To gain a deeper understanding of the current research status of cooling suits in high-temperature mines, this paper provides separate introductions to vest-type cooling suits and full-body cooling suits. It summarizes the categories of cooling suits based on different cooling media and systematically elucidates the advantages and disadvantages of each type. The paper also analyzes the current application status of cooling suits in mine environments. It suggests that the future research directions for cooling suits in mines include the miniaturization of components, intelligent temperature control, optimization of new phase-change materials, development of cooling fabrics, and research in smart fibers.

Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems have been designed to monitor users’ gait patterns, they commonly spend a lot of time and effort to extract gait metrics from signal data. This study aims to design an artificial intelligence-empowered and economic-friendly gait monitoring system. A pair of intelligent shoes with a single inertial sensor and a smartphone application were developed as a gait monitoring system to detect users’ gait cycle, stand phase time, swing phase time, stride length, and foot clearance. We recruited 30 participants (24.09 ± 1.89 years) to collect gait data and used the Vicon motion capture system to verify the accuracy of the gait metrics. The results show that the gait monitoring system performs better on the assessment of the gait metrics. The accuracy of stride length and foot clearance is 96.17% and 92.07%, respectively. The artificial intelligence-empowered gait monitoring system holds promising potential for improving gait analysis and monitoring in the medical and healthcare fields.