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This paper is in the following e-collection/theme issue:

Wearables and MHealth Reviews (680) Ubiquitous Health (uHealth) (269) mHealth for Data Collection and Research (1719) mHealth in a Clinical Setting (1135) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (2367) Wearable Devices and Sensors (1576) Portable and Mobile Technologies for Rehabilitation (282) Fitness Trackers and Smart Pedometers/Accelerometers (790)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76084, first published .
Person checking smart watch for fitness tracking and notifications

Advancements in Wearable Sensor Technologies for Health Monitoring in Terms of Clinical Applications, Rehabilitation, and Disease Risk Assessment: Systematic Review

Advancements in Wearable Sensor Technologies for Health Monitoring in Terms of Clinical Applications, Rehabilitation, and Disease Risk Assessment: Systematic Review

Authors of this article:

Bonsang Gu1 Author Orcid Image ;   Hyeon Su Kim1, 2 Author Orcid Image ;   HyunBin Kim2 Author Orcid Image ;   Jun-Il Yoo3 Author Orcid Image
Article Authors Cited by (23) Tweetations Metrics

Journals

  1. Mehmood S, Manzoor F, Ali Z. <b>Role of Wearable Devices in Monitoring Rehabilitation Outcomes in Physiotherapy Patients</b>. Healer Journal of Biomedical and Health Sciences 2026;2(1):1 View
  2. Bai T, Jiang K, Yu Y, Qie S, Wang C, Wang B, Zhang W. A Review of Research on the Applications of Large Models in Each Functional Module of the Entire Rehabilitation Process. Future Internet 2026;18(2):95 View
  3. Cejudo A, Arrojo M, Martín C, Almeida A. AI and Wearables for Early Detection of Cognitive Impairment and Dementia: Systematic Review. Journal of Medical Internet Research 2026;28:e86262 View
  4. Greco G, Petrelli A, Poli L, Fischetti F, Cataldi S. Machine Learning in Adapted Physical Activity: Clinical Applications, Monitoring, and Implementation Pathways for Personalized Exercise in Chronic Conditions: A Narrative Review. Journal of Functional Morphology and Kinesiology 2026;11(1):106 View
  5. Duan S, Wang Z, Chen X, Ni G. Digital Health Technology Use Among Rehabilitation Professionals in China: Multi-Province Cross-Sectional Survey. Journal of Medical Internet Research 2026;28:e90623 View
  6. Srivastava K, Srivastava R. Explainable deep learning approaches and clinical insights for cancer biomarker identification. Frontiers in Oncology 2026;16 View
  7. Mangalam M, Fabianiak J. The movement imperative: reimagining healthcare through the lens of human movement. Frontiers in Sports and Active Living 2026;8 View
  8. Mahraoui S, Serpelloni M. Wireless Instrumented Ankle Foot Orthosis (AFO) for Gait Cycle Monitoring. Instruments 2026;10(2):23 View
  9. Drugă C, Baniță M, Pantea I, Ciorășteanu R, Repanovici A. Single-Sensor Postural Stability Assessment: Validation and Applications. Applied Sciences 2026;16(10):5029 View
  10. Pană C, Maican C, Vrăjitoru N, Pătrașcu-Pană D, Rădulescu V. From Signals to Remaining Useful Life: Multimodal Sensor Fusion for Fault Diagnosis and Prognostics—Methods, Pitfalls, and Reporting Standards. Sensors 2026;26(12):3661 View
  11. Alonazi M, Abro I, Abdelhaq M, Alsaqour R, Jalal A, Liu H. Attention-Based Multimodal Framework for Athlete-Performance Analysis and Rehabilitation Monitoring Using Vision and Wearable Sensors. Bioengineering 2026;13(7):718 View
  12. Ortega-Robles E, Treviño M, Manjarrez E, Arias-Carrión O. Walking as a Window to the Brain: Redefining Gait in Neurology. Medical Sciences 2026;14(3):338 View
  13. Ferreira J, Freitas M, Gaspar S, Pinho F, Fonseca H, Silva C. Nonlinear Measures Applied to Spontaneous Infant Movement Analysis: A Scoping Review. Sensors 2026;26(13):4267 View
  14. Chinebu T, Okafor K, Uzoeto H, Ifenze O, Nwigwe J, Chidiebere D, Okafor I, Onwusuru I, Okafor W, Apeh O. AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries. Technologies 2026;14(7):406 View
  15. Sagandykova N, Baurzhan M, Gulyayev A, Kairgeldina S, Sergazy S, Daniyarova G, Absattarova K, Kovalenko L, Izbassarova A. Emerging Digital Technologies for Monitoring and Rehabilitation Support in Chronic Dust-Induced Lung Diseases: A Scoping Review. Journal of Personalized Medicine 2026;16(8):407 View
  16. Xie B, Ren R, Zhang Y, Wang X, Zhen J. Utility of Tablet-Based Eye Tracking for Early Screening of Poststroke Cognitive Impairment: Diagnostic Cohort Study. JMIR mHealth and uHealth 2026;14:e83194 View
  17. Sodeify R, Seyednazari M, Dorosti A, Nourazarian A. Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review. Journal of Materials Science: Materials in Medicine 2026;37(1) View
  18. Song W, Liu X, Yu T, Xiang Y, Fu P, Wu M, Yin X, Zhang X, Chen Z. Early identification of vascular cognitive impairment from a multimodal perspective: a combined diagnosis from targeted cognitive assessments, imaging biomarkers, and molecular fluid biomarkers to ecological behavioral characteristics. Alzheimer's & Dementia 2026;22(8) View
  19. Dutta S, Mulchandani A. Carbon Nanotube-Based Biosensors for Non-Invasive Biofluid Analysis. Biosensors 2026;16(8):431 View
  20. Sun Y, Day S, Walters K, Schrag A, Saleem S. Clinical Validity of Wrist‐ and Trunk‐Worn Sensor‐Derived Data Models in Parkinson’s Disease. Parkinson's Disease 2026;2026(1) View
  21. Riaz H, Haibo J. Technology assisted gait rehabilitation for lower limb recovery: A narrative review of clinical, wearable and community based approaches. Journal of Bodywork and Movement Therapies 2026;48:1084 View

Conference Proceedings

  1. Kouser H, Sri B, Bharat S, Sona D. 2026 International Conference on Next Generation Electronics (NELEX). Gait Guard: Speed and Applied Load Measurement Monitoring Wearable Sock System View
  2. Said S, Youssef K, Eleyan A, Alkork S, Nait-Ali A. 2026 7th International Conference on Bio-engineering for Smart Technologies (BioSMART). A Deep Learning Framework for User Identification Using 8-Channel sEMG Biometrics View