A smart and home-based telerehabilitation tool for patients with neuromuscular disorder

Conference paper

Manna, S., Azhar, H., Smith, D. and Islam, T. 2022. A smart and home-based telerehabilitation tool for patients with neuromuscular disorder.

Publication process dates
Authors	Manna, S., Azhar, H., Smith, D. and Islam, T.
Type	Conference paper
Description	More than fourteen million people suffer from neuromuscular diseases, including strokes, spinal cord injuries, Parkinson's disease, etc. To return to normal life sooner, a rigorous rehabilitation process is needed. In hospitals, physiotherapists and neurological experts prescribe specific neurorehabilitation exercises. In most cases, patients need to schedule an appointment to receive treatment in a hospital or to have physiotherapists visit them at home. The number of neuromuscular patients has increased, resulting in longer hospital waiting times. In particular, during COVID-19, patients were not allowed to visit hospitals or have physiotherapists visit them due to government restrictions. Online guides for personalised and custom rehabilitation therapy for joint spasticity and stiffness are also not available. This paper reports the development of an IoT-based prototype system that monitors and records joint movements using sensory footwear (consisting of FSR and IMU sensors) and Kinect sensors. In addition, a prototype web portal is also being developed to record performance data during exercises at home and interact with clinicians remotely. A pilot study has been conducted with six healthy individuals and test results show that there is a strong correlation between Kinect data and FSR data in terms of coordination between joint movements.
Keywords	Telerehabilitation; Neuromuscular patient; Wearable sensors; Kinect sensor; Correlation coefficient
Year	2022
Conference	7th IEEE-EMBS Conference on Biomedical Engineering and Sciences
Official URL	https://iecbes.org/index.php
References	[1] M. Lloyd, “Over 10,000 people waiting over a year for neurological services, Neurological Alliance analysis reveals,” The Neurological Alliance, Jul. 12, 2021. https://www.neural.org.uk/news/over-10000-people-waiting-over-a-year... (accessed Oct. 07, 2022). [2] A. Patel, V. Berdunov, Z. Quayyum, D. King, M. Knapp and R. Wittenberg, "Estimated societal costs of stroke in the UK based on a discrete event simulation", Age and Ageing, vol. 49, no. 2, pp. 270-276, 2019. Available: 10.1093/ageing/afz162. [3] G. Iacobucci, "Swedish company launches NHS partnership in bid to enter GP app market", BMJ, p. k4596, 2018. Available: 10.1136/bmj.k4596.. [4] S. Armstrong, "The apps attempting to transfer NHS 111 online", BMJ, p. k156, 2018. Available: 10.1136/bmj.k156.. [5] W. Tao, T. Liu, R. Zheng and H. Feng, "Gait Analysis Using Wearable Sensors", Sensors, vol. 12, no. 2, pp. 2255-2283, 2012. Available: 10.3390/s120202255. [6] C. Tan, "Is remote rehabilitation after stroke as effective as conventional therapy?", Neurology, vol. 95, no. 17, pp. e2462-e2464, 2020. Available: 10.1212/wnl.0000000000010839. [7] H. Sarsak, "Telerehabilitation services: a successful paradigm for occupational therapy clinical services?", International Physical Medicine & Rehabilitation Journal, vol. 5, no. 2, 2020. Available: 10.15406/ipmrj.2020.05.00237. [8] D. Anton, I. Berges, J. Bermúdez, A. Goñi and A. Illarramendi, "A Telerehabilitation System for the Selection, Evaluation and Remote Management of Therapies", Sensors, vol. 18, no. 5, p. 1459, 2018. Available: 10.3390/s18051459. [9] G. Fortino, and R. Gravina, “A cloud-assisted wearable system for physical rehabilitation”. In ICTs for Improving Patients Rehabilitation Research Techniques, Springer, Berlin, Heidelberg, pp. 168-182, 2014. [10] lady ada, “Force Sensitive Resistor (FSR),” Adafruit Learning System, Jul. 29, 2012. https://learn.adafruit.com/force
Deposited	17 Oct 2022

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