Real-time smart multisensing wearable platform for monitoring sweat biomarkers during exercise

Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise in hot and humid conditions. Real-time noninvasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration status during endurance exercise. In this work, we describe a platform that includes different sweat biomonitoring prototypes of cost-effective, smart wearable devices for continuous biomonitoring of sweat during exercise. One prototype is based on conformable and disposable soft sensing patches with an integrated multi-sensor array requiring the integration of different sensors and printed sensors with their corresponding functionalization protocols on the same substrate. The second is based on silicon based sensors and paper microfluidics. Both platforms integrate a multi-sensor array for measuring sodium, potassium, and pH in sweat. We show preliminary results obtained from the multi-sensor prototypes placed on two athletes during exercise. We also show that the machine learning algorithms can predict the percentage of body weight loss during exercise from biomarkers such as heart rate and sweat sodium concentration collected over multiple subjects.