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Sensors
Volume 23
Issue 3
10.3390/s23031117
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Article

Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity

by
Adam Szulc
1,
Piotr Prokopowicz
2,
Krzysztof Buśko
1 and
Dariusz Mikołajewski
2,*
1
Institute of Physical Education, Kazimierz Wielki University in Bydgoszcz, 85-064 Bydgoszcz, Poland
2
Institute of Computer Science, Kazimierz Wielki University in Bydgoszcz, 85-064 Bydgoszcz, Poland
*
Author to whom correspondence should be addressed.
Sensors 2023, 23(3), 1117; https://doi.org/10.3390/s23031117
Submission received: 15 December 2022 / Revised: 15 January 2023 / Accepted: 16 January 2023 / Published: 18 January 2023
(This article belongs to the Special Issue Wearable Sensors for Physical Activity and Healthcare Monitoring)
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Featured Application

Potential applications of the work are systems for objective artificial-intelligent performance assessment in healthy individuals (including athletes) and patients with various injuries and conditions, including within the eHealth paradigm, including future wearable devices (e.g., e-shoes).

Abstract

The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model of different levels of physical activity with a focus on the lower limbs was constructed. The proposed fuzzy model assessing lower limb peak torque in an isokinetic mode demonstrated its effectiveness. The novelty of our research lies in the use of hierarchical fuzzy logic to extract computational rules from data provided explicitly and then to determine the corresponding physiological and pathological mechanisms. The contribution of our research lies in complementing the methods for describing physiology, pathology and rehabilitation with fuzzy parameters, including the so-called dynamic norm embedded in the model.
Keywords: posture-movement assessment; deaf athletes; computational models; fuzzy logic posture-movement assessment; deaf athletes; computational models; fuzzy logic

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MDPI and ACS Style

Szulc, A.; Prokopowicz, P.; Buśko, K.; Mikołajewski, D. Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity. Sensors 2023, 23, 1117. https://doi.org/10.3390/s23031117

AMA Style

Szulc A, Prokopowicz P, Buśko K, Mikołajewski D. Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity. Sensors. 2023; 23(3):1117. https://doi.org/10.3390/s23031117

Chicago/Turabian Style

Szulc, Adam, Piotr Prokopowicz, Krzysztof Buśko, and Dariusz Mikołajewski. 2023. "Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity" Sensors 23, no. 3: 1117. https://doi.org/10.3390/s23031117

APA Style

Szulc, A., Prokopowicz, P., Buśko, K., & Mikołajewski, D. (2023). Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity. Sensors, 23(3), 1117. https://doi.org/10.3390/s23031117

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