A Rehabilitation-Internet-of-Things in the Home to Augment Motor Skills and Exercise Training
- 24 November 2016
- journal article
- Published by SAGE Publications in Neurorehabilitation and Neural Repair
- Vol. 31 (3), 217-227
- https://doi.org/10.1177/1545968316680490
Abstract
Although motor learning theory has led to evidence-based practices, few trials have revealed the superiority of one theory-based therapy over another after stroke. Nor have improvements in skills been as clinically robust as one might hope. We review some possible explanations, then potential technology-enabled solutions. Over the Internet, the type, quantity, and quality of practice and exercise in the home and community can be monitored remotely and feedback provided to optimize training frequency, intensity, and progression at home. A theory-driven foundation of synergistic interventions for walking, reaching and grasping, strengthening, and fitness could be provided by a bundle of home-based Rehabilitation Internet-of-Things (RIoT) devices. A RIoT might include wearable, activity-recognition sensors and instrumented rehabilitation devices with radio transmission to a smartphone or tablet to continuously measure repetitions, speed, accuracy, forces, and temporal spatial features of movement. Using telerehabilitation resources, a therapist would interpret the data and provide behavioral training for self-management via goal setting and instruction to increase compliance and long-term carryover. On top of this user-friendly, safe, and conceptually sound foundation to support more opportunity for practice, experimental interventions could be tested or additions and replacements made, perhaps drawing from virtual reality and gaming programs or robots. RIoT devices continuously measure the actual amount of quality practice; improvements and plateaus over time in strength, fitness, and skills; and activity and participation in home and community settings. Investigators may gain more control over some of the confounders of their trials and patients will have access to inexpensive therapies.Keywords
This publication has 81 references indexed in Scilit:
- Scaling Up mHealth: Where Is the Evidence?PLoS Medicine, 2013
- Effects of Telerehabilitation on Physical Function and Disability for Stroke PatientsStroke, 2012
- A review of wearable sensors and systems with application in rehabilitationJournal of NeuroEngineering and Rehabilitation, 2012
- Getting Neurorehabilitation RightNeurorehabilitation and Neural Repair, 2012
- Should Body Weight–Supported Treadmill Training and Robotic-Assistive Steppers for Locomotor Training Trot Back to the Starting Gate?Neurorehabilitation and Neural Repair, 2012
- A Systematic Review of Instruments Assessing Participation: Challenges in Defining ParticipationArchives of Physical Medicine and Rehabilitation, 2011
- Body-Weight–Supported Treadmill Rehabilitation after StrokeThe New England Journal of Medicine, 2011
- Aerobic Exercise Improves Cognition and Motor Function PoststrokeNeurorehabilitation and Neural Repair, 2009
- Be smart, exercise your heart: exercise effects on brain and cognitionNature Reviews Neuroscience, 2008
- The Evolution of Walking-Related Outcomes Over the First 12 Weeks of Rehabilitation for Incomplete Traumatic Spinal Cord Injury: The Multicenter Randomized Spinal Cord Injury Locomotor TrialNeurorehabilitation and Neural Repair, 2007