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A Wearable Personalised Sonification and Biofeedback Device to Enhance Movement Awareness
Toh Yen Pang1, Thomas Connelly1, Frank Feltham2
1Biomedical Engineering, School of Engineering, STEM College, RMIT University, Melbourne, VIC 3000, Australia.
Sensors (Basel, Switzerland)
|August 10, 2024
Summary
This study developed a wearable device using inertial measurement units (IMUs) for personalized sound feedback to improve gait and balance. Preliminary tests show enhanced movement awareness, aiding rehabilitation for individuals with irregular gait.
Area of Science:
- Biomechanics
- Rehabilitation Engineering
- Wearable Technology
Background:
- Movement sonification shows promise for rehabilitation and motion control.
- Existing systems for gait detection and sonification face challenges in cost-effectiveness, usability, and reliability.
- Enhanced movement awareness is crucial for individuals with irregular gait and posture.
Purpose of the Study:
- To introduce a novel wearable personalized sonification and biofeedback device.
- To improve movement awareness for individuals with irregular gait and posture.
- To facilitate gait correction and enhance functional mobility through real-time auditory cues.
Main Methods:
- Integration of inertial measurement units (IMUs) and MATLAB for data processing.
- Development of a wearable sensor system for capturing kinematic parameters.
- Generation of real-time auditory feedback (discrete and continuous tones) based on heel strike and sagittal plane rotations.
Main Results:
- Preliminary testing with 20 participants demonstrated promising improvements in movement awareness via auditory cues.
- The system showed potential for enhancing gait and balance.
- The device offers real-time feedback for posture and movement adjustments.
Conclusions:
- The developed wearable sonification and biofeedback device shows potential for gait rehabilitation.
- Auditory cues can significantly improve movement awareness, benefiting individuals with compromised gait.
- Future research should focus on real-world applications and diverse populations, including the elderly and Parkinson's patients.

