Against the backdrop of national fitness being elevated to a national strategy and "smart sports" injecting new vitality into building a leading sports nation, the development of modern sports has shifted from "experience-driven" to "data-driven." The realization of smart sports relies on modern Internet of Things (IoT) architectures, wherein sensors, as the core of data acquisition, must address challenges such as accuracy, flexibility, endurance, and environmental adaptability in sports scenarios. To meet the demand for monitoring mechanical signals during athletic activities in smart sports, this paper provides a systematic review of the application of experimental mechanical sensing technology in smart sports. It aims to offer quantitative foundations for optimizing sports techniques, preventing injuries, and evaluating training effectiveness, thereby contributing to the precision of athletic training and the high-quality development of smart sports. The review is primarily divided into two aspects: physiological mechanics and sports mechanics. In terms of physiological mechanical signal monitoring, it focuses on analyzing sensing technological innovations and signal processing optimizations in hemodynamics and muscle mechanics. Regarding sports mechanical signal monitoring, it systematically explores detection schemes for interactive forces during movement and biological postures, while comparing the differences in mechanical characteristics across various sports disciplines.