Authors:
Pekka Siirtola
;
Heli Koskimäki
and
Juha Röning
Affiliation:
University of Oulu, Finland
Keyword(s):
Human Activity Recognition, Accelerometer, Open Data Sets, Cross-validation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Cardiovascular Imaging and Cardiography
;
Cardiovascular Technologies
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Signal Processing
;
Software Engineering
;
Theory and Methods
Abstract:
In this article, it is studied how well inertial sensor-based human activity recognition models work when
training and testing data sets are collected in different environments. Comparison is done using publicly open
human activity data sets. This article has four objectives. Firstly, survey about publicly available data sets
is presented. Secondly, one previously not shared human activity data set used in our earlier work is opened
for public use. Thirdly, the genaralizability of the recognition models trained using publicly open data sets
are experimented by testing them with data from another publicly open data set to get knowledge to how
models work when they are used in different environment, with different study subjects and hardware. Finally,
the challenges encountered using publicly open data sets are discussed. The results show that data gathering
protocol can have a statistically significant effect to the recognition rates. In addition, it was noted that often
publicly open
human activity data sets are not as easy to apply as they should be.
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