Background: Connected sensor technologies can capture raw data and analyze them using advanced statistical methods such as machine learning or artificial intelligence to generate interpretable behavioral or physiological outcomes. Previous research conducted on connected sensor technologies has focused on design, development, and validation. Published review studies 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: This study aimed to map research that focused on using connected sensor technologies to augment rehabilitation services by informing care decisions.
Methods: The Population, Concept, and Context framework will be used to define inclusion criteria. Relevant articles published between 2008 to the present will be included if (1) the study enrolled adults (population), (2) the intervention used at least one connected sensor technology and involved data transfer to a clinician so that the data could be used to inform the intervention (concept), and (3) the intervention was within the scope of 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 2 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 partners will review results to enhance interpretation and trustworthiness.
Results: We conducted initial searches to refine the search strategy in February 2024. 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.
Trial Registration: Open Science Framework jys53; https://osf.io/jys53.
International Registered Report Identifier (irrid): DERR1-10.2196/60496.
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http://dx.doi.org/10.2196/60496 | DOI Listing |
Sci Data
December 2024
Slovak University of Technology, Faculty of Informatics and Information Technologies, Bratislava, 842 16, Slovakia.
In this paper, we describe the dataset captured with our proprietary data capture solution mounted on top of a Land Rover Defender vehicle. The captured data are the real data of drives on various Slovak roads. The total dataset consist of almost 33 hours of driving with a automotive grade FPD Link camera with 30 fps and with additional sensors such as high-precision GNSS sensor and modem towards mobile data connectivity LTE and 5 G.
View Article and Find Full Text PDFNano Lett
December 2024
Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, United States.
Single-walled carbon nanotubes (SWCNTs) are fluorescent materials that have been developed as sensors for measuring the activities of enzymes. However, most sensors to date rely on end-point measurement and empirical functions to correlate enzyme concentrations with fluorescence responses. Less emphasis is put on analyzing time-dependent fluorescence responses and their connections with enzymatic kinetics.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Biomedical Engineering, University of Los Andes, Bogotá, Colombia.
Agriculture 4.0 technologies continue to see low adoption among small and medium-sized farmers, primarily because these solutions often fail to account for the specific challenges of rural areas. In this work, we propose and implement a design methodology to develop a Precision Agriculture solution aimed at assisting farmers in managing water stress in Hass avocado crops.
View Article and Find Full Text PDFAnal Chem
December 2024
NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong-Macao Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou 510515, China.
A simple, rapid, and visual approach is developed to perform diagnosis of urinary tract infection (UTI) and antimicrobial susceptibility testing (AST) by employing smart bifunctional DNA (bfDNA) sensors, exonuclease III, concatermers of CuO nanoparticles (CuONPs), and gold NPs (AuNPs) aggregation [AuNPs agglutination (AA)], namely, the bfDEC-AA method. The bfDNA sensors serve as probes for identifying 16S rRNA genes of bacterium or 18S rRNA of fungus and as mediators connecting the concatermers of CuONPs. The AA as a signal source is triggered by Cu(I)-catalyzed azide-alkyne cycloaddition click chemistry.
View Article and Find Full Text PDFMicrosyst Nanoeng
December 2024
Key Laboratory of MEMS of the Ministry of Education, Southeast University, Nanjing, 210096, China.
Piezoelectric resonance sensors are essential to many diverse applications associated with chemical and biological sensing. In general, they rely on continuously detecting the resonant frequency shift of piezoelectric resonators due to analytes accreting on their surfaces in vacuum, gas or fluid. Resolving the small analyte changes requires the resonators with a high quality factor.
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