AI Medical Compendium Journal:
Journal of applied physiology (Bethesda, Md. : 1985)

Showing 1 to 4 of 4 articles

Prediction of oxygen uptake kinetics during heavy-intensity cycling exercise by machine learning analysis.

Journal of applied physiology (Bethesda, Md. : 1985)
Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurately predicted during moderate exercise using easy-to-obtain sensor inputs. However, V̇o prediction a...

Automated CT-derived skeletal muscle mass determination in lower hind limbs of mice using a 3D U-Net deep learning network.

Journal of applied physiology (Bethesda, Md. : 1985)
The loss of skeletal muscle mass is recognized as a complication of several chronic diseases and is associated with increased mortality and a decreased quality of life. Relevant and reliable animal models in which muscle wasting can be monitored noni...

Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

Journal of applied physiology (Bethesda, Md. : 1985)
Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o) by w...

An experimental comparison of the relative benefits of work and torque assistance in ankle exoskeletons.

Journal of applied physiology (Bethesda, Md. : 1985)
Techniques proposed for assisting locomotion with exoskeletons have often included a combination of active work input and passive torque support, but the physiological effects of different assistance techniques remain unclear. We performed an experim...