Illness detection based on nervous system metrics

The system uses a wearable device to track a person's heart rate variability (HRV) over time. It then feeds this HRV data, specifically looking at its low and high frequency components, into a machine learning program. This program compares the HRV patterns from different time periods to spot significant changes, and if a change is detected, it shows an illness risk score on a user's phone or device.

Why it matters: Since 2021, the accessibility and performance of machine learning models for time-series physiological data have significantly improved, potentially simplifying the development of the required classifier.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedWearable sensor, machine learning software system

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