# Novel Methods of AI-Based Gait Analysis in Post-Stroke Patients
## 1 Introduction  
Gait is the primary means of human movement. Despite the apparent simplicity of the matter, there are many definitions of gait, as walking is one of the most complex activities performed by humans. It is also one of the most frequently performed activities, occupying on average 10% of an individual's time each day.Gait is such an important activity in people's daily lives that any deficit in it can seriously reduce their subjective health-related quality of life. Research on the assessment of gait function is therefore important not only in terms of the patient's mobility, but also in terms of the patient's future quality of life, ability to achieve health-related goals, family life, and study and/or work [1]. In addition, clinical studies have confirmed the relationship between various medical conditions and a patient's gait characteristics [2].  
The normal human gait is stereotyped--this means that the range of possible deviations from the global gait pattern is so narrow that both the normal gait pattern and the acceptable range of deviations from it can be established for the whole population. Furthermore, on the basis of the values of deviations from the global gait pattern, it is possible to make inferences about health and disease (pathological changes in gait pattern caused by disease or injury) in a given patient [3, 4].  
This also means that gait, despite differences among individuals, is characterized by a certain degree of repeatability and can be described in terms of norms (depending on many factors, such as length of lower limbs, age, state of health, etc.). Deviations from these norms, in turn, provide information on abnormalities, providing an opportunity for the appropriate choice of therapy. Thus, gait diagnosis can be performed on both healthy people (to ensure they are within normal limits) and people with a wide range of gait deficits. For the aforementioned reasons, the search is on for low-cost, accurate, and fast ways to analyze gait, not only for clinical purposes, but also, for example, to optimize the movements of athletes. It is imperative that gait-testing methods are selected in such a way as to ensure, among other things, ease and rapidity of testing and low cost while maintaining testing sensitivity [5; 6].  
The analysis of gait function in healthy individuals, the assessment of gait pattern pathology, and the targeted restoration (re-education) of gait function in patients with functional deficits places high demands on specialists. This is aided by the use of gait measures that are low-cost, quick and simple to use, accurate, reliable, reproducible, and independent of the patient and the therapist. These measures must be usable in everyday clinical practice in neurological, post-stroke, and rehabilitation wards, and in outpatient practice in rehabilitation.A good diagnostic is already able to perceive changes in a patient's gait during observation and use these changes to make clinical inferences. However, such a model of clinical gait assessment requires experience and is difficult to transfer to another person and to standardize. Hence, the optimization of gait diagnosis is essential [7; 8].