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

E-Health / Health Services Research and New Models of Care (517) Digital Health Reviews (1289) mHealth for Rehabilitation (263) Wearable Devices and Sensors (888) Portable and Mobile Technologies for Rehabilitation (151) Stroke (163)

Published on in Vol 22, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15981, first published .
Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

Authors of this article:

Jack Parker1 Author Orcid Image ;   Lauren Powell1 Author Orcid Image ;   Susan Mawson1 Author Orcid Image
Article Authors Cited by (33) Tweetations (19) Metrics

Journals

  1. Hall N, Parker D, Williams A. An exploratory qualitative study of health professional perspectives on clinical outcomes in UK orthotic practice. Journal of Foot and Ankle Research 2020;13(1) View
  2. Melendez-Calderon A, Shirota C, Balasubramanian S. Estimating Movement Smoothness From Inertial Measurement Units. Frontiers in Bioengineering and Biotechnology 2021;8 View
  3. Forsyth J, Chase H, Roberts N, Armitage L, Farmer A. Application of the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies in Assessing Mobile-Delivered Technologies for the Self-Management of Type 2 Diabetes Mellitus: Scoping Review. JMIR Diabetes 2021;6(1):e23687 View
  4. Baumgartner C, Baumgartner J, Pirker-Kees A, Rumpl E. Wearables in der Schlaganfallmedizin. Klinische Neurophysiologie 2021;52(01):10 View
  5. Peters D, O’Brien E, Kamrud K, Roberts S, Rooney T, Thibodeau K, Balakrishnan S, Gell N, Mohapatra S. Utilization of wearable technology to assess gait and mobility post-stroke: a systematic review. Journal of NeuroEngineering and Rehabilitation 2021;18(1) View
  6. Bardus M, Borgi C, El-Harakeh M, Gherbal T, Kharroubi S, Fares E. Exploring the Use of Mobile and Wearable Technology among University Student Athletes in Lebanon: A Cross-Sectional Study. Sensors 2021;21(13):4472 View
  7. Morrow C, Johnson E, Simpson K, Seo N. Determining Factors that Influence Adoption of New Post-Stroke Sensorimotor Rehabilitation Devices in the USA. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2021;29:1213 View
  8. David A, ReethaJanetSureka S, Gayathri S, Annamalai S, Samuelkamleshkumar S, Kuruvilla A, Magimairaj H, Varadhan S, Balasubramanian S. Quantification of the relative arm use in patients with hemiparesis using inertial measurement units. Journal of Rehabilitation and Assistive Technologies Engineering 2021;8 View
  9. Selamat S, Che Me R, Ahmad Ainuddin H, Salim M, Ramli H, Romli M. The Application of Technological Intervention for Stroke Rehabilitation in Southeast Asia: A Scoping Review With Stakeholders' Consultation. Frontiers in Public Health 2022;9 View
  10. Li Q, Liu Y, Zhu J, Chen Z, Liu L, Yang S, Zhu G, Zhu B, Li J, Jin R, Tao J, Chen L. Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation. JMIR mHealth and uHealth 2021;9(9):e24402 View
  11. Hernandez A, Bubyr L, Archambault P, Higgins J, Levin M, Kairy D. Virtual Reality–Based Rehabilitation as a Feasible and Engaging Tool for the Management of Chronic Poststroke Upper-Extremity Function Recovery: Randomized Controlled Trial. JMIR Serious Games 2022;10(3):e37506 View
  12. Pregnolato G, Rimini D, Baldan F, Maistrello L, Salvalaggio S, Celadon N, Ariano P, Pirri C, Turolla A. Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study. International Journal of Environmental Research and Public Health 2023;20(6):5082 View
  13. Toh S, Fong K, Gonzalez P, Tang Y. Application of Home-Based Wearable Technologies in Physical Rehabilitation for Stroke: A Scoping Review. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023;31:1614 View
  14. Martino Cinnera A, Picerno P, Bisirri A, Koch G, Morone G, Vannozzi G. Upper limb assessment with inertial measurement units according to the international classification of functioning in stroke: a systematic review and correlation meta-analysis. Topics in Stroke Rehabilitation 2024;31(1):66 View
  15. Moulaei K, Bahaadinbeigy K, Haghdoostd A, Nezhad M, Sheikhtaheri A. Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review. Archives of Public Health 2023;81(1) View
  16. Langerak A, Regterschot G, Evers M, van Beijnum B, Meskers C, Selles R, Ribbers G, Bussmann J. A Sensor-Based Feedback Device Stimulating Daily Life Upper Extremity Activity in Stroke Patients: A Feasibility Study. Sensors 2023;23(13):5868 View
  17. Hwang Y, Tung Y, Chen C, Lin B. B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023;31:4008 View
  18. Rivera B, Nurse C, Shah V, Roldan C, Jumbo A, Faysel M, Levine S, Kaufman D, Afable A. Do digital health interventions hold promise for stroke prevention and care in Black and Latinx populations in the United States? A scoping review. BMC Public Health 2023;23(1) View
  19. Salaorni F, Bonardi G, Schena F, Tinazzi M, Gandolfi M. Wearable devices for gait and posture monitoring via telemedicine in people with movement disorders and multiple sclerosis: a systematic review. Expert Review of Medical Devices 2024;21(1-2):121 View
  20. Toh F, Lam W, Gonzalez P, Fong K. ‘Smart reminder’: A feasibility pilot study on the effects of a wearable device treatment on the hemiplegic upper limb in persons with stroke. Journal of Telemedicine and Telecare 2024 View
  21. Paterson S, Dawes H, Winward C, Bartram E, Dodds E, McKinon J, Gaskell H, Collett J. Use of the Capability, Opportunity and Motivation Behaviour model (COM-B) to Understand Interventions to Support Physical Activity Behaviour in People with Stroke: An Overview of Reviews. Clinical Rehabilitation 2024;38(4):543 View
  22. Broderick M, Burridge J, Demain S, Johnson L, Brereton J, O'Shea R, Bentley P. Multicentre pilot randomised control trial of a self-directed exergaming intervention for poststroke upper limb rehabilitation: research protocol. BMJ Open 2024;14(1):e077121 View
  23. Lee E, Tan W, Pham B, Kawaja A, Theng Y. Addressing Data Absenteeism and Technology Chauvinism in the Use of Gamified Wearable Gloves Among Older Adults: Moderated Usability Study. JMIR Serious Games 2024;12:e47600 View
  24. Sharma B, Phan P, Davies J, Hoang T, Nguyen C, Ji A, Zhu K, Nicotra E, Lovell N, Do T. Soft Upper‐Limb Wearable Robotic Devices: Technology and Applications. Advanced Intelligent Systems 2024 View
  25. Toh F, Lam W, Cruz Gonzalez P, Fong K. Effects of a Wearable-Based Intervention on the Hemiparetic Upper Limb in Persons With Stroke: A Randomized Controlled Trial. Neurorehabilitation and Neural Repair 2024 View
  26. Song Q, Qin Q, Suen L, Liang G, Qin H, Zhang L. Effects of wearable device training on upper limb motor function in patients with stroke: a systematic review and meta-analysis. Journal of International Medical Research 2024;52(10) View
  27. Nascimento A, Custódio B, Soares A, Noveletto F, Eichinger F. SIRTET. Revista de Estudos Interdisciplinares 2024;6(4):01 View
  28. Sánchez-Gil J, Sáez-Manzano A, López-Luque R, Ochoa-Sepúlveda J, Cañete-Carmona E. Gamified devices for stroke rehabilitation: A systematic review. Computer Methods and Programs in Biomedicine 2025;258:108476 View

Books/Policy Documents

  1. Klamroth-Marganska V, Giovanoli S, Easthope C, Schönhammer J. Neurorehabilitation Technology. View
  2. Choukou M, (Katie) Zhu X, Malwade S, Dhar E, Abdul S. Healthcare Information Management Systems. View