مشروع الانظمة العلاجية
TRANSCRIPT
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.
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