Abstract
This paper describes research into the development of a collaborative home-based patient-therapist system for stroke patient rehabilitation. Our prototype system is designed so that home-based rehabilitation exercises are interactive and adapt to the progress of the patient. This way patients are encouraged to do the exercises most appropriate for their stage in the recovery process and can make the most of the time spent working on their rehabilitation. The system also keeps a record of patient progress that is communicated to the patient and medical professionals via mobile or personal-computer interfaces so they can work together towards a more effective overall plan for rehabilitation. This allows the physician to be better informed to make clinical decisions based on the progress of the patient. Results of early evaluations demonstrate the utility of our prototype system to provide users with a stimulating interactive experience as well as the systems potential to support medical experts to make more informed decisions relating to patient treatment. Results also indicate that patients feel more involved in their rehabilitation and that general communication between the medical experts and patients is improved.
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References
Adamson, J., Beswick, A., Ebrahim, S.: Is stroke the most common cause of disability? J. Stroke Cerebrovasc. Dis. 13(4), 171–177 (2004)
Bai, J., Song, A.: Development of a novel home based multi-scene upper limb rehabilitation training and evaluation system for post-stroke patients. IEEE Access 7, 9667–9677 (2019)
Caimmi, M., Malosio, M., Pedrocchi, N., Vicentini, F., Tosatti, L.M., Molteni, F., et al.: Upper limb robotic rehabilitation: Treatment customization. Gait Posture 37, S13–S14 (2013)
Colombo, R., et al.: Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE Trans. Neural Syst. Rehabil. Eng. 13(3), 311–324 (2005)
De Capua, C., Meduri, A., Morello, R.: A smart ECG measurement system based on web-service-oriented architecture for telemedicine applications. IEEE Trans. Instrum. Meas. 59(10), 2530–2538 (2010)
Escudero, D.A., Marqués, L.A., Taboada, F.C.: Up-date in spontaneous cerebral hemorrhage. Med. Intensiva 32(6), 282–295 (2008)
Estrin, D., Sim, I.: Open mHealth architecture: an engine for health care innovation. Science 330(6005), 759–760 (2010)
Fugl-Meyer, A.R., Jääskö, L., Leyman, I., Olsson, S., Steglind, S.: The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand. J. Rehabil. Med. 7(1), 13–31 (1975)
Gladstone, D.J., Danells, C.J., Black, S.E.: The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabilitation Neural Repair 16(3), 232–240 (2002)
Hecimovich, M.D., Volet, S.E.: Importance of building confidence in patient communication and clinical skills among chiropractic students. J. Chiropractic Educ. 23(2), 151–164 (2009)
Huygelier, H., Schraepen, B., van Ee, R., Abeele, V.V., Gillebert, C.R.: Acceptance of immersive head-mounted virtual reality in older adults. Sci. Rep. 9(1), 4519 (2019)
Kang, Y.J., et al.: Development and clinical trial of virtual reality-based cognitive assessment in people with stroke: preliminary study. CyberPsychology Behav. 11(3), 329–339 (2008)
Party, I.S.W., et al.: National Clinical Guideline for Stroke, vol. 20083. Citeseer, Princeton (2012)
Prevention, S.: Guidelines for medical treatment for stroke prevention. Ann. Intern. Med. 121, 54–55 (1994)
Ruiz-Zafra, A., Noguera, M., Benghazi, K., Ochoa, S.F.: A cloud collaborative approach for managing patients wellness. In: 2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 637–642. IEEE (2015)
Saunders, D.H., Greig, C.A., Mead, G.E.: Physical activity and exercise after stroke: review of multiple meaningful benefits. Stroke 45(12), 3742–3747 (2014)
Suzman, R., Beard, J.: Global health and aging. NIH Publ. 1(4), 273–277 (2011)
Thrasher, T.A., Zivanovic, V., McIlroy, W., Popovic, M.R.: Rehabilitation of reaching and grasping function in severe hemiplegic patients using functional electrical stimulation therapy. Neurorehabilitation Neural Repair 22(6), 706–714 (2008)
Wu, J.: How WeChat, the most popular social network in china, cultivates wellbeing (2014)
Acknowledgments
The authors are thankful for the support provided by the therapists and patients in the branch of rehabilitation in Suzhou BenQ Medical Center and the First Affiliated Hospital of Soochow University for participating in the user testing stage and evaluation of this project. This work is supported by XJTLU Key Program Special Fund KSF-E-10 and Research Development Fund RDF-14-03-22.
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Craig, P., Jin, Y., Sun, J. (2020). A Home-Based Adaptive Collaborative System for Stroke Patient Rehabilitation. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2020. Lecture Notes in Computer Science(), vol 12341. Springer, Cham. https://doi.org/10.1007/978-3-030-60816-3_1
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DOI: https://doi.org/10.1007/978-3-030-60816-3_1
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