Research quarterly for exercise and sport
29261437
PURPOSE: The purpose of this study was to examine differences in heart rate recovery (HRRec) and oxygen consumption recovery (VO recovery) between young healthy-weight children and children with obesity following a maximal volitional graded exercise ...
American journal of health promotion : AJHP
29431507
PURPOSE: Limited research has evaluated the independent and additive associations of moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB), and cardiorespiratory fitness (CRF) with metabolic syndrome, which was the purpose of this st...
OBJECTIVE: In this paper we propose artificial intelligence methods to estimate cardiorespiratory fitness (CRF) in free-living using wearable sensor data.
BACKGROUND: Exercise testing devices for evaluating cardiopulmonary fitness in patients with severe disability after stroke are lacking, but we have adapted a robotics-assisted tilt table (RATT) for cardiopulmonary exercise testing (CPET). Using the ...
Disability and rehabilitation. Assistive technology
27762641
PURPOSE: The integration of sufficient cardiovascular stress into robot-assisted gait (RAG) training could combine the benefits of both RAG and aerobic training. The aim was to summarize literature data on the immediate effects of RAG compared to wal...
BACKGROUND: Robot-assisted gait training (RAGT) is effective for improving dynamic balance and aerobic capacity, but previous RAGT method does not set suitable training intensity. Recently, high-intensity treadmill gait training at 70% of heart rate ...
Previous studies have demonstrated that cardiorespiratory fitness is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined ca...
BMC medical informatics and decision making
29258510
BACKGROUND: Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into p...
This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hypertension, and who are likely to benefit most from interventions, using the cardiorespiratory fitness da...
Background Prognostication of heart failure patients from cardiopulmonary exercise test (CPET) currently involves simplification of complex time-series data into summary indices. We hypothesized that prognostication could be improved by considering t...