Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19582, first published .
In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study

In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study

In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study

Journals

  1. Bhattacharjya S, Cavuoto L, Reilly B, Xu W, Subryan H, Langan J. Usability, Usefulness, and Acceptance of a Novel, Portable Rehabilitation System (mRehab) Using Smartphone and 3D Printing Technology: Mixed Methods Study. JMIR Human Factors 2021;8(1):e21312 View
  2. Sun X, Xu K, Shi Y, Li H, Li R, Yang S, Jin H, Feng C, Li B, Xing C, Qu Y, Wang Q, Chen Y, Yang T, Si W. Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering. Evidence-Based Complementary and Alternative Medicine 2021;2021:1 View
  3. Burns S, Terblanche M, Perea J, Lillard H, DeLaPena C, Grinage N, MacKinen A, Cox E. mHealth Intervention Applications for Adults Living With the Effects of Stroke: A Scoping Review. Archives of Rehabilitation Research and Clinical Translation 2021;3(1):100095 View
  4. Christopoulou S. Impacts on Context Aware Systems in Evidence-Based Health Informatics: A Review. Healthcare 2022;10(4):685 View
  5. Aphiphaksakul P, Siriphorn A, Pinzon R. Home-based exercise using balance disc and smartphone inclinometer application improves balance and activity of daily living in individuals with stroke: A randomized controlled trial. PLOS ONE 2022;17(11):e0277870 View
  6. Bhattacharjya S, Linares I, Langan J, Xu W, Subryan H, Cavuoto L. Engaging in a home-based exercise program: a mixed-methods approach to identify motivators and barriers for individuals with stroke. Assistive Technology 2023;35(6):487 View
  7. Ding J, Yang Y, Wu X, Xiao B, Ma L, Xu Y. The telehealth program of occupational therapy among older people: an up-to-date scoping review. Aging Clinical and Experimental Research 2022;35(1):23 View
  8. Bo W, Cavuoto L, Langan J, Subryan H, Bhattacharjya S, Huang M, Xu W. A progressive prediction model towards home-based stroke rehabilitation programs. Smart Health 2022;23:100239 View
  9. Blum S, Hölle D, Bleichner M, Debener S. Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer. Sensors 2021;21(23):8135 View
  10. Triantafyllidis A, Segkouli S, Zygouris S, Michailidou C, Avgerinakis K, Fappa E, Vassiliades S, Bougea A, Papagiannakis N, Katakis I, Mathioudis E, Sorici A, Bajenaru L, Tageo V, Camonita F, Magga-Nteve C, Vrochidis S, Pedullà L, Brichetto G, Tsakanikas P, Votis K, Tzovaras D. Mobile App Interventions for Parkinson’s Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review. Sensors 2023;23(7):3396 View
  11. Gebreheat G, Goman A, Porter-Armstrong A. The use of home-based digital technology to support post-stroke upper limb rehabilitation: A scoping review. Clinical Rehabilitation 2024;38(1):60 View
  12. Gooch H, Jarvis K, Stockley R. Behavior Change Approaches in Digital Technology–Based Physical Rehabilitation Interventions Following Stroke: Scoping Review. Journal of Medical Internet Research 2024;26:e48725 View
  13. Kondo K, Kim S, Noguchi N, Akiyama R, Murata W, Lee B. Learning program enhances rehabilitation professionals’ perceived ease of using 3d printing: a pilot randomized controlled trial. Disability and Rehabilitation: Assistive Technology 2024:1 View