Emerging Technologies as a Support for Proprioceptive Rehabilitation: a Scoping Review

Uziel  Trujillo Colón; José Luis Hernández Hernández; Eduardo De La Cruz Gámez; Rayma Ireri  Maldonado Astudillo; Ricardo Salazar

doi:10.17488/RMIB.46.1.1472

Authors

Uziel Trujillo Colón Universidad Autónoma de Guerrero, México https://orcid.org/0009-0006-8238-6163
José Luis Hernández Hernández Universidad Autónoma de Guerrero, México
Eduardo De La Cruz Gámez Tecnológico Nacional de México/Instituto Tecnológico de Acapulco, México https://orcid.org/0000-0003-3318-788X
Rayma Ireri Maldonado Astudillo Universidad Autónoma de Guerrero, México https://orcid.org/0000-0001-8880-4465
Ricardo Salazar Universidad Autónoma de Guerrero / CONAHCYT, México https://orcid.org/0000-0002-5844-8321

DOI:

https://doi.org/10.17488/RMIB.46.1.1472

Keywords:

convolutional neural networks, exoskeletons, mechanical devices, therapies

Abstract

Proprioceptive training encompasses interventions aimed at enhancing proprioceptive function to improve motor function performance. Three types of interventions are considered: Movement Training (MT); Somatosensory Stimulation Training (SST), and Force Reproduction Training (FRT). This study analyzes the potential of emerging technologies, such as exoskeletons, mechanical devices, Artificial Intelligence (AI), Virtual Reality (VR), the Internet of Things (IoT), and sensors, highlighting their application in proprioceptive therapies, with particular emphasis on MT, SST, and FRT. A total of 107 articles published in scientific journals were reviewed, of which 30 complied with inclusion criteria: 1) Implementation of proprioceptive intervention therapy; 2) use of technology; 3) publication after 2019, and 4) written in the English language. Of the studies analyzed, 43 % employed AI, indicating its increasing adoption, while IoT was the least utilized technology, with only 3 %. It is concluded that emerging technologies plays a crucial role in proprioceptive rehabilitation by enabling the analysis of data before and after surgical procedures, real-time pattern assessment, and the classification of sensory signals. Moreover, it offers alternatives to traditional measurement methods.

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