Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in ...
INTRODUCTION: Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between ...
We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a Fas ...
Speech-based degree of sleepiness estimation is an emerging research problem. This paper investigates an end-to-end approach, where given raw waveform as input, a convolutional neural network (CNN) estimates at its output the degree of sleepiness. Within t ...
The quality of sleep has recently come to the forefront of public health concerns in industrialized nations. Indeed, voluntary sleep curtailment is widespread, sleep disorders are increasingly recognized and both correlate with the current epidemiology of ...
Periodic environments like we experience on the surface of planet earth lead living organisms to evolve molecular anticipation devices known a circadian clocks. The word circadian refers to the period of these oscillations which last about (circa) one day ...
