Accuracy and repeatability study of an elbow exoskeleton for multistage exercises

Book chapter


Manna, Soumya K 2022. Accuracy and repeatability study of an elbow exoskeleton for multistage exercises. in: 2022 20th International Conference on Mechatronics - Mechatronika (ME) IEEE.
AuthorsManna, Soumya K
Abstract

The need for post-stroke rehabilitation is paramount especially with the increasing number of stroke survivors worldwide. It appears that patients must receive multistage therapy consisting of specific exercises to improve their neuro-motor function. Modern-day advancement in biomedical technology has transformed the exoskeleton into a potential tool for post-stroke rehabilitation. Several exoskeletons have been developed for providing post-stroke exercises, however, their actions are influenced by several inhibiting factors such as abnormal sensor data, continuous usage of power source, safety from anatomical range etc. Besides their working principle is limited to providing a specific type of exercise. To overcome the current limitations of the existing systems for providing multistage exercises in post-stroke rehabilitation, a novel elbow exoskeleton has been developed where joint movements are supported by an electric motor or springs in different stages. The innovative mechanism incorporates the benefits of an electric motor and springs; the electric motor is used to maintain external force-controlled joint movement during the acute stage whereas joint motion is partially assisted or resisted by spring force in the recovery stage hence minimizing the energy consumption from motors. A pilot experiment has been conducted among healthy participants to measure the joint parameters and to analyze the accuracy and repeatability of the measurements by the exoskeleton. The measured joint parameters from the exoskeleton have been also compared with the Kinect motion analysis system where the measurement error in joint angle is around 1% to 6%. The correlation coefficient between consecutive joint measurements is higher than 0.99 proving the high repeatability of measurement.

KeywordsPost-stroke rehabilitation; Elbow exoskeleton; Multistage exercises; Repeatability; Accuracy; Correlation coefficient
Year2022
Book title2022 20th International Conference on Mechatronics - Mechatronika (ME)
PublisherIEEE
Output statusPublished
ISBN9781665410403
9781665410397
9781665410410
Publication dates
Online07 Dec 2022
Publication process dates
Deposited17 Oct 2022
Digital Object Identifier (DOI)https://doi.org/10.1109/me54704.2022.9983396
Official URLhttps://ieeexplore.ieee.org/abstract/document/9983396
References

[1] Stroke Association of UK (2018), “State of the nation Stroke statistics 2018” [online at] https://www.stroke.org.uk/sites/default/files/ state_of_the_nation_2018.pdf.
[2] H. Lo and S. Xie, "Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects", Medical Engineering & Physics, vol. 34, no. 3, pp. 261-268, 2012. Available: 10.1016/j.medengphy.2011.10.004.
[3] 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, Feb. 2020, doi: 10.1093/ageing/afz162.
[4] D. Saha, "Effects of Robot Assisted Therapy as an Adjunct to Conventional Therapy in Upper Limb Motor Recovery after Stroke", Journal of Medical Science And clinical Research, pp. 13978-13986, 2016. Available: 10.18535/jmscr/v4i11.78.
[5] B. Dobkin, "Strategies for stroke rehabilitation", The Lancet Neurology, vol. 3, no. 9, pp. 528-536, 2004. Available: 10.1016/s1474-4422(04)00851-8.
[6] S. Manna and V. Dubey, "A Portable Elbow Exoskeleton for Three Stages of Rehabilitation", Journal of Mechanisms and Robotics, vol. 11, no. 6, 2019. Available: 10.1115/1.4044535.
[7] T. Proietti, V. Crocher, A. Roby-Brami and N. Jarrasse, "Upper-Limb Robotic Exoskeletons for Neurorehabilitation: A Review on Control Strategies", IEEE Reviews in Biomedical Engineering, vol. 9, pp. 4-14, 2016. Available: 10.1109/rbme.2016.2552201.
[8] L. Peternel, T. Noda, T. Petrič, A. Ude, J. Morimoto and J. Babič, "Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation", PLOS ONE, vol. 11, no. 2, p. e0148942, 2016. Available: 10.1371/journal.pone.0148942.
[9] D. Reinkensmeyer and M. Boninger, "Technologies and combination therapies for enhancing movement training for people with a disability", Journal of NeuroEngineering and Rehabilitation, vol. 9, no. 1, p. 17, 2012. Available: 10.1186/1743-0003-9-17.
[10] S. Manna and V. Dubey, "Comparative study of actuation systems for portable upper limb exoskeletons", Medical Engineering & Physics, vol. 60, pp. 1-13, 2018. Available: 10.1016/j.medengphy.2018.07.017.
[11] S. Roccella et al., "Design of a hand exoskeleton (handexos) for the rehabilitation of the hand", Gerontechnology, vol. 7, no. 2, 2008. Available: 10.4017/gt.2008.07.02.134.00.
[12] B. Hu, F. Zhang, H. Lu, H. Zou, J. Yang and H. Yu, "Design and Assist-as-Needed Control of Flexible Elbow Exoskeleton Actuated by Nonlinear Series Elastic Cable Driven Mechanism", Actuators, vol. 10, no. 11, p. 290, 2021. Available: 10.3390/act10110290.
[13] T. Shank, M. Eppes, J. Hossain, M. Gunn and T. Rahman, "Outcome Measures with COPM of Children using a Wilmington Robotic Exoskeleton", The Open Journal of Occupational Therapy, vol. 5, no. 1, 2017. Available: 10.15453/2168-6408.1262.
[14] R. Ham, T. Sugar, B. Vanderborght, K. Hollander and D. Lefeber, "Compliant actuator designs", IEEE Robotics & Automation Magazine, vol. 16, no. 3, pp. 81-94, 2009. Available: 10.1109/mra.2009.933629.
[15] G. Liu, F. Gao, D. Wang and W. Liao, "Medical applications of magnetorheological fluid: a systematic review", Smart Materials and Structures, vol. 31, no. 4, p. 043002, 2022. Available: 10.1088/1361-665x/ac54e7.
[16] B. Cesqui, P. Tropea, S. Micera and H. Krebs, "EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study", Journal of NeuroEngineering and Rehabilitation, vol. 10, no. 1, p. 75, 2013. Available: 10.1186/1743-0003-10-75.

Additional information

Publications router: Date 2022-12-07 of type 'publication_date' with format 'printed' included in notification
Publications router: Date 2022-12-07 of type 'ppub' included in notification
Publications router: Date 2022-12-07 of type 'issued' included in notification

Event20th Mechatronica 2022
Permalink -

https://repository.canterbury.ac.uk/item/92x3z/accuracy-and-repeatability-study-of-an-elbow-exoskeleton-for-multistage-exercises

  • 56
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Investigating security issues (multilayer attacks) on IoT devices using machine learning
Al Sukhni, B., Manna, S., Dave, J. and Zhang, L. 2024. Investigating security issues (multilayer attacks) on IoT devices using machine learning.
Safeguarding IoMT: Semi-automated Intrusion Detection System (SAIDS) for detecting multilayer attacks
Al Sukhni, B., Manna, S., Dave, J. and Zhang, L. 2024. Safeguarding IoMT: Semi-automated Intrusion Detection System (SAIDS) for detecting multilayer attacks.
Integration of graduate employability skills through industry outsourced CDIO project
Manna, S., Joyce, N. and Nortcliffe, A. 2023. Integration of graduate employability skills through industry outsourced CDIO project. in: Lyng, R., Bennedsen, J., Bettaied, L., Bodsberg, N. R., Edstrom, K., Guojonsdottir, M. S., Roslof, J., Solbjord, O. K. and Oien, G. (ed.) The 19th CDIO International Conference: Proceedings - Full Papers NTNU SEED. pp. 425-435
Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities
Manna, S., Azhar, H. and Greace, A. 2023. Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities. Heliyon. 9 (4), p. e15210. https://doi.org/10.1016/j.heliyon.2023.e15210
Machine learning-based solutions for securing IoT systems against multilayer attacks
Al Sukhni, B., Manna, S., Dave, J. and Zhang, L. 2022. Machine learning-based solutions for securing IoT systems against multilayer attacks. in: Singh Tomar, R., Verma, S., Kumar Chaurasia, B., Singh, V., Abawajy, J. H., Akashe, S., Hsiung, Pao-Ann and Prasad, R. (ed.) Communication, Networks and Computing Third International Conference, CNC 2022, Gwalior, India, December 8–10, 2022, Proceedings, Part I Cham Springer. pp. 140-153
Investigating the security issues of multi-layer IoT attacks using machine learning techniques
Al Sukhni, Badeea, Dave, Jugal M., Manna, Soumya K. and Zhang, Leishi 2022. Investigating the security issues of multi-layer IoT attacks using machine learning techniques. in: 2022 Human-Centered Cognitive Systems (HCCS) IEEE.
Investigating the security issues of multi-layer IoMT attacks using machine learning techniques
Al Sukhni, B., Manna, S., Dave, J. and Zhang, L. 2022. Investigating the security issues of multi-layer IoMT attacks using machine learning techniques.
A smart and home-based telerehabilitation tool for patients with neuromuscular disorder
Manna, Soumya K., Hannan, M. A., Azhar, B., Smith, D. and Islam, T. 2022. A smart and home-based telerehabilitation tool for patients with neuromuscular disorder. IEEE. https://doi.org/10.1109/iecbes54088.2022.10079410
Evaluation of students’ performance in CDIO projects through blended learning
Manna, S., Battikh, N., Nortcliffe, A. and Camm, J. 2022. Evaluation of students’ performance in CDIO projects through blended learning.
A smart and secure IoMT tele-neurorehabilitation framework for post-stroke patients
Manna, S., Azhar, H. and Sakel, M. 2022. A smart and secure IoMT tele-neurorehabilitation framework for post-stroke patients. in: Bhaumik, S., Chattopadhyay, S., Chattopadhyay, T. and Bhattacharya, S. (ed.) Proceedings of International Conference on Industrial Instrumentation and Control ICI2C 2021 Singapore Springer. pp. 11-20
Enhancing hands-on skills under capstone CDIO project using blended learning approach
Manna, S., Battikh, N. and Camm, J. 2021. Enhancing hands-on skills under capstone CDIO project using blended learning approach . Sheffield
An inclusive student-led online class test during the pandemic
Manna, S. and Azhar, H. 2021. An inclusive student-led online class test during the pandemic . Assessment and Feedback Symposium 2021.
Adaptive and flexible online learning during Covid19 lockdown
Manna, S., Nortcliffe, A., Sheikholeslami, G. and Richmond-Fuller, A. 2021. Adaptive and flexible online learning during Covid19 lockdown.
Developing engineering growth mindset through CDIO outreach activities
Manna, S., Nortcliffe, A. and Sheikholeslami, G. 2020. Developing engineering growth mindset through CDIO outreach activities. in: Proceedings of the 16th International CDIO Conference Gothenburg, Sweden CDIO.
Design of a game-based rehabilitation system using Kinect sensor
Manna, S. and Dubuy, V. N. 2019. Design of a game-based rehabilitation system using Kinect sensor. Minneapolis, MN, USA ASME.
Assessment of joint parameters in a Kinect sensor based rehabilitation game
Manna, S. and Dubey, V. N. 2019. Assessment of joint parameters in a Kinect sensor based rehabilitation game. Anaheim, California, USA ASME.
Rehabilitation strategy for post-stroke recovery using an innovative elbow exoskeleton
Manna, S. and Dubey, V. N. 2019. Rehabilitation strategy for post-stroke recovery using an innovative elbow exoskeleton. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. 233 (6), pp. 668-680. https://doi.org/10.1177/0954411919847058
A portable elbow exoskeleton for three stages of rehabilitation
Manna, S. and Dubey, V. N. 2019. A portable elbow exoskeleton for three stages of rehabilitation. Journal of Mechanisms and Robotics. 11 (6), p. 065002. https://doi.org/10.1115/1.4044535