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Sokolova F.M., Tsareva A.V., Yakovleva O.A. Issues of evaluation in the adequacy of the gait rehabilitation among neurosurgical patients

DOI: 10.34835/issn.2308-1961.2020.9.p354-362
Issues of evaluation in the adequacy of the gait rehabilitation among neurosurgical patients
Fanida Menikhanovna Sokolova, the candidate of pedagogical sciences, senior lecturer, professor, doctor of rehabilitation, Lesgaft National State University of Physical Education, Sport and Health, St. Petersburg, training specialist and guideline developer, Polenov Neurosurgical Institute – branch of the Almazov National Medical Research Centre, Saint Petersburg; Anna Vyacheslavovna Tsareva, the assistant, St. Petersburg Electrotechnical University; Olga Andreevna Yakovleva, the teacher, Lesgaft National State University of Physical Education, Sport and Health, St. Petersburg
Introduction. The article covers the issues of evaluation among the patient the outcomes of neurorehabilitation, whereas the very fact of achieving the daily life autonomy does not guarantee that patient will be able to resume their normal lifestyle. Thus, it is crucial that the gait kinematics operational research and its biomechanical evaluation must be carried out regularly. The aim of the research is to define issues of the operational control over the gait rehabilitation in neurosurgical patients and to propose solutions of addressing them. The objectives of the study are: 1) to identify potential for refinement of adequacy estimation methods in gait rehabilitation among the neurosurgical patients; 2) to suggest ways of addressing the gait rapid assessment in hospital setting. Methodology and organization of the study: The theoretical analysis of the modern outcomes estimation methods in neurosurgical rehabilitation (drawing on the example of gait techniques) using scientific methodological literature has been carried out. The results of the study and the further discussion: this study focuses on the differences between the main modern estimation methods of gait efficiency. In particular, scaling ocular estimation methods mainly show activity performance and do not influence on the structure of move itself. The study reveals the information value of the every method and possibility of applying them in hospital setting; for instance, scales are applicable in these settings, however, they have no information value regarding the evaluation of the structure of move. Modern methods using different sensors or video capturing either demand special equipment, specific environment, and trained personnel or do not provide live data of the every parameter of interest. Conclusion: The issues of the gait rapid assessment in hospital setting have been revealed: time and space limits of one exercise/procedure do not allow installing the special equipment rapidly. Thus, the lasting duration of installation leads to the early patient’s exhaustion; the main disadvantage of the scaling modern estimation methods is stressing attention more on the fact of move performing than its structure which leads to the positive estimation of the move result performing even when this move is done as part of the pathological stereotype. The development and introduction of the pedagogical protocol of the gait kinematics monitoring and wireless personalized portable system usage have been suggested.
Keywords: physical rehabilitation, neurorehabilitation, neurosurgery, locomotor system impairments, gait rehabilitation, adequacy of gait rehabilitation, gait rehabilitation patient outcomes, gait rehabilitation evaluation, gait rehabilitation assessment, portable data measuring system, wireless system, assessment scale, rehabilitation measures assessment.
  1. Alekseev, V.V., Korolev, P.G. and Ivanova, N.E. (2017), “”The implementation of micro-mechanical sensors for control of the parameters of the kinematic portrait of the human”, Devices, No. 7, pp.6-15.
  2. Bakulev S.E., Kuznetsov A.O., Kuznetsov P.O., Pavlenko A.V., Simakov A.M., Taimazov V.A., Chistyakov V.A. (2020), A telemetry device to measure 3D kinematic characteristics of human movement including the anthropomorphic mechanism, Patent RF, No. 2019129370/14 (057861).
  3. Belova A.N. and Prokopenko A.S. (2010), Neurorehabilitation, T.M. Andreeva, Moscow.
  4. Evseev, S.P. (2018), “Physical rehabilitation in Adapted Physical Education”, Physical rehabilitation in sports, medicine and adaptive physical culture: materials of the IV All-Russian scientific-practical conference, St. Petersburg, pp.14-18.
  5. Evseeva O.E., Grachikov A.A., Evseev S.P. (2017), “On the Experience of Work on Individual Program of Rehabilitation and Habilitation of Disabled People and Children in the Field of Physical Culture and Sports”, Uchenye zapiski universiteta imeni P.F. Lesgafta, No. 7 (149), pp.66-74.
  6. Skvortsov, D.V. (2008), Biomechanical methods of rehabilitation in gait and balance disorders, dissertation, Moscow.
  7. Taimazov V.A., Bakulev S.E., Simakov A.M., Pavlenko A.V., Kuznetsov P.O., Kuznetsov A.O., Chistyakov V.A. (2018), “Innovative methods of direct measurement of all kinematic characteristics of the spatial movement of the boxer”, Uchenye zapiski universiteta imeni P.F. Lesgafta, No. 2 (156), pp. 237-243.
  8. Tsareva, A.V., Kurochkin, A.Yu. and Alekseev, V.V. (2019), “Information-measurement system for research of kinematics of movements of the lower limbs of the person and wireless data transfer”, Modeling, Optimization and Information Technology, No. 3 (26), available at:
  9. Azcueta, J.P.V., Libatique, N.C. and Tangonan, G.L. (2014), “In situ sports performance analysis system using inertial measurement units, high-fps video camera, and the Android platform”, In Proceedings of the 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control Environment and Management, pp. 12-16.
  10. Jung, P.G. Oh, S., Lim, G. and Kong K. (2014), A mobile motion capture system based on inertial sensors and smart shoes, Journal of Dynamic Systems, Measurement, and Control, pp. 136.
  11. Nukala, B. Shibuya, N., Rodriguez, A., Tsay, J., Nguyen, T., Zupancic, S. and Lie, D.Y. (2015), “Comparing nape vs. T4 placement for a mobile Wireless Gait Analysis sensor using the Dynamic Gait Index test”, Eighth International Conference on Mobile Computing and Ubiquitous Networking (ICMU), pp. 68-69.
  12. Shibuya, N. Nukala, B.T., Rodriguez, A.I., Tsay, J., Nguyen, T.Q., Zupancic, S. and Lie, D.Y (2015), “A real-time fall detection system using a wearable gait analysis sensor and a support vector machine (svm) classifier”, Mobile Computing and Ubiquitous Networking (ICMU), 2015 Eighth International Conference on. 2015. pp. 66–67.
  13. Sun, B. Liu, X., Wu, X. and Wang, H. (2014), “Human gait modeling and gait analysis based on Kinect”, Robotics and Automation (ICRA), IEEE International Conference, pp. 3173–3178.
  14. Wang B., Rajput, K.S., Tam, W.K., Tung, A.K. and Yang, Z. (2009), “Free Walker: A smart insole for longitudinal gait analysis”, Engineering in Medicine and Biology Society (EMBC), 37th Annual International Conference of the IEEE, pp. 3723–3726.
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Article arrived in edition 09.09.2020
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