Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor
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%.
Authors
- Su-Ping Deng (ORCID: https://orcid.org/0000-0001-6619-6497)
- Weihong Tan (ORCID: https://orcid.org/0000-0002-8066-1524)
- Futing Wang (ORCID: https://orcid.org/0000-0001-7306-5495)
- Yujin Li (ORCID: https://orcid.org/0000-0003-1103-3273)
- Jing Xu (ORCID: https://orcid.org/0000-0003-3157-6902)
- Hongfen Yang (ORCID: https://orcid.org/0000-0001-8367-4104)
- Ren Cai (ORCID: https://orcid.org/0000-0003-2583-7133)
- Choong Eui Song (ORCID: https://orcid.org/0000-0001-9221-6789)
- Jiajun Zhan
- Weihua Li (ORCID: https://orcid.org/0000-0001-5660-5082)
Institutions
- Xinyang Normal University (CN)
- Hunan University (CN)
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Sciences (CN)
- China University of Petroleum, Beijing (CN)
- Renji Hospital (CN)
- Zhejiang Cancer Hospital (CN)
- Cancer Hospital of Chinese Academy of Medical Sciences (CN)
- Institute of Molecular Medicine (IN)
- Hengyang Academy of Agricultural Sciences (CN)
- China University of Petroleum, East China (CN)
- University of Chinese Academy of Sciences (CN)
- University of South China (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1021/acs.nanolett.4c06485
- Citations
- 25
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 16.85
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province