Telehealth, Wearable Sensors, and the Internet: Will They Improve Stroke Outcomes Through Increased Intensity of Therapy, Motivation, and Adherence to Rehabilitation Programs?

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.

Fast Periodic Visual Stimulation indexes preserved semantic memory in healthy ageing.

Behavioural studies investigating the preservation of semantic memory in healthy ageing have reported mixed findings. One suggested reason for this discrepancy is that the processes underpinning lexical access to semantic knowledge may be sensitive to ageing. It is therefore necessary to assess semantic memory utilising tasks that are not explicitly linguistic. In this study, a fast periodic visual stimulation (FPVS) paradigm coupled with EEG was used to assess the ability of younger and older adults to automatically distinguish between images by their semantic category. Participants were presented with a 6 Hz stream of images drawn from one semantic category except every fifth image (occurring at a rate of 1.2 Hz) which was drawn from an alternate semantic category. For both younger and older adults, results demonstrate successful and comparable semantic categorisation. This was detectable at the individual level for 71% and 72% of older and younger adults, respectively. Given the rapid presentation rate and absence of explicit instruction to categorise images, the task is unlikely to utilise linguistic strategies and suggests the maintenance of semantic memory in healthy ageing. Moreover, this study utilised mobile EEG equipment and short presentation times that would be suitable for practical application outside a research setting.