Wearable motion-monitoring systems have been widely used in recent years. However, the battery energy storage problem of traditional wearable devices limits the development of human sports training applications. In this paper, a self-powered and portable micro-structure triboelectric nanogenerator (MS-TENG) has been made. It consists of micro-structure polydimethylsiloxane (PDMS) film, fluorinated ethylene propylene (FEP) film, and lithium chloride polyacrylamide (LiCl-PAAM) hydrogel. Through the micro-structure, the voltage of the MS-TENG can be improved by 7 times. The MS-TENG provides outstanding sensing properties: maximum output voltage of 74 V, angular sensitivity of 1.016 V/degree, high signal-to-noise ratio, and excellent long-term service stability. We used it to monitor the running skills of speed skaters. It can also store the biomechanical energy which is generated in the process of speed skating through capacitors. It demonstrates capability of sensor to power electronic calculator and electronic watch. In addition, as a flexible electrode hydrogel, it can readily stretch over 1300%, which can help improve the service life and work stability of MS-TENG. Therefore, MS-TENG has great application potential in human sports training monitoring and big data analysis.

Smart sport and big data have become inextricably linked with new technologies and devices to monitor sport-related information in real time. In this paper, a lightweight, portable and self-powered triboelectric nanogenerator (LPS-TENG) has been developed to monitor the frequency and force of skaters’ pedaling. Friction layers are formed of polytetrafluoroethylene (PTFE) and nylon films. Based on the triboelectric effect, LPS-TENG does not require an external power supply, and it can be used to monitor biomechanical motion independently. Under the conditions of 1 Hz and 17.19 N, the outputting voltage of LPS-TENG is stabilized at 14 V. Wireless data transmission is achieved with the help of the LPS-TENG and AD module. Visual feedback is provided by the upper computer system in the process of processing data. The wireless intelligent motion correction system is composed of an LPS-TENG, an AD module and a back-end computer. It can clearly analyze the changes between different frequencies and forces during skating. Results showed that the signal of tester’s high-frequency and great-force motion, was transmitted to the computer, and its feedback was given after analysis and processing successfully. The system may help coaches develop training methods, means and tactics to increase athletes’ performance and competitive level in athletic sport. The purpose of this study is to provide new ideas for monitoring skaters’ sport techniques, promote the use of force sensors in the monitoring of sport and develop intelligent assistant training systems.

With the energy crisis and environmental pollution becoming a growing concern worldwide, the development of clean and renewable energy from the environment has become an imperative for human survival and development. However, the equipment used to harvest clean renewable energy is large, subject to environmental impacts and regional differences (such as wind, solar and tidal energy). In this study, a biodegradable eggshell membrane triboelectric nanogenerator (EM-TENG) is introduced for the purpose of harvesting low-frequency mechanical energy. A Wireless Intelligent Motion Monitoring System (WIMMS) has been created using EM-TENG. It includes a Bluetooth sensor terminal and an intelligent processing terminal for digital signal reception on a host computer. The EM-TENG can be attached to knee and ankle joints to monitor posture. Therefore, for real-time monitoring of joint and kinetic chain changes during land training of ice dance athletes, the intelligent ice dance land training aid system is important. As a wearable motion monitoring sensor, EM-TENGs application in intelligent motion monitoring, intelligent wearable devices and big data analytics is being promoted.

Introduction: Web-implemented exercise intervention is the latest and innovative method to improve people's mental health. Currently, many studies have proven that web-implemented interventions are effective to improve depression and anxiety in adults. However, the influence of different web-implemented exercise interventions on depression and anxiety in patients with neurological disorders is still unclear.Objective: The study aims to systematically summarize the type and content of web-implemented exercise interventions and quantify the effect of different web-implemented exercise interventions on depression and anxiety in patients with neurological disorders.Methods: Four literature databases (PubMed, Web of Science, China National Knowledge Infrastructure, and WanFang data) were searched. The literature search considered studies published in English or Chinese before October 13, 2022. Randomized controlled trials (RCTs) that participants accepted web-implemented interventions were included. Two authors independently extracted data and assessed the risk of bias for included studies. Standardized mean differences (SMD) with 95% CI were used to integrate the effect size.Results: 16 RCTs (a total of 963 participants) were included. The results showed that web-implemented exercise intervention had a significant effect on depression (SMD = −0.80; 95% CI, −1.09 to −0.52; I² = 75%; P < 0.00001) and anxiety (SMD = −0.80; 95% CI, −1.23 to −0.36; I² = 75%; P = 0.0003) in patients with a neurological disorder. The subgroup analysis showed that the effectiveness of the web-implemented exercise intervention was influenced by several factors, such as web-implemented exercise intervention type, component, and intervention duration.Conclusion: Web-implemented exercise intervention has a relieving effect on depression and anxiety symptoms in patients with neurological disorders. Additionally, the intervention type, intervention duration, and component can influence the effect size.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier: CRD42023409538.

Aerobic capacity is important for speed skaters to achieve good results in middle–long distance events. The technical characteristics of speed skating cause intermittent blood flow blockage in the lower limbs. Therefore, an athlete’s aerobic capacity on ice may differ from that measured by cycling or running. Now, the on-ice aerobic capacity lacks methods for conducting aerobic capacity tests on ice. Objective: The objective of this study was to develop a method for measuring on-ice aerobic capacity for young athletes and to compare it with the VO_2max test on cycling. Methods: This study established a test method for the on-ice aerobic capacity of young, high-level speed skaters with incremental load (on-ice incremental skating test, OIST) through expert interviews and literature review. In the first part, OIST was used to test the aerobic abilities of 65 youth professional speed skaters (51 males and 14 females) on ice and to explore the correlation with their specific performance. The second part compares the relationship between aerobic capacity on ice and aerobic capacity on bicycle of 18 young high-level male athletes. The third part establishes the regression formula of ice ventilation threshold heart rate. The OIST established in this study can evaluate the on-ice aerobic capacity of athletes from National Level and Level 1&2 in China. The athletes’ on-ice aerobic capacity indicators were significantly lower than those of the cycling test. However, the values of absolute VO_2max and absolute ventilatory threshold had a high correlation (R = 0.532, p < 0.05; R = 0.584, p < 0.05). The regression formula of ventilatory threshold heart rate on ice = 0.921 × HRmax (Cycling test) −9.243. The OIST established in this study meets the characteristics and requirements of the VO_2max measurement method. The OIST seems to be able to better evaluate the aerobic capacity of athletes skating on ice. The indicators of maximum oxygen uptake and ventilation threshold in OIST were significantly lower than those in the aerobic cycling test, but there was a good correlation. The aerobic cycling test can be used as an important selection index of the ice aerobic capacity of speed skaters. The regression formula will provide an important basis for coaches to accurately monitor the intensity of ice training.