In this study, the hypothesis being explored is that VO2Max and other CPET parameters can be accurately estimated from biosignals (namely, motion from accelerometers and cardiopulmonary variables from EKG) collected during activities of daily living using wearable biosensors worn by study participants. This study will aim to collect development and validation data for a machine learning algorithm and to evaluate the performance of the algorithm. A total of 1000 participants will be enrolled including: (Normal) 100 participants, self-reported healthy male and female participants aged 18 to 80 and (Standard of Care) 900 participants.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Collect development and validation data for a VO2Max (eVO2Max) machine learning algorithm and to evaluate the performance of the algorithm.
Timeframe: March 2025