Smart Objects for Clinical Rehabilitation and Education: A Scoping Review of Design, Sensing, and Validation
Interaction with physical objects plays a key role in the development, assessment, and treatment of cognitive and motor skills across the lifespan. In recent years, this interaction has been enhanced by smart objects, namely everyday items augmented with embedded sensing, processing, and feedback capabilities. These objects enable objective behavioural data collection while preserving natural and engaging human–object interactions. However, the literature remains fragmented and often focused on specific applications or interaction paradigms. This scoping review provides an overview of smart objects developed for clinical and educational contexts, with intended uses including assessment, treatment, training, education, and data collection to support machine learning approaches. Forty-two studies published from 2010 up to the final search date of 29 June 2026 were analysed following the PRISMA-ScR guidelines. The review adopts a design- and hardware-oriented perspective, classifying smart objects according to physical shape, intended use, target population, and validation level. Particular attention is given to embedded electronic components, measured parameters, and the exploitation of sensing and feedback technologies during human–object interaction. By synthesising current solutions, this review highlights emerging trends, recurring limitations, and open challenges related to design choices, technological constraints, and experimental validation, supporting the development of robust, adaptable, and real-world-ready smart objects.
Authors
- Filippo Cavallo (ORCID: https://orcid.org/0000-0001-7432-5033)
- Laura Fiorini (ORCID: https://orcid.org/0000-0001-5784-3752)
- M. V. Maselli (ORCID: https://orcid.org/0009-0004-0893-6513)
- L. Pugi
Institutions
- University of Florence (IT)
Publication Details
- Journal
- Sensors
- Published
- 2026-09-14
- DOI
- https://doi.org/10.3390/s26185812
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00