Current State of Connected Sensor Technologies Used During Rehabilitation Care: Protocol for a Scoping Review (Preprint)

Abstract

BACKGROUND Connected sensor technologies can capture data using algorithms to generate measures of behavioral or physiological function. Previous research of such products has focused on design, development, and validation. Some reviews have either summarized general technological solutions to address specific behaviors such as physical activity or focused on remote monitoring solutions in specific patient populations. OBJECTIVE To map research that focuses on using connected sensor technologies to augment rehabilitation services. METHODS The Population, Concept, and Context framework was used to define inclusion criteria. Relevant articles will be included if the sample included adults (population), the intervention used at least one connected sensor technology and involved data transfer to clinician so that it could be used to inform the intervention (concept), and the intervention relates to rehabilitation (context). An initial search strategy will be built in Embase, peer reviewed, and then translated to Ovid MEDLINE ALL, Web of Science Core Collection, and CINAHL. Duplicates will be removed prior to screening articles for inclusion. Two independent reviewers will screen articles in two stages: title/abstract and full text. Discrepancies will be resolved through group discussion. Data from eligible articles relevant to population, concept, and context will be extracted. Descriptive statistics will be used to report findings, and relevant outcomes will include the type and frequency of connected sensor used and method of data sharing. Additional details will be narratively summarized and displayed in tables and figures. Key shareholders will review results to enhance interpretation and trustworthiness. RESULTS The results of this scoping review are expected in October 2024. CONCLUSIONS Results from the scoping review will identify critical areas of inquiry to advance the field of technology augmented rehabilitation. Results will also support the development of a longitudinal model to support long-term health outcomes. CLINICALTRIAL Open Science Framework (osf.io/jys53).