Human Activity Dataset Generation - Smartphone-Based Human Activity Recognition - page 56

online as a research resource. The data have been collected from one experiment
which is thoroughly described in the following section.
4.2.1 Smartphone Selection
Finding a suitable smartphone to perform HAR involves the evaluation of the up-to-
date devices in themarket following the selection criteria listed in Sect. 2.4.1 , inwhich
hardware, sensors and software are the primary elements to be considered. Also, other
aspects such as price, market of available brands and potential future distribution of
applications were taken into account. However, by the time this selection process was
done (2011), the smartphones with the required embedded sensors were very limited,
as well as their specifications regarding speed and direct access to the sensors through
their OS. This motivated the assessment of only the available high-end devices at that
time. As it is known with the accelerated growth of current technologies, it was just a
matter of 2 years to discover that now in almost every mid- and high-end smartphone
in the market the required sensors and hardware with even higher specifications were
available. This finding expands the range of applications of the developed approaches
of this work to a greater group of devices.
4.2.1.1 Up-to-date Smartphones
For the selection of the smartphone regarding sensor type, we took as a reference point
an already available inertial sensor, the 9X2 (Rodríguez-Martín 2010 ), which had
already demonstrated its applicability in the detection of various human motor disor-
ders in people with disabilities (e.g. PD patients) (Rodríguez-Martín et al. 2013a , b ).
It is internally composed of three triaxial sensors: an accelerometer, a gyroscope
and a magnetometer. It collects inertial sensor data that can be stored on a microSD
memory card or wirelessly transmitted to a terminal via Bluetooth. We expected to
find smartphones with those minimum characteristics. Figure 4.2 shows an image of
the sensor.
Table 4.1 presents a comparison of the 9X2 sensor with two high-end smartphone
candidates. It includes their characteristics regarding hardware and software. The
embedded accelerometer and gyroscope smartphone specifications outperform the
ones from the reference inertial sensor regarding speed and operation ranges, mak-
ing them potentially suitable for their application in HAR. However, even though the
specified frequencies are provided by the devices datasheets, the net frequency of
these inertial sensors is limited by the smartphones OS which regulates their opera-
tion speed and battery consumption. It is around 100 Hz and it can vary depending
on the OS load, but it is sufficient to properly capture human body motion accord-
ing to (Karantonis et al. 2006 ) (refer to Sect. 4.3.2 ). Regarding memory and Central