这是阿尔托大学一项学科交叉课程（智能可穿戴）的硬件原型项目。基于足底压力与膝关节拉伸的双传感器系统，实现识别站立、坐姿、行走、爬楼、坐站转换五种下肢动态。传感器完全嵌入袜子与护膝织物，不干扰自然步态。采用双ESP32分布式架构处理5通道实时数据；可视化网页界面通过AI辅助编程独立开发，实现了传感器数据的实时读取与动作识别结果展示，打通了从硬件采集到软件呈现的全链路。
A hardware prototype developed at Aalto University exploring non-intrusive lower-limb activity recognition. The system integrates plantar pressure sensors into socks and a stretch sensor into a knee pad, using a dual-ESP32 distributed architecture to process 5-channel real-time data. A custom-built data visualization interface — developed with AI-assisted coding — displays live sensor readings and classifies five movement states: standing, sitting, walking, stair-climbing, and sit-stand transitions.
以下为具体汇报文件：
