With the assistance of powerful machine learning algorithms, data collecting and processing efficiency of wearable electromechanical sensors are highly improved. Meanwhile, the functions and applications of these intelligent sensing systems are widely enhanced and expanded. In this review, wearable electromechanical sensors with various working mechanisms and their typical usage for monitoring human physiological signals are outlined. The recent advances of machine learning-assisted wearable electromechanical sensing systems in specific applications of tactile perception, gesture/gait recognition, and health care are then summarized and discussed. Finally, current existing limitations and future perspectives are discussed. The progress of intelligent wearable electromechanical sensing systems will promote the development in the domains of human-machine interface (HMI), soft robotics, metaverse, etc.