Monitoring of psycho-physiological Processes Based on Skin Conductivity , Heart Rate and Skin Temperature

Abstract— Happens to humans a lot of psychological

changes resulting from exposure to situations get him daily or

as a result of the actions that carried out by his activity and

his thinking, and these changes are known as "stress".

Human exposed to the stress, making the nerve impulses

carrying sense to stimulate many glands, including the sweat

glands in the skin layers, causing an increase in secretions of

these glands of sweat that reaches the skin surface through

ducts , influenced by the conductivity of the skin because of

sweat. In addition; many vital signs affected by the secretions

of various glands throughout the body resulting from

psychological status, such as increased heart rate and skin

temperature.

The idea of this project is to design a device that has the

ability to measure various physiological signals, which are

closely linked with symptoms of stress, such as Galvanic Skin

Response (GSR), Heart Rate (HR), and Skin Temperature

(SKT), are measured by different types of medical sensor

equipment and process by Arduino Microcontroller.

Environmental variables and psychological measured

will be made to the microcontroller, such as a microcontroller

(Arduino) for the purpose of data processing, and then take

deliberate and targeted samples for tests and taking different

values and analyzed for "specific stress range" in each case

to facilitate the diagnosis in the future. So, it is crucial to track

their stress levels early to avoid health problems and

complications. The purpose of this project was to build a

reliable and effective device to measure stress level easily.

I. INTRODUCTION

Stress is one of the major factors that contributes to physical

and physiological health problems. Stress may affect our main

body systems such as nervous system, musculoskeletal system,

respiratory system, cardiovascular system, endocrine system,

gastrointestinal system and reproductive system. If one of these

body systems shut down or not working properly due to stress,

human daily activities will be get influence too, Hence There is a

connection between stress and illness.

Unfortunately, stress disease is one of the most complex

diseases in therapy, and most of the routes in the diagnosis and

knowledge of the level of tension takes a lot of time, according to

public statistics, one person in every four people suffering from

anxiety in a period of his life, so the early detection of stress

protects persons acute complications.

II. BACKGROUND AND MOTIVATION

The treatment of psychiatric patients and people with stress

needs to sessions of treatment and long to identify and diagnose

the disease, and most people with stress do not realize the

seriousness of its complications, leading to acute stress.

Add modern technology helps in detecting the level of stress

that would help in the identification of associated with psychiatric

illnesses, and this will help the doctor to assess the psychological

state of the patient and therefore easier to reduce risks.

It will be invented a way to measure a reliable, easy to use,

reduce the financial and physical burden on the patient and also get

the results in a few minutes, as well as all that, will be to collect

and analyze the results in order to reach the range for stress

acceptable and range is unacceptable which is harmful to the

patient's health, so this project is a research project and applied.

The main objectives of this project can be summarized as

follow:-

Development a suite of a wearable physiological sensors

for affective responses from physiological signals,

namely, GSR, HR, and SKT.

Design the sensors with ability to measure, store, and

transmit physiological parameters using low-power

wireless Bluetooth communication.

Processing final results of the physiological signals to

find out range unacceptable stress by taking samples and

statistical analysis.

Help patients to speed up the process of diagnosis and

thus speeding up the treatment and reduces the risk of

complications of severe psychological.

III . Literature Review and Related Work

Stress is defined as a common physical reaction to events

that cause people to feel threatened and caused their emotional

state to become imbalanced [1]. An optimum stress level allows a

person to work at their optimum level of performance. However,

stress stops being positive and starts giving negative impact on

health, emotion and even daily activities. Figure 1.1 illustrates the

relationship of stress level and performance.

Figure 1.1:Stress curve [1].

Stress detection system (SDS) has been designed in previous

works for various applications such as measuring soldier stress,

computer users stress, automobile drivers stress, and so on. So,

different methodologies and systems have been designed by

researchers to cope for the different purposes of research.

For example, Alberto de S. S. et al. proposed a noninvasive

SDS with heart rate (HR) and galvanic skin response (GSR) as

physiological signals input [2]. A database is needed for training,

validating and testing the proposed system and it is acquired by

performing a set of psychological experiments with the purpose

of inducing stress in individuals. The researchers successfully

implemented the 7 proposed system with fuzzy logic and they

recorded 99.5% accuracy by acquiring HR and GSR data with 10-

second measurement and 90% if the period is reduced to 3 to 5

seconds.

Singh M. et al. proposed the use of four main parameters

and their derivatives, namely, Heart rate (HR), galvanic skin

response (GSR), electromyogram (EMG), and respiration rate

(RR) [3]. These four parameters are selected based on their

properties namely non-invasiveness when being acquired and

because their variation is strongly related to stress stimuli [4].

Sun F. T. et al. presented an activity-aware mental stress

detection scheme. The researchers obtained electrocardiogram

(ECG), galvanic skin response (GSR), and accelerometer data

from 20 participants [5]. The purpose of accelerometer in this

case is to measure the proper acceleration of participants across

three daily common activities: sitting, standing, and walking.

Mental stress classification for 10-fold cross validation obtained

92.4% accuracy with the aid of activity information derived from

the accelerometer classification and 80.9% accuracy for between-

subjects classification.

Shi Y. et al. used SDS to study both mental and physical

stress. For automatic stress detection, the researchers trained

personalized models using Support Vector Machines (SVMs).

Experiments on the recorded data show that the model can achieve

good precision and high detection rate. In this work,

Electrocardiogram (ECG), Galvanic Skin Resistance (GSR),

Respiration Rate (RR), Temperature are measured with different

sampling frequency [6].

IV. METHADOLOGY

In this project a portable noninvasive stress level detector

will be designed and implemented, this device will read the

physiological signals; namely, Galvanic Skin Response (GSR),

Heart Rate (HR), and Skin Temperature (SKT), that are low cost,

low power, and non-intrusive to be embedded on a wristband.

These wearable sensors will be capable of long-term physiological

monitoring, which is important when dealing with the treatment

and management of many chronic illnesses, neurological disorders,

and mental health issues. Examples include: epileptic seizures,

autism spectrum disorders, depression, drug addiction and anxiety

disorders.

V . ANALYISIS

This section gives a detail description of the system

operation; The figure below illustrates the general block diagram

that is composed of two main parts; sensing part and processing

part. The sensing part contains galvanic skin response(GSR)sensor

to measure the electrical conductance of the skin, which varies

with its moisture level, and heart rate sensor (HR) to determine the

number of heart rate per minute, also, the skin temperature sensor

(SKT) that reading the skin temperature, this variable entered into

the accounts of the level of tension in the body.

Figure : Main Block Diagram for the System.

The following parts describe the principle of operation of

each stage.

Galvanic skin response (GSR) sensor Design

In this project a new non-invasive method to measure Skin

Conductance (SC) by Sensor that provides information about

sweat gland activity on the hand.

The Figure below demonstrates the block diagram of the

system used to acquire the GSR data though electrical signals

from the GSR sensor.

Block diagram for GSR circuit

Wheatstone bridge

Figure below shows the circuit that use a Wheatstone The

purpose of using Wheatstone bridge observation is the change in

skin resistance and thus the conductivity of the skin, in order to

get different readings each case.

Wheatstone bridge circuit

In the pervious , R3 is used for calibration and GSR

electrodes represents the resistance of the skin resistance. When

the voltage (v=5), then the voltage difference between two

terminals can be calculated by the below Equation .

Vd=V ( GSRGSR+R1

−R3

R2+R3)

Voltage Follower

One of the problems expected to occur is non-arrival of electric

current to the rest of the circuit parts of required current. So to

avoid these problems, it has been used voltage follower or Buffer

which has a voltage gain of 1, with an ideal op amp gives simply:

Vout = Vin

Because the op amp has such high input impedance, it draw

very little current..

Voltage Followers circuit

Differential Amplifier

The purpose of the differential amplifier is to amplify the

difference between two input terminals.

Differential Amplifier circuit

The differential amplifier voltage is shown in the below

equation:

V O=¿

Only the difference will get amplified 24 times to be detect.

Low Pass Filter

The low pass filter enable us to filter out unwanted signals it

allow low frequency signals from 0Hz to the cut-off frequency of

5Hz,.such that at high frequencies C1 and C2 act as short

circuits.

Low-Pass Filter circuit

FC can be calculated by using R8, R9, C1 and C2 as expressed in

below equation :

FC=1

2π √R8 R9C1C2

Let C1= 22nF, so C2was calculated from equation C2 = 150nF :

And R8, R9 is: R8 = 167.88 KΩ & R9= 1887.9 KΩ

Heart Rate Sensor Design

The heart rate sensor, will be used to monitor the rate of heart-

beat of the patient. by choose Photoplethysmography technique. This

technique depends on the change of blood volume in the finger.

The block diagram shown in the below Figure is built to

illustrate the basic design of the proposed heart rate system.

Block diagram for HR Sensor

Infra-Red Transceiver

The Photoplethysmography technique, depends on the

amount of infra-red (IR) lights that reflected from the finger.

LED and phototransistor are arranged in the opposite direction

to sense the reflective IR-beam from the changes in arterial

blood volume in the finger, as shown in the below figure.

HR Sensor

Transmittance and reflectance are two basic types of

Photoplethysmography. The light is emitted into the tissue and

the reflected light is measured by the detector.

The following circuit showed in below figure, the

ON/OFF control scheme for the infra-red light source.

IR transceiver circuit

The transistor (2N3940) is chosen to deliver a constant

current for IR- LED. the forward current (IF) at which the LED

will transmit the desired wave length is at 20mA. This current

is delivered by the transistor as collector current IC=20mA . with

DC gain current (β) is equal 60the base current (IB) is:

I β=I c

β= 20

60∗1000=0.33 mA

The resistance R3 that generates the desired Iβis:

R3=V cc−vBE

I B,The base-emitter voltage (VBE) and VCC are

0.8V and 5V respectively ,hence the value of R3 equal 12.7KΩ

Band Pass Filter and Non-inverting Amplifier

we need an amplifier and filter circuits to boost and clean the signal. In Stage I instrumentation as shown in the Figure 4.10,the signal is first passed through a passive (RC) high-pass filter (HPF) to block the DC component .

Band Pass Filter circuit

The cut-off frequency of the HPF is 0.5Hz,then FC can be expressed

in equation : FC=1

2π R4 C3

Let C3 =4.7μF, thenR4=1

2π f c C3=68KΩ

The output from the HPF goes to low-pass filter (LPF),with cut-off

frequency is 3.4Hz, thenFC=1

2π R6C4

Let C4 =100nF, thenR6=1

2 π f c C4=470KΩ

The Op-amp operates in non-inverting mode and has gain 48,

gain can be calculated by equationG=1+R6

R5

the negative input of the Op-amp is tied to a reference voltage (Vref) of

2.0V that is generated using a zener diode, as the below figure

At the output is a potentiometer (P1) that acts as a manual gain control.

The second stage also consists similar HPF and LPF circuits as

shown in the below Figure The two-steps use amplified and filtered signal

is now fed to a third Op-amp, which is configured as a non-inverting

buffer with unity gain.

Comparator

The output of the comparator goes high. Thus, this arrangement

provides an output digital pulse synchronous to heart beat, which

enable the microcontroller to count heartbeat.

Skin Temperature Design

will be used in this project to monitor skin temperature of

the patient.

so the sensor of this type NTC thermistor, and also non-linear,

and it must be converted to linear, and we note of the curve, if it

was taken a specified range, the change in this range will be

linearly, the following Figure illustrates range specified where

be the change of resistance with temperature linearly.

The following block diagram built to illustrate the basic design of the

proposed system.

The skin temperature sensor value depending upon the temperature of

the body . so,The sensor resistance will varied as the temperature is

varied linearly, therefore, the sensor needs a calibration by potentiometer

at a temperature equal to 18 c, the output voltage (Vref) equal 3.33 volt

at by controlling the variable resistance (R3), thus the result of (Vref -

sensor) equal zero .

Voltage Follower

the importance of voltage follower to ensure that the current will reach

for the circuit parts rest fully and properly without problem.

Arduino

The result we have obtained from difference between Vref and Vsensor is

fixed equal 0.05 volt between each temperature degree that appear in the

curve shown in the following Figure .

Now, the relationship has become clear between temperature

and voltage difference, and thus build a linear equation of the

fourth degree, it has been the resulting equation after the

introduction of voltage values at each temperature ( C )as

follows:

C=a V 4+bV 3+cV 2+dV + fC: Temperature , V: Voltage difference that taken from the skin Where a=1.0245 ×10−14 , b=−2.16 ×10−14 ,c=1.911× 10−14 , d = 20 , f = 18.

VI. RESULTS

52 samples distributed to 38 sample for males and 14 for females.

Heart rate output on LCD

GSR output on LCD

SKT output on LCD

8

Based on these results, the resulting readings were divided into levels

High, Medium and Low

VII. CONCLUSION

As a conclusion, a prototype of stress detector has been

successfully developed. Based on the results obtained from the

project, it showed that the project achieved the proposed objective.

Heart rate, GSR and body temperature measurement can be monitored

through LCD display.

In conclusion, there are a few groups of people which are in

additional danger when they are in stressful conditions and a stress

detection system (SDS) can help to prolong their health sensor

handmade GSR sensor and Heart Rate Sensor is implemented with

the device is portable and user friendly. The visual output peripherals

also make the overall system more attractive and useful. By building a

stand-alone stress detector, people can use it to monitor their stress

level easily and understand what stressor cause the stress problem.

Also conclude when measuring psychological and heart rate of a

person leading to change his style if that condition is in danger and

thus protect himself from the risk might get him,and the main

advantages of this noninvasive system are fast and user-friendly

measurement.

VIII.ACKNOWLEDGMENT We would like to thank Palestine Polytechnic University, College of

Engineering, and Electrical Engineering Department. Thanks from

our hearts for all support and for this worthy learning environment.

Also thanks to the head of hopefulness, our parents.

We would like to thank everybody shared in success of this work

either by suggestion, directives, or tips. Thanks to Dr.

Ramziqawasmeh for their great efforts in supervision, suggestion, and

providing experience to accomplish this work. Also we want to thank

both Eng. Fida’aAlja’fra and Eng. ShehdaZahda For all helps and

worthy suggestions and tips to accomplish this project.

REFERENSES

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workplace-q- nueroscientist/ .

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[3] Singh, M. and Abdullah Bin Queyam. Stress Detection in Automobile Drivers using Physiological Parameters: A Review. International Journal of Electrical Engineering. 2013. 5:1-5.[4] Healey, J. A. and Picard, R. W. Detecting stress during real-world driving tasks using physiological sensors. IEEE Transactions on Intelligent Transportation Systems. 2005. 6(2):156-166.[5] Sun, F. T., Kuo, C., Cheng, H. T., Buthpitiya, S., Collins, P. and Griss, M. Activity-Aware Mental Stress Detection Using Physiological Sensors. Proceedings of 2nd International Conference on Mobile Computing, Applications and Services (MobiCASE). Santa Clara, CA, USA : MobiCASE . 2010. 25–28.[6] Shi, Y., Nguyen, M. H., Blitz, P., French, B., Fisk, S., Torre, F., Smailagic, A., Siewiorek, D. P., Mustafa al' Absi, Ertin, E., Kamarck, T. and Kumar, S. Personalized Stress Detection from Physiological Measurements. International Symposium on Quality of Life Technology. 2010.[7] Ro BI, Dawson TL. The role of sebaceous gland activity and scalp micro¯oral metabolism in the etiology of seborrheic dermatitis and dandru . J Investigative Dermatol SP. 2005; 10(3): 194±7. Gabriel S, Lau R W and Gabriel C. The dielectric properties of biologicaltissue: II. Measurements in the frequency range 10 Hz to 20 GHz. Phys. Med.Biol. 1996; 41: 2251–69.

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