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The advancement of intelligent monitoring technologies has created innovative pathways in the health sector. Leveraging sensors within smart devices, data can be seamlessly harvested by network systems. Triboelectric Nanogenerators (TENGs), acting as self-powered sensors, show promise for green, sustainable sensing and health-focused human–machine interactions. This Review Article delves into the four operational mechanisms of TENGs, providing a comprehensive review of their monitoring capabilities across varied environments. Specific applications include tracking human motion parameters, such as angles, frequencies, and trajectories, utilizing diverse materials to measure vital signs, such as heart rate, pulse, blood pressure, and respiration under changing conditions, in rehabilitation settings, employing both composite and standalone TENGs for targeted monitoring. This study also addresses challenges faced by TENGs, focusing on material flexibility, sustainability, washability, elasticity, and biocompatibility. The findings underscore the transformative potential of TENGs in health monitoring, offering valuable insights for fields such as smart sports, rehabilitation, and healthcare sensing. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The development of self-powered smart biosensors has attracted great attention due to their potential applications in human motion monitoring and energy collection systems. Here, a newly designed triboelectric nanogenerator (PSP-TENG) composed of the PU sponge, polytetrafluoroethylene, and polydimethylsiloxane for monitoring rear leg rotation motion in artistic gymnastics has been developed. The PSP-TENG can monitor the buffering and stretching time of rear leg rotation and identify the angle between the hip, knee, and ankle during the stretching stage. Furthermore, the PSP-TENG has the function of converting measured signals into power signals, which can convert collected human motion mechanical energy into electrical energy to power wearable devices. The development of PSP-TENG has made contributions to the field of human motion monitoring, providing ideas for new energy and technologies to improve the environment and promote a virtuous ecological cycle. [ABSTRACT FROM AUTHOR]

In the new era of artificial intelligence (AI) and the Internet of Things (IoT), big data collection and analysis for intelligent sports are of great importance in monitoring human health. Herein, naturally, biodegradable triboelectric nanogenerators (NB‐TENGs) are developed based on low‐cost, recyclable, and environmentally friendly corn bracts, which are further applied in neck motion recognition. Three NB‐TENGs are integrated into an elastic collar to create a neck‐condition monitoring triboelectric sensor (NCM‐TS). An intelligent behavioral monitoring system is achieved by combining NCM‐TS with a deep learning model, which allows the recognition of four types of neck motion with an average accuracy of 94%. The developed neck motion monitoring sensor has broad potential applications in sports health monitoring, rehabilitation training, and healthcare. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The advent of self-powered arrays of tribological nanogenerators (TENGs) that harvest mechanical energy for data collection has ushered in a promising avenue for human motion monitoring. This emerging trend is poised to shape the future landscape of biomechanical study. However, when we try to monitor various regions of the foot across disparate environments simultaneously, it poses a number of problems, such as the lack of satisfactory waterproofing, suboptimal heat resistance, inaccurate monitoring capacity, and the inability to transmit data wirelessly. To overcome these issues, we have developed an array of sensors affixed to the insole's surface to adeptly monitor movement gait patterns and alert users to falls using self-powered triboelectric nanogenerators (TENGs). Each sensor cell on this sensor works as an individual air gap TENG (FWF-TENG), namely flexible, waterproof, and fast response, composed of an Ecoflex single-electrode array. Each FWF-TENG boasts a fast response time of 28 ms, which is sufficient to quickly monitor pressure changes during various badminton activities. Importantly, these sensors can persistently generate electrical signals at 70%RH humidity. Data obtained from these sensors can be transmitted to an upper computer intelligent terminal wirelessly through multi-grouped FHW-ENG sensing terminals in real time to achieve human–computer interaction applications, including motion technical determinations, feedback, and fall alerts. As a result, the interconnected TENG arrays have broad potential applications, including gait rehabilitation monitoring, motion technique identification, and fall alarm applications. [ABSTRACT FROM AUTHOR]

The "Healthy China 2030" plan states that it is necessary to formulate and implement physical health intervention plans for special groups, including women. Based on questionnaire data from women in seven Chinese cities, our research analyzed the status quo of women's fitness, its influencing factors, and the differences in and characteristics of different types of women's fitness demands from four aspects: demography, fitness motivation, fitness behavior, and fitness demands, so as to provide a reference for the promotion of women's fitness. A total of 3473 valid samples were completed. The questionnaire included five age groups: there were 146 in the "20–29 years old" group, 829 in the "30–39 years old" group, 1088 in the "40–49 years old" group, 1105 in the "50–59 years old" group and 305 in the "60 years old and above" group. The questionnaire used in this study was a self-made questionnaire. The contents of the questionnaire included age, occupation, educational level, family circumstances, and health status, women's fitness behavior, fitness motivation and fitness demands. The results show that the current situation of urban women's fitness in China is characterized by low frequency and short duration of exercise. The internal factors affecting women's fitness demands include fitness motivation and fitness behavior. The external factors affecting their fitness demands are social environment and family environment. The differences in women's fitness demands mainly come from women's occupation, monthly income, and family stage. [ABSTRACT FROM AUTHOR]

Rapid gas sensing with high sensitivity and selectivity is pivotal in advanced production, in smart living, and increasingly in medical health applications. This study presents a novel Pt@InNiO x nanoflake isoprene sensor that achieves an exceptionally low limit of detection (LOD) at 2 ppb, the lowest reported for isoprene sensors to date. Notably, it exhibits high selectivity and remarkable antihumidity capacity, thus meeting the stringent requirements for lung cancer screening. To unravel the sensing mechanism, we fabricate an operando DRIFTS-Raman cell coupled to online electrical measurements. It reveals that the ultrasensitive performance of Pt@InNiO x nanoflakes stems from the activated conjugated structure of isoprene by Pt nanoclusters and from the enhanced isoprene adsorption and electron interaction due to the nanoflake morphology. The p-n junction constructed by doping Ni maintains Fermi level equilibrium, shielding it from humidity interference. Practically, we integrate these ultrasensitive Pt@InNiO x nanoflakes into a miniaturized portable electronic device that successfully distinguishes lung cancer patients with expiratory isoprene below 40 ppb, from the healthy population with isoprene above 60 ppb, enabling an accurate diagnosis in clinics. Our work not only provides a breakthrough in low-cost, noninvasive cancer screening through breath analysis but also advances the rational design of cutting-edge gas sensing materials.