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A Systematic Review of Insole Sensor Technology: Recent Studies and Future Directions.

Authors :
Santos, Vítor Miguel
Gomes, Beatriz B.
Neto, Maria Augusta
Amaro, Ana Martins
Source :
Applied Sciences (2076-3417); Jul2024, Vol. 14 Issue 14, p6085, 24p
Publication Year :
2024

Abstract

Background: Integrating diverse sensor technologies into smart insoles offers significant potential for monitoring biomechanical metrics; enhancing sports performance; and managing therapeutic interventions, diseases, disorders, and other health-related issues. The variation in sensor types and applications requires a systematic review to synthesize existing evidence and guide future innovations. Objectives: This review aims to identify, categorize, and critically evaluate the various sensors used in smart insoles, focusing on their technical specifications, application scopes, and validity. Methods: Following the PRISMA guidelines, a search was conducted in three major electronic databases, namely, PubMed, Scopus, and Web of Science, for relevant literature published from 2014 to 2024. Other works not located in the mentioned databases were added manually by parallel searches on related themes and suggestions from the website of the databases. To be eligible, studies were required to describe sensor implementation in insoles, specify the sensor types, and report on either validation experiments or practical outcomes. Results: The search identified 33 qualifying studies. Proper analysis revealed a dominance of pressure sensors, with accelerometers and gyroscopes also being widely used. Critical applications included gait analysis, posture correction, and real-time athletic and rehabilitation feedback. The review also examined the relative effectiveness of different sensor configurations. Conclusions: This systematic review comprehensively classifies sensor technologies within smart insoles and highlights their broad application potential across various fields. Future research should aim to standardize measurement protocols, enhance sensor integration, and advance data processing techniques to boost functionality and clinical applicability. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
14
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
178690571
Full Text :
https://doi.org/10.3390/app14146085