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The article is devoted to assessing the possibility of identifying individual characteristics of a person’s gait according to the data of one accelerometric sensor, as well as the possibility of assessing impaired functioning of the musculoskeletal system with subsequent use in intelligent expert systems based on neural network algorithms. The article notes the prospects of using dynamic measurements to improve the effectiveness of orthopedic diagnostics. The prospects of using accelerometry along with complex medical motion capture systems are noted. The results of distinguishing characteristic gait indicators among a group of subjects according to one accelerometer sensor, as well as an assessment of the distribution structure of the articular angle when walking, are described. As subjects, people with impaired functioning of the musculoskeletal system and people without disorders are involved. The results obtained are in good agreement with the data of goniometric control systems built on the basis of several sensors. Thus, the results of the research show the possibility of obtaining a detailed picture of gait. The results obtained will allow us to form a preliminary structure of the neural network and evaluate its coefficients with the further development of automated control and monitoring systems based on existing portable wearable devices (phone, watch).

The assessment of gait features according to the data of a portable acceleration sensor in an intelligent monitoring system