Realtime Person Identification via Gait Analysis using IMU Sensors on Edge Devices
This paper presents a four-layer CNN for gait-based identification from IMU data. The 236 KB model reaches 96.7% accuracy across 24 classes and runs in real time on an Arduino Nano 33 BLE Sense; a converted spiking model is also evaluated on BrainChip Akida.