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Updated: Feb 28, 2026
A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
Telehealth, Wearable Sensors, and the Internet: Will They Improve Stroke Outcomes Through Increased Intensity of
Jane H Burridge1, Alan Chong W Lee, Ruth Turk
1Faculty of Health Sciences (J.H.B., R.T., M.S., J.W., A.-M.H., C.M.) and Faculty of Health Psychology (L.Y.), University of Southampton, United Kingdom; Mount Saint Mary's University, Los Angeles, California (A.C.W.L.); The University of Maryland School of Medicine, University of Maryland, Baltimore, Maryland (J.W.); Faculty of Engineering, Department of Mechanical Engineering, Imperial College London, London, United Kingdom (R.V., E.F.); and Department of Neurology, North Bristol NHS Trust, United Kingdom (P.C.).
Background And Purpose:
Stroke, predominantly a condition of older age, is a major cause of acquired disability in the global population and puts an increasing burden on health care resources. Clear evidence for the importance of intensity of therapy in optimizing functional outcomes is found in animal models, supported by neuroimaging and behavioral research, and strengthened by recent meta-analyses from multiple clinical trials. However, providing intensive therapy using conventional treatment paradigms is expensive and sometimes not feasible because of social and environmental factors. This article addresses the need for cost-effective increased intensity of practice and suggests potential benefits of telehealth (TH) as an innovative model of care in physical therapy.
Summary Of Key Points:
We provide an overview of TH and present evidence that a web-supported program, used in conjunction with constraint-induced therapy (CIT), can increase intensity and adherence to a rehabilitation regimen. The design and feasibility testing of this web-based program, "LifeCIT," is presented. We describe how wearable sensors can monitor activity and provide feedback to patients and therapists. The methodology for the development of a wearable device with embedded inertial and mechanomyographic sensors, algorithms to classify functional movement, and a graphical user interface to present meaningful data to patients to support a home exercise program is explained.
Recommendations For Clinical Practice:
We propose that wearable sensor technologies and TH programs have the potential to provide most-effective, intensive, home-based stroke rehabilitation.
