| Full text | |
| Author(s): |
Frade, Maria Cecilia Moraes
;
Beltrame, Thomas
;
Gois, Mariana de Oliveira
;
Pinto, Allan
;
Tonello, Silvia Cristina Garcia de Moura
;
Torres, Ricardo da Silva
;
Catai, Aparecida Maria
;
Jaafar, Zulkarnain
Total Authors: 8
|
| Document type: | Journal article |
| Source: | PLoS One; v. 18, n. 3, p. 18-pg., 2023-03-02. |
| Abstract | |
Cardiopulmonary exercise testing (CPET) is a non-invasive approach to measure the maximum oxygen uptake (V O2-max), which is an index to assess cardiovascular fitness (CF). However, CPET is not available to all populations and cannot be obtained continuously. Thus, wearable sensors are associated with machine learning (ML) algorithms to investigate CF. Therefore, this study aimed to predict CF by using ML algorithms using data obtained by wearable technologies. For this purpose, 43 volunteers with different levels of aerobic power, who wore a wearable device to collect unobtrusive data for 7 days, were evaluated by CPET. Eleven inputs (sex, age, weight, height, and body mass index, breathing rate, minute ventilation, total hip acceleration, walking cadence, heart rate, and tidal volume) were used to predict the V O(2-max)by support vector regression (SVR). Afterward, the SHapley Additive exPlanations (SHAP) method was used to explain their results. SVR was able to predict the CF, and the SHAP method showed that the inputs related to hemodynamic and anthropometric domains were the most important ones to predict the CF. Therefore, we conclude that the cardiovascular fitness can be predicted by wearable technologies associated with machine learning during unsupervised activities of daily living. (AU) | |
| FAPESP's process: | 18/19016-8 - Associations between aerobic power and fitness |
| Grantee: | Thomas Beltrame |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 16/22215-7 - Impact of inspiratory muscle training and aging on metabolic mapping, autonomic modulation, and cardiovascular, respiratory and metabolic responses, and prediction of cardiorespiratory health through wearables |
| Grantee: | Aparecida Maria Catai |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 17/09639-5 - Exploring machine learning techniques for aerobic system analysis with applicability for cardiorespiratory rehabilitation programs |
| Grantee: | Thomas Beltrame |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 18/22818-9 - Continuous cardiovascular health evaluation by wearables |
| Grantee: | Maria Cecília Moraes Frade |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 19/16253-1 - Unraveling the secret of Brazilian and Dutch soccer by capturing successful elements of playing style and playing strategies |
| Grantee: | Allan da Silva Pinto |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |