Volume 7 - Issue 3
A Two-Level Approach to Characterizing Human Activities from Wearable Sensor Data
- Sebastien Faye
Interdisciplinary Centre for Security, Reliability and Trust (SnT) University of Luxembourg 4 rue Alphonse Weicker, L-2721 Luxembourg, Luxembourg
sebastien.faye@uni.lu
- Nicolas Louveton
Interdisciplinary Centre for Security, Reliability and Trust (SnT) University of Luxembourg 4 rue Alphonse Weicker, L-2721 Luxembourg, Luxembourg
- Gabriela Gheorghe
Interdisciplinary Centre for Security, Reliability and Trust (SnT) University of Luxembourg 4 rue Alphonse Weicker, L-2721 Luxembourg, Luxembourg
- Thomas Engel
Interdisciplinary Centre for Security, Reliability and Trust (SnT) University of Luxembourg 4 rue Alphonse Weicker, L-2721 Luxembourg, Luxembourg
Keywords: Activity Recognition,Wearable & Mobile Computing, Sensing Systems, Data Analytics.
Abstract
The rapid emergence of new technologies in recent decades has opened up a world of opportunities
for a better understanding of human mobility and behavior. It is now possible to recognize human
movements, physical activity and the environments in which they take place. And this can be done
with high precision, thanks to miniature sensors integrated into our everyday devices. In this paper,
we explore different methodologies for recognizing and characterizing physical activities performed
by people wearing new smart devices. Whether it’s smartglasses, smartwatches or smartphones, we
show that each of these specialized wearables has a role to play in interpreting and monitoring moments
in a user’s life. In particular, we propose an approach that splits the concept of physical activity
into two sub-categories that we call micro- and macro-activities. Micro- and macro-activities are supposed
to have functional relationship with each other and should therefore help to better understand
activities on a larger scale. Then, for each of these levels, we show different methods of collecting,
interpreting and evaluating data from different sensor sources. Based on a sensing system we have
developed using smart devices, we build two data sets before analyzing how to recognize such activities.
Finally, we show different interactions and combinations between these scales and demonstrate
that they have the potential to lead to new classes of applications, involving authentication or user
profiling.