RESUMEN
The rapid growth of the Internet of Things and wearable sensors has led to advancements in monitoring technology in the field of health. One such advancement is the development of wearable respiratory sensors, which offer a new approach to real-time respiratory monitoring compared to traditional methods. However, the energy consumption of these sensors raises concerns about environmental pollution. To address the issue, this study proposes the use of a triboelectric nanogenerator (TENG) as a sustainable energy source. The electrical conductivity of the TENG is improved by incorporating chitosan and carbon nanotubes, with the added benefit of chitosan's biodegradability reducing negative environmental impact. A wireless intelligent respiratory monitoring system (WIRMS) is then introduced, which utilizes a degradable triboelectric nanogenerator for real-time respiratory monitoring, diagnosis, and prevention of obstructive respiratory diseases. WIRMS offers stable and highly accurate respiratory information monitoring, while enabling real-time and nondestructive transmission of information. In addition, machine learning technology is used for sleep respiration state analysis. The potential applications of WIRMS extend to wearables, medical monitoring and sports monitoring, thereby presenting innovative ideas for modern medical and sports monitoring.
Asunto(s)
Nanotubos de Carbono , Dispositivos Electrónicos Vestibles , Tecnología Inalámbrica , Tecnología Inalámbrica/instrumentación , Humanos , Nanotubos de Carbono/química , Monitoreo Fisiológico/instrumentación , Monitoreo Fisiológico/métodos , Sueño/fisiología , Deportes , Quitosano/química , Nanotecnología/instrumentación , Nanotecnología/métodos , Respiración , Conductividad Eléctrica , Suministros de Energía EléctricaRESUMEN
In the smart era, big data analysis based on sensor units is important in intelligent motion. In this study, a dance sports and injury monitoring system (DIMS) based on a recyclable flexible triboelectric nanogenerator (RF-TENG) sensor module, a data processing hardware module, and an upper computer intelligent analysis module are developed to promote intelligent motion. The resultant RF-TENG exhibits an ultra-fast response time of 17 ms, coupled with robust stability demonstrated over 4200 operational cycles, with 6% variation in output voltage. The DIMS enables immersive training by providing visual feedback on sports status and interacting with virtual games. Combined with machine learning (K-nearest neighbor), good classification results are achieved for ground-jumping techniques. In addition, it shows some potential in sports injury prediction (i.e., ankle sprains, knee hyperextension). Overall, the sensing system designed in this study has broad prospects for future applications in intelligent motion and healthcare.
RESUMEN
The use of green intelligent sensing systems which are based on triboelectric nanogenerators have sparked a surge of research in recent years. The development has made significant contributions to the field of promoting human health. However, the integration of an intelligent sensing system with multi-directional triboelectric nanogenerators (TENGs) remains challenges in the field of motion monitoring. To solve this research issue, this study designed a self-powered multifunctional fitness blanket (SF-MFB) which incorporates four TENGs, features multi-sensors and wireless motion monitoring capabilities. It presents a self-powered integrated sensing system which utilizes four TENG sensing units to monitor human motion. Each TENG sensing unit collects the mechanical energy generated during motion. The system is composed of SF-MFB, Bluetooth transmission terminal, and upper computer analysis terminal. Its main purpose is to wirelessly monitor and diagnose human sports skills and enables real-time human-computer interaction. The TENG integrated self-powered sensing system demonstrates practicality in sports skills monitoring, diagnosis, human-computer interaction and entertainment. This research introduces a novel approach for the application of TENG self-powered intelligent integrated sensing system in health promotion.