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2 BACKGROUND
Several authors have delved into the problem of mak-
ing biosignal acquisition hardware tools accessible to
anyone. One of the most comprehensive work known
to date is the Open EEG Project
1
. This is a commu-
nity driven effort to make affordable hardware and
software tools available for anyone with interest in
working with Electroencephalography (EEG), how-
ever it has been mostly focused on EEG data and is
supported by technologies currently outdated.
With the advent of open source hardware plat-
forms such as the Arduino (Banzi, 2009; Buechley
and Eisenberg, 2008) or Raspberry Pi, efforts have
been made to extend their capabilities to biosignal
data acquisition. OLIMEX
2
created a low-cost sen-
sor shield for Electrocardiography (ECG) and Elec-
tromyography (EMG), Advancer Technologies has
devised the MuscleSensor
3
for EMG; the Pulse Sen-
sor
4
for Blood Volume Pulse (BVP) data acquisition
is yet another example. All of these are focused on
very specific modalities and limited to the actual ana-
log front-end for the sensors.
The main advantage of the Arduino-based ap-
proaches is the extremely low cost, given that from
$25 anyone can buy an Arduino board. Nonetheless,
they are designed to deal with very simple require-
ments for example in terms of sampling rate accuracy
and tolerance to noise. Previous work from our group
has actually attempted to use an Arduino Pro Mini
board for ECG data acquisition, however, experimen-
tal results clearly demonstrated several of these short-
comings (Alves et al., 2013).
More recently, Libelium
5
has proposed a multi-
modal sensor platform for e-Health, which includes
sensors for BVP, Blood Oxygenation (SpO2), res-
piration, temperature, ECG, glucose, Accelerome-
try (ACC), Electrodermal Activity (EDA), and blood
pressure. The advantage of this platform is the fact
that it integrates multiple sensors with embedded pro-
cessing algorithms. Still, most of the sensors do not
provide access to raw data, all the sensors are bundled
as a single unit (providing low flexibility for custom
hardware configurations), and at ≈$500 it is not af-
fordable for everyone.
Despite the work developed so far, the physiolog-
ical computing community is still lacking adequate
hardware frameworks, leading our group to develop
preliminary work on hardware for multimodal biosig-
1
http://openeeg.sourceforge.net/doc/
2
http://www.olimex.com/SHIELD-EKG-EMG.html
3
http://www.advancertechnologies.com/
4
http://pulsesensor.com/
5
http://www.libelium.com/130220224710/
nal acquisition (Guerreiro et al., 2013). As high-
lighted in our previous work, further research on the
analog front-end of the voltage differential sensors,
namely the ECG and EMG, was needed, and several
usability issues related with the form factor ultimately
limited the scope of application of our initial proposal.
In this paper we address the main problems found
in the state-of-the-art, and present a completely re-
vised approach to BITalino, which has resulted in
the first low-cost, all-in-one, flexible and easy-to-use
hardware framework for physiological computing.
3 ANATOMY OF A BITALINO
3.1 Design Principles
We devised BITalino as an all-in-one ”Credit Card”
form factor that integrates multiple measurement sen-
sors for bioelectrical and biomechanical data acqui-
sition. The digital back-end is supported by a con-
trol block based on the ATmega328P microcontroller,
a power management block, and a communication
block that uses a Class II Bluetooth v2.0 module for
wireless data transfer to a base station (e.g. com-
puter, mobile phone, etc.). Two auxiliary connectivity
blocks introduced in the board enable RJ22 plugs to
be added to the device. The main specifications are
summarized in Table 1.
Table 1: BITalino specifications.
Sampling Rate 1, 10, 100 or 1000 Hz
Analog Ports 4 input (10-bit) + 2 input (6-bit)
Digital Ports 4 input (1-bit) + 4 output (1-bit)
Data Link Bluetooth (range up to 10m)
Actuators LED
Sensors EMG; ECG; EDA; ACC; LUX
Battery 3.7 V Lithium Ion
Weight 30 g / 1.06 oz
Size 105x60 mm / 4.13x2.36 in
By default, the system comes as a single board,
with its onboard sensors pre-connected to analog and
digital ports on the control block. Nonetheless, the
control, power, and communication blocks, as well
as the firmware are completely general purpose, en-
abling people to use only the digital back-end of the
BITalino with their own custom sensor and actuator
designs. Furthermore, each individual block can be
physically detached from the main board, allowing
people to use it in many different ways; in essence,
this architecture enables three configurations:
• Board: BITalino is used with no modifications,
enabling people to simply experiment with the
BITalino:ANovelHardwareFrameworkforPhysiologicalComputing
247