Selfmeasured

Selfmeasured is a term used to describe data or measurements collected directly by an individual about themselves, often with consumer-grade devices, apps, or manual methods, rather than by clinicians or laboratory instruments. It encompasses a range of health, fitness, and daily living metrics and is widely used in personal health management and increasingly in research.

In health and wellness contexts, self-measured data include home blood pressure readings, daily weight, blood glucose logs, sleep duration tracked by wearables, heart rate, steps, and other activity metrics captured by smartphones or wearable devices. In research and digital health, self-measured data are used to supplement clinician-recorded data, enable remote monitoring, and support large-scale citizen science projects.

The usefulness of self-measured data depends on device quality, proper technique, user adherence, and robust data handling. Limitations include measurement error, user error, device variability, missing data, and privacy or data governance concerns. Standards and best practices—such as calibration protocols, clear measurement instructions, and transparent data provenance—help improve reliability.

From a practical perspective, self-measured data empower individuals and clinicians with continuous monitoring, trend detection, and personalized feedback, while enabling population-level insights when aggregated with appropriate safeguards.

Related concepts include patient-generated health data, self-monitoring, and the quantified self movement.