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Exploring machine learning techniques for aerobic system analysis with applicability for cardiorespiratory rehabilitation programs

Grant number: 17/09639-5
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): November 01, 2017
Effective date (End): October 31, 2021
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Aparecida Maria Catai
Grantee:Thomas Beltrame
Home Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated scholarship(s):18/19016-8 - Associations between aerobic power and fitness, BE.EP.PD


The study of the aerobic system integrated responses during physical activities is of great interest for rehabilitation and training programs. The main objective of this research project is to explore machine learning techniques to model/understand the aerobic system responses by the integration of multiple biological signals during dynamics exercise. Forty young healthy participant of both sexes and variable aerobic power will be recruited for this study. Participants will perform a pseudorandom binary sequence protocol followed by a cardiopulmonary test. During these exercise protocols, biological signals obtained from, among others, near-infrared spectroscopy and photoplethysmography will be used as inputs to machine learning algorithms. These algorithms will be used to model the inter-relationship between the biological signals into general rules in order to build a general description of the aerobic response. Machine learning algorithms include tree decision and artificial neural networks. The aerobic system modeling may allow us to identify physiological events that are related to physiological reserve (such as, the speed of the aerobic system adjustment during exercise transitions) that would impact physical capacity and general health. Therefore, technologies that monitor key physiological events may have the potential to detect changes in aerobic power, allowing "real-time" adjustments of rehabilitation and training programs. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
LINARES, STEPHANIE NOGUEIRA; BELTRAME, THOMAS; FERRARESI, CLEBER; GALDINO, GABRIELA AGUIAR MESQUITA; CATAI, APARECIDA MARIA. Photobiomodulation effect on local hemoglobin concentration assessed by near-infrared spectroscopy in humans. Lasers in Medical Science, v. 35, n. 3, p. 641-649, APR 2020. Web of Science Citations: 1.

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