Overview

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 300 participants will be enrolled including: (Normal) 200 participants, self-reported healthy male and female participants aged 18 to 80 and (Standard of Care) 100 participants

Eligibility

Inclusion Criteria:

1. Willing and able to comply with protocol procedures and available for the duration of the study.
2. Willing to sign and date informed consent document for study participation.
3. Participant is undergoing the Cardiopulmonary Exercise Test (CPET) as Standard of Care

Exclusion Criteria:

1. Participant is pregnant, lactating or ≤30 days post-partum.
2. Any cognitive or physical limitations that, in the opinion of the investigator, limits the participant's ability to fully follow study procedures