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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.

Gait and balance have emerged as a critical area of research in health technology. Gait and balance studies have been affected by the researchers’ slow follow-up of research advances due to the absence of visual inspection of the study literature across decades. This study uses advanced search methods to analyse the literature on gait and balance in older adults from 1993 to 2022 in the Web of Science (WoS) database to gain a better understanding of the current status and trends in the field for the first time. The study analysed 4484 academic publications including journal articles and conference proceedings on gait and balance in older adults. Bibliometric analysis methods were applied to examine the publication year, number of publications, discipline distribution, journal distribution, research institutions, application fields, test methods, analysis theories, and influencing factors in the field of gait and balance. The results indicate that the publication of relevant research documents has been steadily increasing from 1993 to 2022. The United States (US) exhibits the highest number of publications with 1742 articles. The keyword “elderly person” exhibits a strong citation burst strength of 18.04, indicating a significant focus on research related to the health of older adults. With a burst factor of 20.46, Harvard University has made impressive strides in the subject. The University of Pittsburgh displayed high research skills in the area of gait and balance with a burst factor of 7.7 and a publication count of 103. The research on gait and balance mainly focuses on physical performance evaluation approaches, and the primary study methods include experimental investigations, computational modelling, and observational studies. The field of gait and balance research is increasingly intertwined with computer science and artificial intelligence (AI), paving the way for intelligent monitoring of gait and balance in the elderly. Moving forward, the future of gait and balance research is anticipated to highlight the importance of multidisciplinary collaboration, intelligence-driven approaches, and advanced visualization techniques.

The traditional self-supported piezoelectric thin films prepared by filtration methods are limited in practical applications due to their poor tensile properties. The strategy of using flexible polyethylene terephthalate (PET) fabric as the flexible substrate is beneficial to enhancing the flexibility and stretchability of the flexible device, thus extending the applications of pressure sensors. In this work, a novel wearable pressure sensor is prepared, of which uniform and dense ZnO nanoarray-coated PET fabrics are covered by a two-dimensional MXene nanosheet. The ternary structure incorporates the advantages of the three components including the superior piezoelectric properties of ZnO nanorod arrays, the excellent flexibility of the PET substrate, and the outstanding conductivity of MXene, resulting in a novel wearable sensor with excellent pressure-sensitive properties. The PET/ZnO@MXene pressure sensor exhibits excellent sensing performance (S = 53.22 kPa−1), fast response/recovery speeds (150 ms and 100 ms), and superior flexural stability (over 30 cycles at 5% strain). The composite fabric also shows high sensitivity in both motion monitoring and physiological signal detection (e.g., device bending, elbow bending, finger bending, wrist pulse peaks, and sound signal discrimination). These findings provide insight into composite fabric-based pressure-sensitive materials, demonstrating the great significance and promising prospects in the field of flexible pressure sensing.