A Systematic Review of Insole Sensor Technology: Recent Studies and Future Directions
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Non-Invasive Vital Sign Monitoring · Muscle activation and electromyography studies · Context-Aware Activity Recognition Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
University of Coimbra, Centre for Mechanical Engineering, Materials and Processes (CEMMPRE-ARISE), Department of Mechanical Engineering, 3040-248 Coimbra, Portugal
University of Coimbra, Research Unit for Sport and Physical Activity (CIDAF), Faculty of Sport Sciences and Physical Education, 3040-248 Coimbra, Portugal
Funding
FCT—Fundação para a Ciência e a Tecnologia
References (34)
Show source-provided references
1. Intelligent Wearable Systems: Opportunities and Challenges in Health and Sports
2. McDevitt, S., Hernandez, H., Hicks, J., Lowell, R., Bentahaikt, H., Burch, R., Ball, J., Chander, H., Freeman, C., and Taylor, C. (2022). Wearables for Biomechanical Performance Optimization and Risk Assessment in Industrial and Sports Applications. Bioengineering, 9.10.3390/bioengineering9010033 ↗
3. Smart insoles review (2008-2021): Applications, potentials, and future10.1016/j.smhl.2022.100301 ↗
4. Amaro, C.M., Castro, M.A., Roseiro, L., Neto, M.A., and Amaro, A.M. (2020). Plantar Pressure Evaluation during the Season in Five Basketball Movements. Appl. Sci., 10.10.3390/app10238691 ↗
5. Plantar Pressure-Based Insole Gait Monitoring Techniques for Diseases Monitoring and Analysis: A Review10.1002/admt.202100566 ↗
6. Validation of Moticon’s OpenGo sensor insoles during gait, jumps, balance and cross-country skiing specific imitation movements10.1080/02640414.2016.1161205 ↗
7. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews10.1136/bmj.n71 ↗
8. Tibial bone forces can be monitored using shoe-worn wearable sensors during running10.1080/02640414.2022.2107816 ↗
9. Parati, M., Gallotta, M., Muletti, M., Pirola, A., Bellafà, A., De Maria, B., and Ferrante, S. (2022). Validation of Pressure-Sensing Insoles in Patients with Parkinson’s Disease during Overground Walking in Single and Cognitive Dual-Task Conditions. Sensors, 22.10.3390/s22176392 ↗
10. Chatzaki, C., Skaramagkas, V., Tachos, N., Christodoulakis, G., Maniadi, E., Kefalopoulou, Z., Fotiadis, D.I., and Tsiknakis, M. (2021). The Smart-Insole Dataset Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients. Sensors, 21.10.3390/s21082821 ↗
11. Foot angular kinematics measured with inertial measurement units: A reliable criterion for real-time gait event detection10.1016/j.jbiomech.2021.110880 ↗
12. Estimation of hike events and temporal parameters with body-attached sensors10.1007/s12283-023-00411-x ↗
13. Analysis of dual-task elderly gait in fallers and non-fallers using wearable sensors10.1016/j.jbiomech.2016.01.015 ↗
14. Tan, Y., Ivanov, K., Mei, Z., Li, H., Li, H., Lubich, L., Wang, C., and Wang, L. (2021). A Soft Wearable and Fully-Textile Piezoresistive Sensor for Plantar Pressure Capturing. Micromachines, 12.10.3390/mi12020110 ↗
15. Thi Thu Vu, H., Dong, D., Cao, H.-L., Verstraten, T., Lefeber, D., Vanderborght, B., and Geeroms, J. (2020). A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses. Sensors, 20.10.3390/s20143972 ↗
16. A Review in Detection and Monitoring Gait Disorders Using In-Shoe Plantar Measurement Systems10.1109/RBME.2017.2747402 ↗
17. Real-Time Human Foot Motion Localization Algorithm With Dynamic Speed10.1109/THMS.2016.2586741 ↗
18. Seçkin, A.Ç., Ateş, B., and Seçkin, M. (2023). Review on Wearable Technology in Sports: Concepts, Challenges and Opportunities. Appl. Sci., 13.10.3390/app131810399 ↗
19. A Conductive Bamboo Fabric with Controllable Resistance for Tailoring Wearable Sensors10.1021/acsami.2c04192 ↗
20. A new 3D, microfluidic-oriented, multi-functional, and highly stretchable soft wearable sensor10.1038/s41598-022-25048-x ↗
21. A Shoe-Integrated Sensor System for Long-Term Center of Pressure Evaluation10.1109/JSEN.2021.3116249 ↗
22. Baniasad, M., Martin, R., Crevoisier, X., Pichonnaz, C., Becce, F., and Aminian, K. (2023). Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait. Sensors, 23.10.3390/s23073587 ↗
23. Ho, J.G., Kim, Y., and Min, S.D. (2022). Customized Textile Capacitive Insole Sensor for Center of Pressure Analysis. Sensors, 22.10.3390/s22239390 ↗
24. Estimation of ground reaction forces and ankle moment with multiple, low-cost sensors10.1186/s12984-015-0081-x ↗
25. Evaluation of Hemiplegic Gait Based on Plantar Pressure and Inertial Sensors10.1109/JSEN.2023.3268669 ↗
26. Kinematic Analysis of Human Gait Based on Wearable Sensor System for Gait Rehabilitation10.1007/s40846-016-0179-z ↗
27. Open Set User Identification Using Gait Pattern Analysis Based on Ensemble Deep Neural Network10.1109/JSEN.2022.3188527 ↗
28. Prospective Fall-Risk Prediction Models for Older Adults Based on Wearable Sensors10.1109/TNSRE.2017.2687100 ↗
29. Smart Insole: A Wearable Sensor Device for Unobtrusive Gait Monitoring in Daily Life10.1109/TII.2016.2585643 ↗
30. Smartstep: A fully integrated, low-power insole monitor10.3390/electronics3020381 ↗
31. Textile-film sensors for a comfortable intelligent pressure-sensing insole10.1016/j.measurement.2021.109943 ↗
32. Wearable Sensor System for Detecting Gait Parameters of Abnormal Gaits: A Feasibility Study10.1109/JSEN.2018.2814994 ↗
33. Prasanth, H., Caban, M., Keller, U., Courtine, G., Ijspeert, A., Vallery, H., and von Zitzewitz, J. (2021). Wearable Sensor-Based Real-Time Gait Detection A Systematic Review. Sensors, 21.10.3390/s21082727 ↗
34. González, I., Fontecha, J., Hervás, R., and Bravo, J. (2015). An ambulatory system for gait monitoring based on wireless sensorized insoles. Sensors, 15.10.3390/s150716589 ↗