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Longitudinal Evaluation of Hemiplegic Ankle Rehabilitation Efficacy by Wearable Inertial Sensor Systems with an Assortment of Machine Learning Algorithms

DOI: 10.4236/jbise.2023.169009, PP. 121-131

Keywords: Smartphone, Gyroscope, Machine Learning, Hemiparesis, Rehabilitation, Ankle, Longitudinal Evaluation

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Abstract:

With the amalgamation of wearable systems equipped with inertial sensors, such as a gyroscope, and machine learning a therapy regimen can be objectively quantified, and then the initial phase and final phase of a one year therapy regimen can be distinguished through machine learning. In the context of rehabilitation of a hemiplegic ankle, a longitudinal therapy regimen incorporating stretching and then a series of repetitions for raising and lowering the foot of the hemiplegic ankle can be applied over the course of a year. Using a smartphone equipped with an application to function as a wearable and wireless gyroscope platform mounted to the dorsum of the foot by an armband, the initial phase and final phase of a one year longitudinally applied therapy regimen can be objectively quantified and recorded for subsequent machine learning. Considerable classification accuracy is attained to distinguish between the initial phase and final phase by a support vector machine for a one year longitudinally applied hemiplegic ankle therapy regimen based on the gyroscope signal data obtained by a smartphone functioning as a wearable and wireless inertial sensor system.

References

[1]  LeMoyne, R. and Mastroianni, T. (2018) Wearable and Wireless Systems for Healthcare I. Gait and Reflex Response Quantification. Springer, Singapore. https://doi.org/10.1007/978-981-10-5684-0_1
[2]  LeMoyne, R. and Mastroianni, T. (2017) Smartphone and Portable Media Device: A Novel Pathway toward the Diagnostic Characterization of Human Movement. In: Mohamudally, N., Ed., Smartphones from an Applied Research Perspective, InTech, Rijeka, 1-24. https://doi.org/10.5772/intechopen.69961
[3]  LeMoyne, R. and Mastroianni, T. (2018) Homebound Therapy with Wearable and Wireless Systems. In: LeMoyne, R. and Mastroianni, T., Eds., Wearable and Wireless Systems for Healthcare I, Springer, Singapore, 121-132. https://doi.org/10.1007/978-981-10-5684-0_10
[4]  LeMoyne, R. and Mastroianni, T. (2021) Machine Learning Classification of Diadochokinesia for a Hemiplegic Ankle Foot Complex Pair. Proceedings of the 9th International Conference on e-Health and Bioengineering (EHB), Iasi, 18-19 November 2021, 1-4. https://doi.org/10.1109/EHB52898.2021.9657587
[5]  LeMoyne, R. and Mastroianni, T. (2021) Application of a Multilayer Perceptron Neural Network for Differentiation of the Influence of Ankle Stretch Duration for Hemiplegic Affected Ankle Dorsiflexion Quantified by a Smartphone Functioning as a Wearable and Wireless Gyroscope Platform. Proceedings of the 9th International Conference on e-Health and Bioengineering (EHB), Iasi, 18-19 November 2021, 1-4.
https://doi.org/10.1109/EHB52898.2021.9657696
[6]  LeMoyne, R. and Mastroianni, T. (2021) Machine Learning Classification of Hemiplegic Dorsiflexion Based on Knee Orientation. Proceedings of the 9th International Conference on e-Health and Bioengineering (EHB), Iasi, 18-19 November 2021, 1-4. https://doi.org/10.1109/EHB52898.2021.9657565
[7]  LeMoyne, R. and Mastroianni, T. (2021) Conformal Wearable for Quantification of Dorsiflexion for a Hemiplegic Ankle Pair with Distinction by Machine Learning. Proceedings of the 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, 13-16 December 2021, 1307-1310.
https://doi.org/10.1109/ICMLA52953.2021.00212
[8]  Dobkin, B.H. (2003) The Clinical Science of Neurologic Rehabilitation. Oxford University Press, New York.
https://doi.org/10.1093/oso/9780195150643.001.0001
[9]  LeMoyne, R. (2016) Ankle-Foot Complex and the Fundamental Aspects of Gait. In: LeMoyne, R., Ed., Advances for Prosthetic Technology, Springer, Tokyo, 15-27. https://doi.org/10.1007/978-4-431-55816-3_2
[10]  Kandel, E.R., Schwartz, J.H. and Jessell, T.M. (2000) Principles of Neural Science. McGraw-Hill, New York.
[11]  Brashear, A. and Elovic, E. (2016) Spasticity: Diagnosis and Management. Demos Medical Publishing, New York. https://doi.org/10.1891/9781617052422
[12]  Dietz, V. (2002) Proprioception and Locomotor Disorders. Nature Reviews Neuroscience, 3, 781-790.
https://doi.org/10.1038/nrn939
[13]  LeMoyne, R., Coroian, C., Mastroianni, T. and Grundfest, W. (2008) Virtual Proprioception. Journal of Mechanics in Medicine and Biology, 8, 317-338. https://doi.org/10.1142/S0219519408002693
[14]  Ng, S.S. and Hui-Chan, C.W. (2012) Contribution of Ankle Dorsiflexor Strength to Walking Endurance in People with Spastic Hemiplegia after Stroke. Archives of Physical Medicine and Rehabilitation, 93, 1046-1051.
https://doi.org/10.1016/j.apmr.2011.12.016
[15]  Ng, S.S. and Hui-Chan, C.W. (2013) Ankle Dorsiflexion, Not Plantarflexion Strength, Predicts the Functional Mobility of People with Spastic Hemiplegia. Journal of Rehabilitation Medicine, 45, 541-545.
https://doi.org/10.2340/16501977-1154
[16]  Etnyre, B.R. and Abraham, L.D. (1986) Gains in Range of Ankle Dorsiflexion Using Three Popular Stretching Techniques. American Journal of Physical Medicine & Rehabilitation, 65, 189-196.
[17]  Vinti, M., Couillandre, A., Hausselle, J., Bayle, N., Primerano, A., Merlo, A., Hutin, E. and Gracies, J.M. (2013) Influence of Effort Intensity and Gastrocnemius Stretch on Co-Contraction and Torque Production in the Healthy and Paretic Ankle. Clinical Neurophysiology, 124, 528-535. https://doi.org/10.1016/j.clinph.2012.08.010
[18]  Vecchio, M., Gracies, J.M., Panza, F., Fortunato, F., Vitaliti, G., Malaguarnera, G., Cinone, N., Beatrice, R., Ranieri, M. and Santamato, A. (2017) Change in Coefficient of Fatigability Following Rapid, Repetitive Movement Training in Post-Stroke Spastic Paresis: A Prospective Open-Label Observational Study. Journal of Stroke and Cerebrovascular Diseases, 26, 2536-2540. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.05.046
[19]  Baumbach, S.F., Brumann, M., Binder, J., Mutschler, W., Regauer, M. and Polzer, H. (2014) The Influence of Knee Position on Ankle Dorsiflexion—A Biometric Study. BMC Musculoskeletal Disorders, 15, Article No. 246.
https://doi.org/10.1186/1471-2474-15-246
[20]  LeMoyne, R., Mastroianni, T., Hessel, A. and Nishikawa, K. (2015) Ankle Rehabilitation System with Feedback from a Smartphone Wireless Gyroscope Platform and Machine Learning Classification. Proceedings of the 14th International Conference on Machine Learning and Applications (ICMLA), Miami, 9-11 December 2015, 406-409. https://doi.org/10.1109/ICMLA.2015.213
[21]  LeMoyne, R. and Mastroianni, T. (2016) Implementation of a Smartphone as a Wireless Gyroscope Platform for Quantifying Reduced Arm Swing in Hemiplegic Gait with Machine Learning Classification by Multilayer Perceptron Neural Network. Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, 16-20 August 2016, 2626-2630.
https://doi.org/10.1109/EMBC.2016.7591269
[22]  Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P. and Witten, I.H. (2009) The WEKA Data Mining Software: An Update. ACM SIGKDD Explorations Newsletter, 11, 10-18.
https://doi.org/10.1145/1656274.1656278
[23]  Witten, I.H., Frank, E. and Hall, M.A. (2011) Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, Burlington.
[24]  WEKA. http://www.cs.waikato.ac.nz/~ml/weka/
[25]  LeCun, Y., Bengio, Y. and Hinton, G. (2015) Deep Learning. Nature, 521, 436-444.
https://doi.org/10.1038/nature14539
[26]  LeMoyne, R., Mastroianni, T., Whiting, D. and Tomycz, N. (2020) Application of Deep Learning to Distinguish Multiple Deep Brain Stimulation Parameter Configurations for the Treatment of Parkinson’s Disease. Proceedings of the 19th International Conference on Machine Learning and Applications (ICMLA), Miami, 14-17 December 2020, 1106-1111. https://doi.org/10.1109/ICMLA51294.2020.00178

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