Wear is Your Mobile? Investigating Phone Carrying and Use Habits with a Wearable Device

Kristof Van Laerhoven,Marko Borazio,Jan Hendrik Burdinski

doi:10.3389/fict.2015.00010

Abstract

This article explores properties and suitability of mobile and wearable platforms for continuous activity recognition and monitoring. Mobile phones have become generic computing platforms, and even though they might not always be with the user, they are increasingly easy to develop for and have an unmatched variety of on-board sensors. Wearable units in contrast tend to be purpose-built, and require a certain degree of user adaptation, but they are increasingly used to do continuous sensing. We explore the trade-offs for both device types in a study that compares their sensor data and that explicitly examines how often these devices are being worn by the user. To this end, we have recorded a dataset from 51 participants, who were given a wrist-worn sensor and an app to be used on their Smartphone for two weeks continuously, totalling 638 days (or over 15300 hours) of wearable and mobile data. Results confirm findings of previous studies from North America and show that Smartphones are on average being on their user less than 23% of the time, mostly during working hours. Just as noteworthy is the high variance in Smartphone use (in carrying, interacting with, and charging the phone) among participants.

Highlights

Mobile phones have become increasingly general purpose and personal computers that fit in the user’s pocket, being used by a growing number of people around the world
By correlating the amount of motion present in the data from their wearable unit and their mobile phone, we estimate when the phone is being carried by the user. This effectively means that the proximity measure for our method will be restricted to on the user or elsewhere, yet we argue that this measure in itself is already interesting for research, and that our method does have significant advantages over the wearing of Bluetooth transceivers
To estimate whether the phone is carried by the user, our method compares each of the detected motion segments from the wrist sensor to the motion segments present in the phone data

Summary

Introduction

Mobile phones have become increasingly general purpose and personal computers that fit in the user’s pocket, being used by a growing number of people around the world. We tend to use them to manage our schedules and appointments, as navigation systems to find our way in unknown environments, as flashlights, music players, or to obtain updates on the daily news. Along with their variety of uses, their computing capacity is rising steadily, enabling current generations of smartphones to be used for various application scenarios, as, for instance, in

Objectives

Results

Conclusion