Author(s): Ramos, Guilherme Alexandre dos Santos Espadanal
Date: 2018
Persistent ID: http://hdl.handle.net/10362/40257
Origin: Repositório Institucional da UNL
Subject(s): Online Processing; Offline Processing; Biosignals; Monitoring of Fatigue Levels; Machine-Learning; Global Fatigue Index; Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias
Physical activity is a constant in life, prolonging since the primordial times until now as an intrinsic element of human condition, though his character have suffered a transmutation, going from a need, by the predatory nature of the human being, for an option in escaping sedentary habits of contemporary society. Despite the enormous benefits of sports practice, there are also some negative consequences associated, namely the emergence of muscular injuries provided by the installation of fatigue, due to an overload on time or in the intensity of training. The consequences of an injury are drastic, conditioning the quotidian of the injured and carrying high costs for the health system, establishing this problem as the starting point of the present work. Although investigations on this subject have recently appeared, yet is not common to find commercial solutions for evaluating fatigue and with the capability of warning the user about the risk of injury. In order to avoid the fatigue consequences, is proposed the implementation of a computational system for physiological signal processing - Electromyographic (EMG) and Electrocardiographic (ECG) - extracting multiple indexes with informative potential at fatigue level. There is provided an automatic evaluation of the state of fatigue assured by the definition of a Global Fatigue Index that synthesises information from distinct individual fatigue indexes and implementation of a Classification System, with the capability of giving to the user the indication if the physical activity is originating the approximation or deviation from fatigue state. The computer system was built for a future integration as a plugin on a signal acquisition software. This framework is a specialized tool for acquiring and processing of the physiological signals collected in equipments such as bitalino and biosignalsplux, being directed to the practice of indoor cycling.
