| 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 |
Abstract 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) | |