After the COVID-19 outbreak, the effective recycling of large amounts of medical waste has become a pressing issue. Triboelectric nanogenerators (TENGs) can utilize a wide range of materials for sensing and energy harvesting, making them one of the potential ways to turn waste into treasure. However, the reported waste-based TENGs so far suffer from insufficient utilization of medical waste and lack in-depth sensing data analysis in the field of human motion monitoring. To address these issues, this study proposes a TENG based on medical waste. It is designed in two different forms for two application scenarios: energy harvesting and intelligent human motion sensing. The energy harvester has a maximum output power density of up to 65 mW/m(2), which can drive electronic devices such as calculators and thermometers. The motion sensor has good sensitivity and stability for changes in force. When only a single sensor is used to collect data, combined with feature extraction and pattern recognition algorithms, instant input and instant classification of four different human body motions with an accuracy of up to 95.5% are successfully achieved. It is a very significant advantage in the practical application of self-powered intelligent monitoring.