Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. Recent technological and artificial intelligent advancements have equipped healthcare professionals with innovative tools, such as sensor systems and telemedicine equipment, offering groundbreaking opportunities to monitor and analyze patients' physical activity. This paper investigates the potential applications of mobile accelerometers in evaluating the symmetry of specific rehabilitation exercises using a dataset of 1280 tests on 16 individuals in the age range between 8 and 75 years. A comprehensive computational methodology is introduced, incorporating traditional digital signal processing, feature extraction in both time and transform domains, and advanced classification techniques. The study employs a range of machine learning methods, including support vector machines, Bayesian analysis, and neural networks, to evaluate the balance of various physical activities. The proposed approach achieved a high classification accuracy of 90.6% in distinguishing between left- and right-side motion patterns by employing features from both the time and frequency domains using a two-layer neural network. These findings demonstrate promising applications of precise monitoring of rehabilitation exercises to increase the probability of successful surgical recovery, highlighting the potential to significantly enhance patient care and treatment outcomes.

Centre for Security Information and Advanced Technologies Faculty of Applied Informatics Tomas Bata University in Zlín 760 01 Zlín Czech Republic

Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague 160 00 Prague 6 Czech Republic

Department of Mathematics Informatics and Cybernetics University of Chemistry and Technology Prague 166 28 Prague 6 Czech Republic

Department of Neurology Faculty of Medicine in Hradec Králové Charles University Prague 500 05 Hradec Králové Czech Republic

Department of Sports Medicine 2nd Faculty of Medicine and FN Motol Charles University Prague 150 00 Prague 5 Czech Republic

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