Low Power Wearable

Low-power wearable technology focuses on developing miniature devices capable of real-time health monitoring and other applications while minimizing energy consumption. Current research emphasizes efficient machine learning algorithms, particularly lightweight convolutional and recurrent neural networks, often employing quantization and neural architecture search to optimize model size and computational cost for deployment on resource-constrained microcontrollers. This field is significant for enabling continuous, unobtrusive health monitoring in diverse applications like sepsis detection, seizure prediction, and heart rate monitoring, ultimately improving healthcare accessibility and patient outcomes.