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

Wearables and MHealth Reviews (680) mHealth for Data Collection and Research (1720) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (2368) Dementia and Cognitive Decline (877) Wearable Devices and Sensors (1577) Cognitive and Neurorehabilitation (436) mHealth for Rehabilitation (562) Falls and Emergency Detection with Sensors and other Technologies (81) Artificial Intelligence (4744) Neurorehabilitation and Technology (54)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67265, first published .
Elderly woman with wearable health monitor and digital circuit background

Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review

Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review

Authors of this article:

Mirjam Bonanno1 Author Orcid Image ;   Augusto Ielo1 Author Orcid Image ;   Paolo De Pasquale1 Author Orcid Image ;   Antonio Celesti2 Author Orcid Image ;   Alessandro Marco De Nunzio3 Author Orcid Image ;   Angelo Quartarone1 Author Orcid Image ;   Rocco Salvatore Calabrò1 Author Orcid Image
Article Authors Cited by (24) Tweetations Metrics

Journals

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  5. Castelli L, Iacovelli C, Malizia A, Loreti C, Biscotti L, Caliandro P, Bentivoglio A, Calabresi P, Giovannini S. Assessment of Fall Risk in Neurological Disorders and Technology: Relationship Between Silver Index and Gait Analysis. Sensors 2026;26(3):840 View
  6. Devito F, Gattulli V, Impedovo D. Care-MOVE: A Smartphone-Based Application for Continuous Monitoring of Mobility, Environmental Exposure and Cognitive Status in Older Patients. Applied Sciences 2026;16(3):1549 View
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  8. Mayo N, Abou-Sharkh A, Dawes H, Donkers S, Gillis C, Goulding K, Hill E, Mate K, Tomita Y. Discriminating Between Fallers and Non-Fallers Using Kinematic Data from the Heel2Toe™ Wearable Sensor. Sensors 2026;26(5):1716 View
  9. Alqurashi A, Alharthi A, Alammar M, Aldosari N, Al Ayidh A. Classification of fallers and non-fallers in older adults using electrical IMU signal for gait analysis and explainable deep learning. Scientific Reports 2026;16(1) View
  10. N B, Pujari J, Bikku T, Joseph S, Thota S, Mishra P. From Motion to Prevention: A TimeGAN‐Enhanced Hybrid BiLSTM‐CNN‐Attention Model for Predicting Falls and Preventive Interventions. Applied Computational Intelligence and Soft Computing 2026;2026(1) View
  11. Argunsah H, Şirzai H, Gökhan Y, Yavuzer G, Holoğlu K. Phase-Specific Biomechanical Reorganization After Robotic Rehabilitation in Patients with Stroke: A Sensor-Derived Waveform Analysis. Life 2026;16(6):956 View
  12. Calderone A, Baricich A, Pournajaf S, Sottile F, Maggio M, Bonanno M, De Luca R, Ligato F, Quartarone A, Calabrò R. Muscle and mind: rewiring cognitive-motor recovery through exercise-responsive neurophysiology in neurological populations. Frontiers in Psychology 2026;17 View
  13. 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
  14. Benachour Y, Flitti F, Maloukh L, Far A, Boutellaa E, Bentoumi M, Rai M, Aburaed N, Ali K, Rehman M, Mosleh S, Dghaim R, Bouamama S. Machine Learning for Wearable Sensor-Based Human Movement Rehabilitation: A Five-Year Systematic Review. IEEE Access 2026;14:99280 View
  15. Mușat C, Iordan D, Onu I, Sardaru D, Neagu S, Tudor S, Tupu A. Artificial Intelligence, Wearable Sensors, and Mobile Applications in Postural Assessment and Rehabilitation. Balneo and PRM Research Journal 2026;17(Vol.17 No.2) View
  16. Al Shehri W. Decision-Critical Data Quality Contracts for IoT-Based Elderly Care: Symmetric vs. Asymmetric Enforcement for Fall and Health Deterioration Decisions. Symmetry 2026;18(7):1096 View
  17. Wang J, Li J, Xiao Q, Li J, Wang H, Liang X, Wu S, Wang Y, Cui M, Chen X, Suo C, Jiang Y. Olfactory dysfunction is associated with gait impairment in older adults: evidence for a shared amygdala substrate. GeroScience 2026 View
  18. Borty S, Rahman A, Ankolu G, Quddus S, Hasan M, Chakravarty S, Adewuyi M, Sakib N. SafeCircle: An iOS-based, AI-enabled, and privacy-aware remote monitoring system to detect fall and wandering among patients with AD/ADRD. SoftwareX 2026;35:102901 View
  19. Chen L, Guo R, Guo R, Chen Y, Wang Y, Zhang S, Zhang Q. IMU-based gait analysis methods: a systematic review of techniques for different body locations. Frontiers in Sports and Active Living 2026;8 View
  20. Graves J. Wearable Technologies for Remote Neurologic Health Monitoring. Continuum 2026;32(4):1239 View

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Conference Proceedings

  1. Sun Y, Wan H, Li X, Zhang F, Wu W, Zhang H. Proceedings of the 2026 10th International Conference on Artificial Intelligence, Automation and Control Technologies. Cross-Locomotion Task Generalization in sEMG-Based Gait Phase Prediction Using Artificial Neural Networks View
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