Wearable Patch Enables Continuous Noninvasive Cholesterol and Triglyceride Monitoring

Noninvasive monitoring could reduce these barriers while providing continuous measurements that complement laboratory testing. However, accurately linking sweat biochemistry to blood lipid levels has been challenging because sweat composition varies with physiology and perspiration. A new study shows that a wearable patch can continuously assess lipid status by analyzing sweat.

Researchers at the California Institute of Technology (Caltech) have developed a stick-on sweat patch that continuously profiles lipids, including cholesterol and triglycerides. The device analyzes sweat to estimate corresponding blood lipid levels, allowing repeated measurements without blood draws. The approach is presented as a wearable system designed for continuous lipid profiling.

The sensor’s biochemical architecture uses a two-step enzymatic cascade to quantify sweat cholesterol. Because much of sweat cholesterol is present in esterified form and cannot be detected directly, the first reaction converts esterified cholesterol to free cholesterol. A subsequent oxidation step generates hydrogen peroxide, which the electrochemical sensor measures. For triglyceride detection, the patch integrates a polymer that traps and gradually releases adenosine triphosphate (ATP) into sweat, maintaining the cofactor supply for more than 20 hours.

To bridge the non-linear relationship between sweat and blood lipids, the team applies a causal machine learning model to the sensor readouts. The model incorporates physiological factors—including body mass index (BMI), sex, and sweat rate—to refine estimates of blood lipid concentrations. This integration is designed to deliver continuous lipid assessments from noninvasive sweat sampling.

Preclinical testing on 24 participants and the device description are presented in Nature Sensors on July 29, 2026. The researchers indicate the wearable could help provide earlier warning related to cardiovascular or metabolic diseases. The work highlights a pathway for translating sweat chemistry into clinically relevant lipid information using on-body sensing and computational modeling.

"How many people actually get their blood drawn regularly? I haven't done this myself for at least two years, probably, That's why we think a noninvasive way of monitoring lipids will be critical," said Wei Gao, professor in the Cherng Department of Medical Engineering at the California Institute of Technology and Heritage Medical Research Institute Investigator.

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