Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor.

Abstract

Lactic acid has aroused increasing attention due to its close association with serious diseases. A real-time, dynamic, and intelligent detection method is vital for sensitive detection of lactic acid. Here, a machine learning (ML)-assisted perspiration-driven self-powered sensor (PDS sensor) is fabricated using Ni-ZIF-8@lactate oxidase and pyruvate oxidase (Ni-ZIF-8@LOx&POx)/laser-induced graphene (LIG), bilirubin oxidase (BOD)/LIG, and a microchannel for highly sensitive and real-time monitoring of lactic acid in sweat. Driven by the oxidation reaction of lactic acid, PDS sensors exhibit excellent sensitivity, a wide detection range, good reproducibility, and excellent selectivity for lactic acid detection in sweat. When subjects with different body mass index (BMI) undergo aerobic or anaerobic exercise or maintain a sedentary state, PDS sensors can monitor lactic acid in sweat wirelessly and in real-time. Moreover, a ML algorithm was employed to assist PDS sensors to detect lactic acid in the subjects' sweat with a high prediction accuracy of 96.0%.