Low Cost Device for ”At Home” Rehabilitation After a Stroke Event

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The paper proposes a design solution for a low cost device with feedback for upper extremity rehabilitation after a stroke event. Cerebral vascular accident (CVA) or stroke is one of the leading causes of morbidity and mortality worldwide. CVA is the most important cause of long-term disability in Europe, and demographic changes have led to an increase in both incidence and prevalence of this. Most secondary stroke disability is recovered in a few months, but others may persist for life. The rehabilitation should be started as soon as there is a greater chance of recovery in this early stage. Disabilities get worse and remain permanent over time, which is why is recommended the establishment of a rehabilitation program as soon as possible. Today, the use of virtual reality environments allow patients to perform tasks that mimic real life in rehabilitation clinics, but it tends increasingly more in the future these tasks can be done at home, sending data and receiving feedback from doctors. The devices presented in this paper are not only mechanical devices that allow the movement on a certain direction with predetermined effort degree for the patient, possibly controlled by the force of the muscle activity (EMG), but are innovative devices with the possibility to record a full set of biomedical signals. The patient device can record one or more biomedical parameters such as electrocardiography (ECG), heart rate (HR), electromyography (EMG), non-invasive blood pressure (NIBP), oxygen concentration in the blood (SpO2), movement speed and acceleration, angle of motion of a body extremity, torsion, s.a. according to the physician’s prescription and the patient needs. This means that the patient device will be very flexible and can communicate with other medical devices for home use

[1] Chen, J, Nichols, D, Brokaw, EB, Lum, PS, 2017. Home-Based Therapy After Stroke Using the Hand Spring Operated Movement Enhancer (HandSOME) IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(12), Pag. 2305-2312, DOI: 10.1109/TNSRE.2017.2695379

[2] Kwakkel, G., 2006. Impact of intensity of practice after stroke: issues for consideration. Disability and Rehabilitation, 28(13-14), Pag. 823-830, DOI: 10.1080/09638280500534861

[3] Cabana, F, Page, C, Svotelis, A, Langlois-Michaud, S, Tousignant, M, 2016. Is an inhome telerehabilitation program for people with proximal humerus fracture as effective as a conventional face-to face rehabilitation program? A study protocol for a noninferiority randomized clinical trial. BMC SPORTS SCIENCE MEDICINE AND REHABILITATION, 8, DOI: 10.1186/s13102-016-0051-z

[4] Plow, M, Golding, M, 2017, Using mHealth Technology in a Self-Management Intervention to Promote Physical Activity Among Adults With Chronic Disabling Conditions: Randomized Controlled Trial JMIR mHealth and uHealth, 5(12), DOI: 10.2196/mhealth.6394

[5] Schultheis M.T., Rizzo A.A., 2001. The application of virtual reality technology in rehabilitation. Rehabil Psychol, 46(3), Pag.296-311.

[6] Sveistrup, H., 2004. Motor rehabilitation using virtual reality. Journal of NeuroEngineering and Rehabilitation 1(10), doi:

[7] Pollock, A, St George, B, Fenton, M, Firkins, L., 2012. Top ten research priorities relating to life after stroke. Lancet Neurology, 11(3), Pag. 209, doi:

[8] Hunter, S.M., Johansen-Berg, H., Ward, N., Kennedy, N.C., Chandler, E., Weir, C.J., Rothwell, J., Wing, A.M., Grey, M.J., Barton, G., Leavey, N.M., Havis, C., Lemon, R.N., Burridge, J., Dymond, A., Pomeroy, V.M., 2018. Functional Strength Training and Movement Performance Therapy for Upper Limb Recovery Early Poststroke- Efficacy, Neural Correlates, Predictive Markers, and Cost-Effectiveness: FASTINdiCATE Trial. FRONTIERS IN NEUROLOGY, 8, DOI: 10.3389/fneur.2017.00733

[9] Held, JPO, Luft, AR, Veerbeek, JM, 2018. Encouragement-induced real-World upper limb use after Stroke by a tracking and Feedback device: a Study Protocol for a Multi- Center, assessor-Blinded, randomized Controlled trial. FRONTIERS INNEUROLOGY, 9, DOI: 10.3389/fneur.2018.00013

[10] Ciorap, R., Arotariţei, D., Topoliceanu, F., Lupu, R., Corciovă, C, Ungureanu, M., 2005. E-health application for home monitoring of neuro-muscular rehabilitation [Aplicaţie e-Health pentru monitorizarea la domiciliu a recuperării neuro-musculare]. Revista Medico-Chirurgicală a Societății de Medici și Naturaliști din Iași,109(2), Pag.440-444

[11] Wittmann, F, Held, JP, Lambercy, O, Starkey, ML, Curt, A, Hover, R, Gassert, R, Luft, AR, Gonzenbach, RR, 2016. Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system. Journal of Neuroengineering and Rehabilitation, 13, DOI: 10.1186/s12984-016-0182-1

[12] Muri, F, Carbajal, C, Echenique, AM, Fernandez, H, Lopez, NM, 2013. Virtual reality upper limb model controlled by EMG signals, Journal of Physics Conference Series,477, 19TH Argentinean Bioengineering Society Congress (SABI 2013), doi:

[13] Meyer AJ, Patten C, Fregly BJ (2017) Lower extremity EMG-driven modeling of walking with automated adjustment of musculoskeletal geometry. PLOS ONE 12(7), DOI: 10.1371/journal.pone.0179698

[14] Ciorap, R., Arotăriţei, D., Corciova, C., 2006. Multi-objective optimization for fuzzy controller in neuro-muscular rehabilitation [Optimizare multiobiectiv a controlerelor fuzzy şi neuro-fuzzy în aplicaţii e-Health de recuperare neuro-musculară]. Revista Medico-Chirurgicală a Societății de Medici și Naturaliști din Iași, 110(2), p.409-416

[15] Jonsdottir, J, Thorsen, R, Aprile, I, Galeri, S, Spannocchi, G, Beghi, E, Bianchi, E, Montesano, A, Ferrarin, M, 2017. Arm rehabilitation in post stroke subjects: A randomized controlled trial on the efficacy of myoelectrically driven FES applied in a task-oriented approach. PLOS ONE, 12(12), DOI: 10.1371/journal.pone.0188642

[16] Simonetti, D, Zollo, L, Vollero, L, Iannello, G, Guglielmelli, E, 2016. A modular telerehabilitation architecture for upper limb robotic therapy. Advances in Mechanical Engineering, 9(2), DOI: 10.1177/1687814016687252

[17] Mancisidor, A, Zubizarreta, A, Cabanes, I, Bengoa, P, Jung, JH, 2018. Kinematical and dynamical modeling of a multipurpose upper limbs rehabilitation robot. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 49, pag. 374-387, DOI: 10.1016/j.rcim.2017.08.013

[18] Ciorap, R., Andritoi, D., Pomazan, V., Petcu, L., Ungureanu, F., Zaharia, D., 2009. Ehealth system for monitoring of chronic diseases. World Congress on Medical Physics and Biomedical Engineering, Munich; Germany; 7 - 12 September 2009, IFMBE Proceedings, 25 (5), Pag. 259-262, DOI: 10.1007/978-3-642-03904-1-72

[19] Ciorap R., Hritcu-Luca C., Corciova C., Stan A., Zaharia D., 2009. Home Monitoring Device for Cardiovascular Diseases. International Conference on Advancements of Medicine and Health Care through Technology, Cluj-Napoca, Romania 23-26 Septembrie 2009, Pag.49-52; DOI: 10.1007/978-3-642-04292-8_11

[20] Ciorap R.; Corciova C.; Ciorap M.; Zaharia D., 2011. Optimization of the Treatment for Chronic Disease Using an e-Health System. 7th International Symposium on ADVANCED TOPICS IN ELECTRICAL ENGINEERING 2011, Bucureşti, 12-14 Mai 2011, Pag.143-146

[21] Ciorap R., Andrițoi D., Crăciun I., Analysis of physiological parameters during soldier’s combat training, The 12th International Scientific Conference “DEFENSE RESOURCES MANAGEMENT IN THE 21st CENTURY” Braşov, 9-10 November 2017.

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