TY - GEN
T1 - A single vs. multi-sensor approach to enhanced detection of smartphone placement
AU - Guiry, John J.
AU - Karr, Chris J.
AU - Van De Ven, Pepijn
AU - Nelson, John
AU - Begale, Mark
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - In this paper, the authors evaluate the ability to detect on-body device placement of smartphones. A feasibility study is undertaken with N=5 participants to identify nine key locations, including in the hand, thigh and backpack, using a multitude of commonly available smartphone sensors. Sensors examined include the accelerometer, magnetometer, gyroscope, pressure and light sensors. Each sensor is examined independently, to identify the potential contributions it can offer, before a fused approach, using all sensors is adopted. A total of 139 features are generated from these sensors, and used to train five machine learning algorithms, i.e. C4.5, CART, Naïve Bayes, Multilayer Perceptrons, and Support Vector Machines. Ten-fold cross validation is used to validate these models, achieving classification results as high as 99%.
AB - In this paper, the authors evaluate the ability to detect on-body device placement of smartphones. A feasibility study is undertaken with N=5 participants to identify nine key locations, including in the hand, thigh and backpack, using a multitude of commonly available smartphone sensors. Sensors examined include the accelerometer, magnetometer, gyroscope, pressure and light sensors. Each sensor is examined independently, to identify the potential contributions it can offer, before a fused approach, using all sensors is adopted. A total of 139 features are generated from these sensors, and used to train five machine learning algorithms, i.e. C4.5, CART, Naïve Bayes, Multilayer Perceptrons, and Support Vector Machines. Ten-fold cross validation is used to validate these models, achieving classification results as high as 99%.
KW - Enhanced Contextual Awareness
KW - Machine Learning
KW - Multi-Sensor Fusion
KW - Smartphone Placement
UR - http://www.scopus.com/inward/record.url?scp=84929492549&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2014.6944424
DO - 10.1109/EMBC.2014.6944424
M3 - Conference contribution
C2 - 25570792
AN - SCOPUS:84929492549
T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
SP - 3691
EP - 3694
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Y2 - 26 August 2014 through 30 August 2014
ER -