Egocentric Video: A New Tool for Capturing Hand Use of Individuals with Spinal Cord Injury at Home
This provides a new tool for quantitative assessment of hand use at home for individuals with spinal cord injury, addressing a gap in current outcome measures, though it is incremental as it applies existing computer vision methods to a specific domain.
The paper tackled the problem of monitoring hand use in individuals with cervical spinal cord injury outside clinical settings by developing a wearable egocentric camera system with computer vision algorithms, achieving F1-scores of 0.74 for left hand and 0.73 for right hand in detecting hand-object interactions and moderate correlations (ρ up to 0.55) with manual labels for functional measures.
Current upper extremity outcome measures for persons with cervical spinal cord injury (cSCI) lack the ability to directly collect quantitative information in home and community environments. A wearable first-person (egocentric) camera system is presented that can monitor functional hand use outside of clinical settings. The system is based on computer vision algorithms that detect the hand, segment the hand outline, distinguish the user's left or right hand, and detect functional interactions of the hand with objects during activities of daily living. The algorithm was evaluated using egocentric video recordings from 9 participants with cSCI, obtained in a home simulation laboratory. The system produces a binary hand-object interaction decision for each video frame, based on features reflecting motion cues of the hand, hand shape and colour characteristics of the scene. This output was compared with a manual labelling of the video, yielding F1-scores of 0.74 $\pm$ 0.15 for the left hand and 0.73 $\pm$ 0.15 for the right hand. From the resulting frame-by-frame binary data, functional hand use measures were extracted: the amount of total interaction as a percentage of testing time, the average duration of interactions in seconds, and the number of interactions per hour. Moderate and significant correlations were found when comparing these output measures to the results of the manual labelling, with $ρ$ = 0.40, 0.54 and 0.55 respectively. These results demonstrate the potential of a wearable egocentric camera for capturing quantitative measures of hand use at home.