Feasibility evaluation of a novel wearable clothing technology that can be worn at home to assess real life gait analysis

Background
Traditional gait analysis is restricted to lab settings, providing only brief and episodic measurements of rehabilitation progress. The novel upLYFT wearable system integrates movement analysis in clothing, producing decentralised at-home care that enables remote rehabilitation assessments.

Purpose
The upLYFT system integrates IMUs and force sensors in “smart” clothing to provide a user-centred approach to movement and gait analysis in healthcare. Its applications have the potential to further extend to early detection of movement disorders, illness prevention and the mitigation of fall risk.

Methods
All IMU sensors are removable, connected in the leggings via machine-washable conductive textile, and powered by a single removable unit on the pelvis. Processing is performed through novel and proprietary algorithms, both in real-time (to enable the subject to control rehabilitation games with their movement) and on the cloud for a more in-depth analysis of metrics.

In this evaluation , the data was collected using the upLYFT wearable system and Vicon Motion Tracking system to assess kinematics and kinetics accuracy. The data presented comes from 2 able-bodied subjects performing several lower limb lying rehabilitation exercises (simulating bed-bound conditions).

Results
Across all subjects and exercises, the upLYFT wearable system achieved an average correlation of 97.1% ± 1.9% in the main movement axes of each corresponding exercise. From these kinematics, metrics such as range and speed of motion, holding times, joint loads/torques/power, and movement quality can also be measured.

Conclusion
Smart clothing can facilitate at-home customised rehabilitation plans based on individual gait /movement assessments. Further clinical evaluation and gamification are underway, aiming to improve patient adherence to rehabilitation , and assess functional outcomes.

Implications
The upLYFT wearable technology enables long-term data collection and trend analysis for users and clinicians. This cost-effective tool has broad applications, including virtual hospital care, early post-operative discharge, movement and neurological assessment, complication reduction, early problem detection, and sports performance monitoring.
It can compare metrics between impaired and healthy limbs, providing a clearer percentage of recovery against baseline. As adoption grows, the data collected will allow clinicians to benchmark progress within diagnostic cohorts and tailor rehabilitation plans more precisely.