ArticleJournal of neuroengineering and rehabilitation2019
Egocentric video: a new tool for capturing hand use of individuals with spinal cord injury at home.
Article in Journal of neuroengineering and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 54 citations in OpenAlex.
- Video summarization for home-based egocentric footage in spinal cord injury rehabilitation.Biomedical engineering online · 2026Article
- Trends and Innovations in Wearable Technology for Motor Rehabilitation, Prediction, and Monitoring: A Comprehensive Review.Sensors (Basel, Switzerland) · 2024Review
- Artificial intelligence: a new cutting-edge tool in spine surgery.Asian spine journal · 2024Article
- Counting Finger and Wrist Movements Using Only a Wrist-Worn, Inertial Measurement Unit: Toward Practical Wearable Sensing for Hand-Related Healthcare Applications.Sensors (Basel, Switzerland) · 2023Article
- Capturing hand use of individuals with spinal cord injury at home using egocentric video: a feasibility study.Spinal cord series and cases · 2021Article
- Magnetically Counting Hand Movements: Validation of a Calibration-Free Algorithm and Application to Testing the Threshold Hypothesis of Real-World Hand Use after Stroke.Sensors (Basel, Switzerland) · 2021Article
- Perspectives and recommendations of individuals with tetraplegia regarding wearable cameras for monitoring hand function at home: Insights from a community-based study.The journal of spinal cord medicine · 2021Article
- Identifying Hand Use and Hand Roles After Stroke Using Egocentric Video.IEEE journal of translational engineering in health and medicine · 2021Article
- Validity of Novel Outcome Measures for Hand Function Performance After Stroke Using Egocentric Video.Neurorehabilitation and neural repairArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.