Category: Stroke; Technology (e.g. robotics, assistive technology, mHealth)
Objective : To assess the usability of a portable home-based functional rehabilitation system.
Design : A mixed-methods approach was used with participant interviews and usability surveys. Following training, individuals with stroke used the mRehab system for 6 weeks in a home-based setting. Participants’ qualitative reports regarding usability of mRehab were integrated with their survey reports and quantitative performance data.
Setting : Home-based setting
Participants (or Animals, Specimens, Cadavers) : Convenience sample of 12 individuals with stroke.
Interventions : Participants used mRehab - a system designed for functional exercise of upper extremities which utilizes 3D printed household items such as a mug, bowl, key and doorknob coupled with smartphone technology. mRehab can consistently capture movement time, and smoothness during the performance of functional tasks such as transferring the mug or the bowl horizontally or vertically, walking with the mug, taking a sip from the mug, turning a door knob, or typing phone numbers. The smartphone app also provides performance feedback to the user so they can self-monitor their performance.
Main Outcome Measure(s) :
Interviews and surveys to identify usability of mRehab based on the Technology Acceptance Model and System Usability Scale
Results : Common themes reported by participants showed a positive response to mRehab with some suggestions for improvements. Participants liked the functional nature of the activities. Participants reported an interest in activities they perceived to be challenging. These were the activities that they more frequently practiced. Some participants indicated a need for customizing the feedback to be more interpretable. Overall, most participants indicated that they would like to continue using the mRehab system at home.
Conclusions : This portable rehabilitation system is well accepted. Technology can be used in home rehabilitation to help clients with stroke self-manage their long-term recovery.
Sutanuka Bhattacharjya– Post Doctoral Associate, University at Buffalo, Buffalo, New York
Lora Cavuoto– Associate Professor, University at Buffalo, Buffalo, New York
Zhengxiong Li– Student, SUNY, University at Buffalo, Buffalo, New York
Baicheng Chen– Student, University at Buffalo, BUFFALO, New York
Heamchand Subryan– Programmer/Analyst, IDEA Center, University at Buffalo, Buffalo, New York
Wenyao Xu– Associate Professor, University at Buffalo, Buffalo, New York
Jeanne Langan– Assistant Professor, University of Buffalo, Buffalo, New York