How to Calibrate Health Measurements Using Related Body Data

This patent describes a way to make health measurements more accurate by adjusting them based on other related body data, needing less testing and computer power.

What it covers

This patent provides a system and method for improving the accuracy of physiological measurements. It achieves this by calibrating a primary measurement based on a 'variable that affects the measurement,' which can be another related physiological measurement. The technique aims to produce reliable adjustments using minimal initial test data and requiring less computational effort.

What it doesn't cover

• —Does not cover calibration systems that do not use a related physiological variable to adjust the primary measurement.
• —Does not cover calibration techniques that require large amounts of test data or significant computing power.
• —Does not cover calibration of non-biological or non-health-related measurements.
• —Does not cover methods for initial measurement acquisition, only the calibration step.

The clever bit

The clever part is using a related physiological measurement as a variable to adjust and improve the accuracy of a primary physiological measurement. This approach aims to achieve reliable calibration with significantly less initial test data and computing resources than traditional methods.

Why it matters

Accurate physiological measurements are vital for health monitoring, medical diagnostics, and fitness tracking. This patent matters because it aims to make these measurements more reliable and easier to achieve. By needing less test data and computational power, it could enable more efficient and cost-effective sensors in various devices.

Real-world examples

• 1.Smartwatches measuring heart rate
• 2.Continuous glucose monitors
• 3.Blood pressure cuffs
• 4.Fitness trackers
• 5.Medical diagnostic devices