Prototype Design

The methodology is based in the creation and design of several prototypes and architectures in order to measure and compare the performance of every one.

The first prototype was based in the board Arduino Uno R3 and the e-Health Shield as the hardware components.

The software used was the Arduino IDE version 1.0.6 and the e-Health library version 2.2 because due a compatibility problem the code for the e-Health Sensor Platform cannot be compiled with the last version of Arduino IDE 1.6.1. or if the compilation did  work, some sensors especially the pulsioximeter sensor return wrong values.

Also for the first prototype was used the library ChibiOS/RT, an embedded real time operative system  in order to run concurrently two or more process in the Arduino CPU and try to get different sample frequency for every sensor.

With the first prototype working was analysed the code of the e-Health library for each sensor.

Pulsioximeter Sensor

This pulsioximeter is based in an infra-red sensor adapted to connect to e-Health board. The sensor has a display led (light emitting diode) screen which is connected pin by pin to the Arduino using a wire to the board. The sensor can get two biometric variables: SPO2 that is the level in percentage of the blood oxygen and BPM that is the bit per minute or heart frequency.

The code related to pulsioximeter is in the file eHealth.cpp of the library lines 515-545, in this code is possible to see that the values of the sensor are obtained measuring the level of every led in the display then for the lecture is necessary to read all the leds to get two variables. Also is possible to read in the line 537 that the pulsioximeter has a minimal sample frequency of 300 microseconds because the code apply a 300 microseconds delay between the lectures of every leds. And then apply an addition formula to obtain the values.

Galvanic Skin Response (GSR) Sensor

The GSR sensor get the measuring of the electrical conductance of the skin, which varies with the moisture level. This is of interest because the sweat glands are controlled by the sympathetic nervous system, so moments of strong emotion, change the electrical resistance of the skin. Skin conductance is used as an indication of psychological or physiological arousal, The Galvanic Skin Response Sensor (GSR - Sweating) measures the electrical conductance between 2 points, and is essentially a type of ohmmeter (e-Health Platform documentation).

The conductivity of the skin is measured at fingers of the palm. When a high level of sweating take place the electrical resistance drops down.
The sensor is connected to the Analog A2 pin of Arduino. This pin is the sensor value and convert all the input to an analogue value between 0 and1023.

With this sensor is possible obtain three variables

• SkinConductanceVoltaje: Defined as (sensor value * 5.0)/1,023 with a minimal sample frequency of 2 milliseconds
• SkinConductance: Defined as 2((SkindConductanceVoltaje – 0.5) / 100,000)
• SkinResistance: Defined as 1/conductance with a minimal sample frequency of 4 milliseconds

Methodologies

Due to the nature of the problem the methodology will be based on an exploration of different hardware configurations with benchmarks for each of these configurations or prototypes using one, two or three sensors at the same time.

With each prototype will be analysed different software libraries and programming techniques in order to obtain maximum performance.

Quantitative data will be obtained to compare each prototype and the pros and cons of each will be exposed. These prototypes will be based on the Arduino platform or similar platforms such as Raspberry Pi or Intel Galileo.

The highest performance prototype will be adjust and modified in order to get more than 2 biomedical signals with suitable sampling frequency for use in testing and research. Different types of sampling techniques will be analysed to establish one that be securely, stable and reliable.

Problem Statement

The e-Health Sensor Platform is presented as a very good option for research and study of human emotions but early tests have shown that the platform sometimes is unstable and not very reliable.

The objective of this thesis is to test the platform, modify and develop the necessary software to make it more stable and reliable for future studies related to Affective Computing specially oriented in the field of learning but not restricted only to this area.

The work includes testing the e-Health Sensor Platform with different hardware architectures to define which presents the best performance and obtaining more than 2 or more biomedical signals simultaneously.

Background

The human being is emotional, all our activities are influenced by our personal emotions. When we learn something new, when we talk with our partners, when we make business or when we take decisions our emotions are influencing and probably affect the final result.

For that reason the study of emotions is interesting and his outcomes are applied to several areas like learning, marketing or health (Harley, J. M., Bouchet, F., Hussain, S., Azevedo, R., & Calvo, R. 2014).

The study of the emotions using electronic devices has increased last years, there are many papers related to this topic called Affective Computing (Calvo & D’Mello. 2010).

Affective Computing is all related to study the emotions using tools like computers or other electronic devices. One of the problems in this area is the high cost of the sensors used to collect the electrical signals in order to detect emotional changes (Harley, J. M., Bouchet, F., Hussain, S., Azevedo, R., & Calvo, R., 2014).

With the rise of open source movement in both hardware and software have been developed interesting projects that lower costs and give access to new technologies and measuring sensors at reasonable prices (Santos Ribeiro A.,Salvado D., Evans G., Soares Augusto J. and Ferreira H. 2014).

Arduino is one of these platforms, basically it is a prototyping board provided with a micro controller and developed with an open architecture. This board was designed to make it possible to add "Shields" and extend its functionality.

A shield very interesting for the study of emotions is the e-Health Sensor Platform. The e-Health was designed by the company Cooking Hacks to allow researchers, developers and artists get measurements and data for biomedical research, testing or fun. This platform allows to get biomedical variables such as temperature, electrocardiograms, galvanic skin response or blood pressure, however this is not medically certified.