Main Article Content

Abstract

Stroke and traumatic brain injury often lead to hand motor impairments that limit independence and quality of life.This study presents a portable, low-cost actuator system for the E‑Glove: a soft robotic glove designed to deliver continuous passive motion (CPM) for hand rehabilitation. The actuator design was envisioned to be capable of producing sufficient torque to overcome severe stiffness (resistive force ≥8 N), user-friendly control, and portability. The actuator module consists of two TowerPro MG996R servo motors controlled by an Arduino Nano, with capacitive touch sensors allowing three discrete speed settings (35.7, 45.5, and 50.0 degrees/s) and RGB LED feedback. Biomechanical analysis determined a lever arm of 0.07 m and calculated a maximum resistive torque of 12.28 N-m, resulting in a safety factor >1 for severe flexure. Prototype testing confirmed reliable operation at all speed levels and safe disengagement upon power‑off. The detachable actuator housing, powered via USB‑C, supports home‑based therapy and remote monitoring. This work addresses critical barriers to accessibility, promoting high‑frequency rehabilitation outside clinical settings.

Keywords

Sarung tangan rehabilitasi tangan gerakan pasif terus menerus aktuator servo terapi pasca stroke Soft robotic glove hand rehabilitation continuous passive motion servo actuator post‑stroke therapy

Article Details

How to Cite
Pasaribu, A. D. P., & Lestari, W. D. (2025). Design and Development of a Low-Cost Soft-Robotic Actuator System for Hand Rehabilitation: The E‑Glove Prototype. Jurnal Ilmiah Momentum, 21(1), 83–92. https://doi.org/10.36499/jim.v21i1.13835

References

  1. Abd Elhady, A. E. S., Ahmed, G. M., Hassan, A., Mohamed Ibrahim, S., & Mohamed Abdelmageed, S. (2025). Efficacy of robotic training gloves in improving hand function and movement in stroke patients. Sport TK, 14, 1–17. https://doi.org/10.6018/sportk.660321
  2. Bates, M., & Sunderam, S. (2023). Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review. Frontiers in Human Neuroscience, 17. https://doi.org/10.3389/fnhum.2023.1121481
  3. Chen, S., Li, Y., Shu, X., Wang, C., Wang, H., Ding, L., & Jia, J. (2020). Electroencephalography Mu Rhythm Changes and Decreased Spasticity After Repetitive Peripheral Magnetic Stimulation in Patients Following Stroke. Frontiers in Neurology, 11(September), 1–12. https://doi.org/10.3389/fneur.2020.546599
  4. Duruöz, M. T. (2019). Hand Function: A Practical Guide to Assessment, Second Edition. Hand Function: A Practical Guide to Assessment, Second Edition, March 2022, 1–357. https://doi.org/10.1007/978-3-030-17000-4
  5. Huang, L., Yi, L., Huang, H., Zhan, S., Chen, R., & Yue, Z. (2024). Corticospinal tract: a new hope for the treatment of post-stroke spasticity. Acta Neurologica Belgica, 124(1), 25–36. https://doi.org/10.1007/s13760-023-02377-w
  6. Hwang, D., Shin, J. H., & Kwon, S. (2021). Kinematic assessment to measure change in impairment during active and active-assisted type of robotic rehabilitation for patients with stroke. Sensors, 21(21). https://doi.org/10.3390/s21217055
  7. Kruse, A., Suica, Z., Taeymans, J., & Schuster-Amft, C. (2020). Effect of brain-computer interface training based on non-invasive electroencephalography using motor imagery on functional recovery after stroke - a systematic review and meta-analysis. BMC Neurology, 20(1), 1–14. https://doi.org/10.1186/s12883-020-01960-5
  8. Mansour, S., Ang, K. K., Nair, K. P. S., Phua, K. S., & Arvaneh, M. (2022). Efficacy of Brain–Computer Interface and the Impact of Its Design Characteristics on Poststroke Upper-limb Rehabilitation: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Clinical EEG and Neuroscience, 53(1), 79–90. https://doi.org/10.1177/15500594211009065
  9. Pan, B., Huang, Z., Jin, T., Wu, J., Zhang, Z., & Shen, Y. (2021). Motor function assessment of upper limb in stroke patients. Journal of Healthcare Engineering, 2021. https://doi.org/10.1155/2021/6621950
  10. Saeedi-Boroujeni, A., Purrahman, D., Shojaeian, A., Poniatowski, Ł. A., Rafiee, F., & Mahmoudian-Sani, M. R. (2023). Progranulin (PGRN) as a regulator of inflammation and a critical factor in the immunopathogenesis of cardiovascular diseases. Journal of Inflammation (United Kingdom), 20(1), 1–14. https://doi.org/10.1186/s12950-023-00327-0
  11. Stefano, A. (2023). The Fascinating Functional Anatomy of the Human Hand. 07, 2–3. https://doi.org/10.37421/2684-4265.2023.7.275
  12. Wang, T., Liu, Z., Gu, J., Tan, J., & Hu, T. (2023). Effectiveness of soft robotic glove versus repetitive transcranial magnetic stimulation in post-stroke patients with severe upper limb dysfunction: A randomised controlled trial. Frontiers in Neurology, 13. https://doi.org/10.3389/fneur.2022.887205
  13. Wu, J., Cheng, H., Zhang, J., Yang, S., & Cai, S. (2021). Robot-Assisted Therapy for Upper Extremity Motor Impairment after Stroke: A Systematic Review and Meta-Analysis. Physical Therapy, 101(4), 1–13. https://doi.org/10.1093/ptj/pzab010
  14. Yasuda, H., Ueda, M., Ueno, K., Naito, Y., Ishii, R., & Takebayashi, T. (2025). Enhancing mu-ERD through combined robotic assistance and motor imagery: a novel approach for upper limb rehabilitation. Frontiers in Human Neuroscience, 19(June), 1–8. https://doi.org/10.3389/fnhum.2025.1571386
  15. Yurkewich, A., Kozak, I. J., Ivanovic, A., Rossos, D., Wang, R. H., Hebert, D., & Mihailidis, A. (2020). Myoelectric untethered robotic glove enhances hand function and performance on daily living tasks after stroke. Journal of Rehabilitation and Assistive Technologies Engineering, 7. https://doi.org/10.1177/2055668320964050