Self-Aware Machine Learning for Multimodal Workload Monitoring during Manual Labor on Edge Wearable Sensors
Giulio Masinelli, Farnaz Forooghifar, Adriana Arza, David Atienza, Amir Aminifar · IEEE Design and Test · 2020
Editor's notes: This article discusses self-awareness in wearable edge devices to enable real-time and long-term health monitoring. The authors use the notion of self-awareness to improve the battery life of edge wearable sensors for multimodal health and workload monitoring. This approach leads to a 27.6% lower energy consumption with less than 6% of performance loss. -Umit Y. Ogras, Arizona State University.