to Quantitative Mobility Measurements for Power Wheelchair Users

Area of Science:

• Rehabilitation Engineering
• Human-Computer Interaction
• Biomedical Signal Processing

Background:

• Quantitative mobility assessment is crucial for power wheelchair users' quality of life.
• Current methods lack widely adopted, non-intrusive quantitative mobility measurement tools.
• Existing mobile device data presents analysis challenges due to weak maneuver signals and sensor heterogeneity.

Purpose of the Study:

• To develop and validate a novel approach for non-intrusively measuring power wheelchair user mobility.
• To overcome data analysis challenges associated with mobile sensor data from power wheelchairs.
• To enable quantitative mobility assessment using common mobile devices like smartphones and smartwatches.

Main Methods:

• Developed a collaborative algorithm suite to process mobility data.
• Algorithms focus on noise reduction, identifying intrinsic wheelchair maneuver patterns, and stabilizing analysis.
• Implemented methods to mitigate data spikes and dips from abrupt maneuver changes.

Main Results:

• The proposed approach accurately identifies wheelchair maneuvers from mobile device data.
• Performance was consistent across different mobile device models and sensor placements.
• Successfully addressed challenges of data heterogeneity and weak signal patterns.

Conclusions:

• The novel approach enables accurate, non-intrusive quantitative mobility assessment for power wheelchair users.
• Utilizing personal mobile devices offers a practical solution for daily life data collection.
• This technology has the potential to significantly improve quality of life monitoring and support for wheelchair users.