Your activity tracker knows when you quit smoking

Abstract

This paper discusses outcomes of our exploratory research aiming to discover ways of utilising continuous long term respiratory rate data collected from actigraphy (wrist-worn accelerometers.) We show that by monitoring changes in respiratory rate during sleep, we can detect and visualise various physical conditions that were previously not detectable using such simple wearable sensors, namely; the subjective level of drunkenness, fever, and smoking cessation. This study provides valuable insight into the potential of actigraphy, not simply as a tool for detecting common daily activities, but as a base for building a generic lifelog system that can evaluate the more qualitative aspects of your life.