Triboelectric and Piezoelectric Nanogenerators for Self-Powered Healthcare Monitoring Devices: Operating Principles, Challenges, and Perspectives.
Enrique Delgado-AlvaradoJaime Martínez-CastilloLuis Zamora-PeredoJose Amir Gonzalez-CalderonRicardo López-EsparzaMuhammad Waseem AshrafShahzadi TayyabaAgustin L Herrera-MayPublished in: Nanomaterials (Basel, Switzerland) (2022)
The internet of medical things (IoMT) is used for the acquisition, processing, transmission, and storage of medical data of patients. The medical information of each patient can be monitored by hospitals, family members, or medical centers, providing real-time data on the health condition of patients. However, the IoMT requires monitoring healthcare devices with features such as being lightweight, having a long lifetime, wearability, flexibility, safe behavior, and a stable electrical performance. For the continuous monitoring of the medical signals of patients, these devices need energy sources with a long lifetime and stable response. For this challenge, conventional batteries have disadvantages due to their limited-service time, considerable weight, and toxic materials. A replacement alternative to conventional batteries can be achieved for piezoelectric and triboelectric nanogenerators. These nanogenerators can convert green energy from various environmental sources (e.g., biomechanical energy, wind, and mechanical vibrations) into electrical energy. Generally, these nanogenerators have simple transduction mechanisms, uncomplicated manufacturing processes, are lightweight, have a long lifetime, and provide high output electrical performance. Thus, the piezoelectric and triboelectric nanogenerators could power future medical devices that monitor and process vital signs of patients. Herein, we review the working principle, materials, fabrication processes, and signal processing components of piezoelectric and triboelectric nanogenerators with potential medical applications. In addition, we discuss the main components and output electrical performance of various nanogenerators applied to the medical sector. Finally, the challenges and perspectives of the design, materials and fabrication process, signal processing, and reliability of nanogenerators are included.
Keyphrases
- healthcare
- end stage renal disease
- chronic kidney disease
- ejection fraction
- prognostic factors
- peritoneal dialysis
- public health
- mental health
- risk assessment
- physical activity
- electronic health record
- body mass index
- machine learning
- patient reported outcomes
- current status
- solid state
- data analysis
- health insurance
- human health
- weight gain