Abstract
BackgroundCurrent 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 aims to monitor functional hand use outside of clinical settings.MethodsThe 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.ResultsThe output from the algorithm was compared with a manual labelling of the video, yielding F1-scores of 0.74 ± 0.15 for the left hand and 0.73 ± 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.ConclusionsThese results demonstrate the potential of a wearable egocentric camera for capturing quantitative measures of hand use at home.
Highlights
Upper extremity (UE) impairment can severely limit individuals’ ability to perform activities of daily living (ADLs)
A recent study in stroke survivors found that improvements in motor function according to clinicbased outcome measures (capacity, as defined in Marino’s modification of the International classification of functioning, disability and health (ICF) model [11]) do not necessarily translate into increased limb use in the community, as measured by accelerometry [12]
This testing set consisted of 8 males and 1 female with an average age of 52 ± 13 years and an average upper extremity motor score (UEMS) of 17 ± 4
Summary
Upper extremity (UE) impairment can severely limit individuals’ ability to perform activities of daily living (ADLs). A recent study in stroke survivors found that improvements in motor function according to clinicbased outcome measures (capacity, as defined in Marino’s modification of the International classification of functioning, disability and health (ICF) model [11]) do not necessarily translate into increased limb use in the community (performance), as measured by accelerometry [12]. These findings point to the need for novel outcome measures that can directly measure performance and better describe the impact of new interventions on the daily lives of individuals with SCI. A wearable first-person (egocentric) camera system is presented that aims to monitor functional hand use outside of clinical settings
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