Date Presented 03/22/24
This presentation will discuss the feasibility and usability of a novel digital system that combines computer vision with smart sensors to measure upper limb functional movement performance and guide the user during their home exercise program.
Primary Author and Speaker: Sutanuka Bhattacharjya
Contributing Authors: Ashwin Ashok
PURPOSE: Diminished hand function is associated with a variety of chronic and age-related conditions frequently leading to lifetime disability and dependence on caregivers due to limitations in performing many daily tasks. Whereas ongoing practice of upper limb movement is required to optimize motor performance post-discharge, long-term home rehabilitation programs provide inadequate support to users. The purpose of this study is to investigate the usability of DigiHand, a digital rehabilitation system and its ability to support home-based upper limb rehabilitation of stroke survivors.
DESIGN: A cross sectional phenomenological design was used utilizing semi-structured interviews with five community-dwelling stroke survivors with upper limb impairment.
METHOD: The DigiHand system guided the users during activities (i.e. moving a mug to a shelf, or pouring from a mug and taking a sip) and provided feedback to the user. The users were interviewed about their experience with the set-up process, their perceived difficulty level, and their opinion of the system’s ability to support their home-based rehabilitation.
RESULTS: Thematic analysis led to two primary themes – (1) the users reported that the DigiHand was useful because it’s tasks, order, and set-up were adaptable and personalized to the client’s needs and preferences; (2) the personal factors of the client and the system itself were compatible for successful engagement with the system.
CONCLUSION: The findings indicated that the DigiHand system can be used to provide objective performance-based feedback to users during home-based rehabilitation. The smart objects are designed by using daily use objects (e.g. mug) augmented with smart sensors and computer vision technology that capture arm and hand movement during functional performance can provide objective performance-based feedback to users thus keeping them informed about their progress and facilitate active engagement in home exercise program.
References
Ashok, A., & Bhattacharjya, S. Virtual Hand Rehabilitation using a Mobile Camera. Poster presentation at 2020 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). Published in IEEE Xplore, https://doi.org/10.1145/3384420.3431771.
Bhattacharjya, S., Stafford, M., Cavuoto, L., Yang, Z., Song, C., Subryan, H., Xu, W., Langan, J. (2019). Harnessing smartphone technology and three-dimensional printing to create a mobile rehabilitation system, mRehab: Assessment of usability and consistency in measurement. Journal of NeuroEngineering and Rehabilitation, 16. PMID: 31665036 PMCID: PMC6820925. https://doi.org/10.1186/s12984-019-0592-y
Winstein CJ, Wolf SL, Dromerick AW, et al. Effect of a Task-Oriented Rehabilitation Program on Upper Extremity Recovery Following Motor Stroke: The ICARE Randomized Clinical Trial. JAMA. 2016;315(6):571–581.
Wolf SL, Wolf SL, Lecraw DE, et al. Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Experimental Neurology. 1989;104(2):125–132.
