Find in Library

Oxygen uptake (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula>) is an essential metric for evaluating cardiopulmonary health and athletic performance, which can barely be directly measured. Heart rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula>) is a prominent physiological indicator correlated with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> and is often used for indirect <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction. This study investigates the impact of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> placement on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction accuracy by analyzing <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> data combined with the respiratory rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>E</mi><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula>) and minute ventilation (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><mi>E</mi></mrow></semantics></math></inline-formula>) from three anatomical locations: the chest; arm; and wrist. Twenty-eight healthy adults participated in incremental and constant workload cycling tests at various intensities. Data on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>E</mi><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><mi>E</mi></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> were collected and used to develop a neural network model for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction. The influence of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> position on prediction accuracy was assessed via Bland–Altman plots, and model performance was evaluated by mean absolute error (MAE), coefficient of determination (R²), and mean absolute percentage error (MAPE). Our findings indicate that <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> combined with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>E</mi><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><mi>E</mi></mrow></semantics></math></inline-formula> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn><mi mathvariant="normal">H</mi><mi mathvariant="normal">R</mi><mo>+</mo><mi mathvariant="normal">R</mi><mi mathvariant="normal">E</mi><mi mathvariant="normal">S</mi><mi mathvariant="normal">P</mi><mo>+</mo><mover accent="true"><mrow><mi mathvariant="normal">V</mi></mrow><mo>˙</mo></mover><mi mathvariant="normal">E</mi></mrow></msub></mrow></semantics></math></inline-formula>) produces the most accurate <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> predictions (MAE: 165 mL/min, R²: 0.87, MAPE: 15.91%). Notably, as exercise intensity increases, the accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction decreases, particularly within high-intensity exercise. The substitution of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> with different anatomical sites significantly impacts <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction accuracy, with wrist placement showing a more profound effect compared to arm placement. In conclusion, this study underscores the importance of considering <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><mi>R</mi></mrow></semantics></math></inline-formula> placement in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> prediction models, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>E</mi><mi>S</mi><mi>P</mi></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><mi>E</mi></mrow></semantics></math></inline-formula> serving as effective compensatory factors. These findings contribute to refining indirect <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mover accent="true"><mrow><mi>V</mi></mrow><mo>˙</mo></mover><msub><mrow><mi>O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></semantics></math></inline-formula> estimation methods, enhancing their predictive capabilities across different exercise intensities and anatomical placements.