Abstract
In this paper we propose solution of the problem of clinical gait analysis in post-stroke patients using advanced artificial intelligence approaches: fuzzy logic, neural networks, and fractal dimension. We focus on the stroke influence on gait pattern and features due to stroke is regarded one of the major causes of disability, including gait disorders. No doubt gait may be described by many parameters but it still needs advanced computational approach. Statistical analysis and simulation of gait features allow for relatively early detection of many limitations, selection of the proper therapeutic method, and assessment of the therapy progress. Results presented here are promising despite our approach needs for further studies toward clinical application.
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References
Awad, L.N., Reisman, D.S., Wright, T.R., Roos, M.A., Binder-Macleod, S.A.: Maximum walking speed is a key determinant of long distance walking function after stroke. Top. Stroke Rehabil. 21(6), 502–509 (2014). https://doi.org/10.1310/tsr2106-502
Ayis, S., Wellwood, I., Rudd, A.G., McKevitt, C., Parkin, D., Wolfe, C.D.A.: Variations in health-related quality of life (HRQoL) and survival 1 year after stroke: five European population-based registers. BMJ Open 5(6) (2015). https://doi.org/10.1136/bmjopen-2014-007101
Bhatnagar, P., Scarborough, P., Smeeton, N.C., Allender, S.: The incidence of all stroke and stroke subtype in the United Kingdom, 1985 to 2008: a systematic review. BMC Public Health 10(1), 539 (2010). https://doi.org/10.1186/1471-2458-10-539
Gray, J., Lie, M.L.S., Murtagh, M.J., Ford, G.A., McMeekin, P., Thomson, R.G.: Health state descriptions to elicit stroke values: do they reflect patient experience of stroke? BMC Health Serv. Res. 14(1), 573 (2014). https://doi.org/10.1186/s12913-014-0573-6
Heuschmann, P., Wiedmann, S., Wellwood, I., Rudd, A., Di Carlo, A., Bejot, Y., Ryglewicz, D., Rastenyte, D., Wolfe, C.: Three-month stroke outcome. Neurology 76(2), 159–165 (2011). https://doi.org/10.1212/WNL.0b013e318206ca1e
Klimkiewicz, P., Kubsik, A., Woldańska-Okońska, M.: NDT-Bobath method used in the rehabilitation of patients with a history of ischemic stroke. Wiad. Lek. 65(2), 102–107 (2012)
Lozano-Ortiz, C.A., Muniz, A.M.S., Nadal, J.: Human gait classification after lower limb fracture using artificial neural networks and principal component analysis. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, pp. 1413–1416, August 2010
Mikołajewska, E.: Associations between results of post-stroke NDT-Bobath rehabilitation in gait parameters, ADL and hand functions. Adv. Clin. Exp. Med. 22(5), 731–738 (2013)
Mikołajewska, E.: The value of the NDT-Bobath method in post-stroke gait training. Adv. Clin. Exp. Med. 22(2), 261–272 (2013)
Mikołajewska, E., Prokopowicz, P., Mikolajewski, D.: Computational gait analysis using fuzzy logic for everyday clinical purposes – preliminary findings. Bio-Algorithms Med-Syst. 13(1) (2017). https://doi.org/10.1515/bams-2016-0023
Muniz, A., Nadal, J.: Application of principal component analysis in vertical ground reaction force to discriminate normal and abnormal gait. Gait Posture 29(1), 31–35 (2009). https://doi.org/10.1016/j.gaitpost.2008.05.015
Prokopowicz, P., Mikołajewska, E., Mikołajewski, D., Kotlarz, P.: Analysis of temporospatial gait parameters, pp. 289–302. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59614-3_17
Prokopowicz, P., Mikołajewski, D., Mikołajewska, E., Kotlarz, P.: Fuzzy system as an assessment tool for analysis of the health-related quality of life for the people after stroke. In: Rutkowski, L., et al. (ed.) Artificial Intelligence and Soft Computing, pp. 710–721. Springer, Cham (2017)
Prokopowicz, P., Mikołajewski, D., Mikołajewska, E., Tyburek, K.: Modeling trends in the hierarchical fuzzy system for multi-criteria evaluation of medical data. In: Kacprzyk, L., et al. (ed.) Advances in Fuzzy Logic and Technology 2017, pp. 207–219. Springer, Cham (2018)
Richards, C.L., Malouin, F., Dean, C.: Gait in stroke: assessment and rehabilitation. Clin. Geriatr. Med. 15(4), 833–855 (1999)
Roelker, S.A., Bowden, M.G., Kautz, S.A., Neptune, R.R.: Paretic propulsion as a measure of walking performance and functional motor recovery post-stroke: a review. Gait Posture 68, 6–14 (2019). https://doi.org/10.1016/j.gaitpost.2018.10.027
Sheffler, L.R., Chae, J.: Hemiparetic gait. Phys. Med. Rehabil. Clin. N. Am. 26(4), 611–623 (2015). Stroke Rehabilitation
Thrift, A.G., Howard, G., Cadilhac, D.A., Howard, V.J., Rothwell, P.M., Thayabaranathan, T., Feigin, V.L., Norrving, B., Donnan, G.A.: Global stroke statistics: an update of mortality data from countries using a broad code of cerebrovascular diseases. Int. J. Stroke 12(8), 796–801 (2017)
Thrift, A.G., Thayabaranathan, T., Howard, G., Howard, V.J., Rothwell, P.M., Feigin, V.L., Norrving, B., Donnan, G.A., Cadilhac, D.A.: Global stroke statistics. Int. J. Stroke 12(1), 13–32 (2017). https://doi.org/10.1177/1747493016676285
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Piotr, P., Dariusz, M., Krzysztof, T., Emilia, M., Piotr, K. (2020). AI-Based Analysis of Selected Gait Parameters in Post-stroke Patients. In: Choraś, M., Choraś, R. (eds) Image Processing and Communications. IP&C 2019. Advances in Intelligent Systems and Computing, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-31254-1_24
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