Efficient Wearable Sensor Human Activity Recognition Using Bidirectional Selective State Space Models

HARMamba, a lightweight and efficient activity recognition model, leverages bidirectional selective state space modeling to outperform attention-based and convolutional networks in recognition accuracy while maintaining lower computational complexity and memory consumption.