White Paper: Edge AI for Wearables

Elias Kettunen, Development Engineer at Cicor Nordic Engineering, has authored a white paper on how Edge AI enables advanced anomaly detection in wearable medical devices. You can request your copy here.

Abstract

Wearable medical devices are becoming more intelligent as AI moves onto the device itself. Running models directly on embedded hardware allows real time analysis, protects sensitive data, and reduces dependency on cloud connectivity.

This white paper explains how lightweight neural networks can detect anomalies in biosignals such as ECG, blood flow, skin conductance, and temperature. It outlines the principles behind Edge AI, the optimisation techniques that make on device processing possible, and the role of anomaly detection in identifying early signs of irregular conditions. The paper also highlights current limitations and future opportunities for integrating AI into next generation wearables.