Approximately 22% of the 86 million people in the United States living with prediabetes are unaware of their condition. Detection of acetone in human respiration offers an effective and painless approach for the diagnosis of prediabetes. In this work, a wearable active acetone biosensor employing chitosan and reduced graphene oxide (RGO) as sensitive materials was developed to non-invasively diagnose prediabetes. When operated under 97.3% relative humidity at room temperature, the prepared chitosan and RGO composite film-based sensor exhibited a good sensing response of 27.89% under 10 ppm acetone in respiratory gases, which is about 5 times higher than the sensing response of pure chitosan film-based devices. In addition, finite element analysis and phase-field simulation were conducted to provide theoretical support for the active sensing mechanism. This work not only presents a wirelessly powered wearable active acetone biosensor, but also paves the way for a new method of non-invasive prediabetes diagnosis.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- General Materials Science
- Electrical and Electronic Engineering