Skip to main content
Log in

A low cost wearable wireless sensing system for paretic hand management after stroke

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

This paper describes the design of a low cost wearable hand exercise device that can assist repetitive wrist and finger exercise for stroke patients. The design of this device was guided by neurobiological principles of motor learning, such as sensory-motor integration, movement repetition, and cognitive interaction. This pilot study tested the efficacy of a wireless sensing system in the device to serve as a facilitator of repetitive hand exercise, which is an essential part of rehabilitation after stroke. The results from healthy young adults showed that the device with a wireless sensing system yielded quantitatively better motor function with the repetitive wrist and finger joint movements.This proof-of-concept study shows potential therapeutic evidence for stroke rehabilitation as well as the potential utility of sensing system for stroke rehabilitation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Towfighi A, Saver JL (2011) Stroke declines from third to fourth leading cause of death in the United States: historical perspective and challenge ahead. Stroke 42:2351–2355

    Article  Google Scholar 

  2. Gray CS, French JM, Bates D, Cartilidge NE, James OF, Venables G (1990) Motor recovery following acute stroke. Age Ageing 19:179–184

    Article  Google Scholar 

  3. Kamper DG, Fischer HC, Cruz EG, Rymer WZ (2006) Weakness is the primary contributor to finger impairment in chronic stroke. Arch Phys Med Rehab 87:1262–1269

    Article  Google Scholar 

  4. Denier Van Der Gon JJ, Ter Haar Romeny BM, Zuylen EJ (1985) Behaviour of motor units of human arm muscles: differences between slow isometric contraction and relaxation. J Physiol 359:107–118

    Article  Google Scholar 

  5. Kamper DG, Rymer WZ (2000) Quantitative features of the stretch response of extrinsic finger muscles in hemiparetic stroke. Muscle Nerve 23:954–961

    Article  Google Scholar 

  6. Kamper DG, Rymer WZ (2001) Impairment of voluntary control of finger motion following stroke: role of inappropriate muscle coactivation. Muscle Nerve 24:673–681

    Article  Google Scholar 

  7. Kamper DG, Harvey RL, Suresh S, Rymer WZ (2003) Relative contributions of neural mechanisms versus muscle mechanics in promoting finger extension deficits following stroke. Muscle Nerve 28:309–318

    Article  Google Scholar 

  8. Heo P, Gu GM, Lee SJ, Rhee K, Kim J (2012) Current hand exoskeleton technologies for rehabilitation and assistive engineering. Int J Precis Eng Manuf 13:807–824

    Article  Google Scholar 

  9. Schabowsky CN, Godfrey SB, Holley RJ, Lum PS (2010) Development and pilot testing of HEXORR: hand exoskeleton rehabilitation robot. J NeuroEng Rehab 7:36

    Article  Google Scholar 

  10. Benlamri R, Zhang X (2014) Context-aware recommender for mobile learners. Human-centric Comput Inf Sci 4:12

    Article  Google Scholar 

  11. Ng CK, Ee GK, Noordin NK (2013) Finger triggered virtual musical instruments. J Converg 4:39–46

    Google Scholar 

  12. Chagnaadorj O, Tanaka J (2014) Gesture input as an out-of-band channel. J Inf Process Syst 10:99–102

    Article  Google Scholar 

  13. Lee JK, Kang WM, Park JH, Kim JS (2014) GWD: Gesture-based wearable device for secure and effective information exchange on battlefield environment. J Converg 5:6–10

    Google Scholar 

  14. Silachan K, Tantatsanawong P (2014) Imputation of medical data using subspace condition order degree polynomials. J Inf Process Syst 10:395–411

    Article  Google Scholar 

  15. Sinha A, Lobiyal DK (2013) Performance evaluation of data aggregation for cluster-based wireless sensor network. Human-centric Comput Inf Sci 3:13

    Article  Google Scholar 

  16. Lee JD, Park JH, Sin CH (2014) PPS-RTBF: Privacy protection system for right to be forgotten. J Converg 5:37–40

    Article  Google Scholar 

  17. Zaidi SMA, Jung J, Song B (2014) Prioritized multipath video forwarding in WSN. J Inf Process Syst 10:176–192

    Article  Google Scholar 

  18. Feese S, Burscher MJ, Jonas K, Troster G (2014) Sensing spatial and temporal coordination in teams using the smartphone. Human-centric Comput Inf Sci 4:1

    Article  Google Scholar 

Download references

Acknowledgments

“This work was supported by the Soonchunhyang University Research Fund and the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (IITP-2015-H8601-15-1009) supervised by the NIPA (National IT Industry Promotion Agency)”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bong-Keun Jung.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Min, SD., Wang, CW., Lee, HM. et al. A low cost wearable wireless sensing system for paretic hand management after stroke. J Supercomput 74, 5231–5240 (2018). https://doi.org/10.1007/s11227-016-1787-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-016-1787-7

Keywords

Navigation