Emotions are an unstoppable and uncontrollable aspect of mental state of human. Some bad situations give
stress and leads to different sufferings. One can’t avoid situation but can have awareness when body feel
stress or any other emotion. It becomes easy for doctors whose patient is not in condition to speak. In that
case person’s physiological parameters are measured to decide emotional status. While experiencing
different emotion, there are also physiological changes taking place in the human body, like variations in
the heart rate (ECG/HRV), skin conductance (GSR), breathing rate(BR), blood volume pulse(BVP),brain
waves (EEG), temperature and muscle tension. These were some of the metrics to sense emotive coefficient.
This research paper objective is to design and develop a portable, cost effective and low power
embedded system that can predict different emotions by using Naïve Bayes classifiers which are based on
probability models that incorporate class conditional independence assumptions. Inputs to this system are
various physiological signals and are extracted by using different sensors. Portable microcontroller used
in this embedded system is MSP430F2013 to automatically monitor the level of stress in computer. This
paper reports on the hardware and software instrumentation development and signal processing approach
used to detect the stress level of a subject.To check the device's performance, few experiments were done in
which 20 adults (ten women and ten men) who completed different tests requiring a certain degree of effort,
such as showing facing intense interviews in office.
Pain and Opioids: damage and danger, mechanism and meaningMark Sullivan
In this presentation, I argue that pain exists more to protect than to inform, so survival implications affect pain processing. The salience and valence of pain are continually adjusted to promote survival. For humans, physical survival depends on social survival, so our brains have evolved to make both physical and social injury painful, with our endogenous opioid system modulating both forms of pain to promote both forms of survival.
EXAMINATION OF THE SKIN CONDUCTANCE LEVEL (SCL) AS AN INDEX OF THE ACTIVITY O...ijbesjournal
This paper displays standardized measurements to examine the skin conductance level (SCL) as an index for the sympathetic nervous system’s activity considering a possible standardization of personal variability. SCL measurements were performed at baseline, Cold-Pressor-Tests and Stroop Tests for 15 subjects and inter- and intra-individual mean SCL values were examined. The logarithmic representation displays a high inter-individual variability, denoted by a high fluctuation range of the absolute values and SCL amplitudes. A standardization of inter-individuality could not be achieved by the applied methods (range correction and z-transformation). For the relative intra-individual comparison of the stress situation to the baseline, a method of correction for the determination of the real effect of sympathetic activation was established. EDA should be combined with other parameters of the ANS for a more precise evaluation of stress situations in the context of changes in blood pressure.
Galvanic Skin Response Data Classification for Emotion Detection IJECEIAES
Emotion detection is a very exhausting job and needs a complicated process; moreover, these processes also require the proper data training and appropriate algorithm. The process involves the experimental research in psychological experiment and classification methods. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. It means that the emotion detection can be done satisfactorily and well performed.
Pain and Opioids: damage and danger, mechanism and meaningMark Sullivan
In this presentation, I argue that pain exists more to protect than to inform, so survival implications affect pain processing. The salience and valence of pain are continually adjusted to promote survival. For humans, physical survival depends on social survival, so our brains have evolved to make both physical and social injury painful, with our endogenous opioid system modulating both forms of pain to promote both forms of survival.
EXAMINATION OF THE SKIN CONDUCTANCE LEVEL (SCL) AS AN INDEX OF THE ACTIVITY O...ijbesjournal
This paper displays standardized measurements to examine the skin conductance level (SCL) as an index for the sympathetic nervous system’s activity considering a possible standardization of personal variability. SCL measurements were performed at baseline, Cold-Pressor-Tests and Stroop Tests for 15 subjects and inter- and intra-individual mean SCL values were examined. The logarithmic representation displays a high inter-individual variability, denoted by a high fluctuation range of the absolute values and SCL amplitudes. A standardization of inter-individuality could not be achieved by the applied methods (range correction and z-transformation). For the relative intra-individual comparison of the stress situation to the baseline, a method of correction for the determination of the real effect of sympathetic activation was established. EDA should be combined with other parameters of the ANS for a more precise evaluation of stress situations in the context of changes in blood pressure.
Galvanic Skin Response Data Classification for Emotion Detection IJECEIAES
Emotion detection is a very exhausting job and needs a complicated process; moreover, these processes also require the proper data training and appropriate algorithm. The process involves the experimental research in psychological experiment and classification methods. This paper describes a method on detection emotion using Galvanic Skin Response (GSR) data. We used the Positive and Negative Affect Schedule (PANAS) method to get a good data training. Furthermore, Support Vector Machine and a correct preprocessing are performed to classify the GSR data. To validate the proposed approach, Receiver Operating Characteristic (ROC) curve, and accuracy measurement are used. Our method shows that the accuracy is about 75.65% while ROC is about 0.8019. It means that the emotion detection can be done satisfactorily and well performed.
A Review of ECG signals for Human Emotion Detectionrahulmonikasharma
This article evaluates the present development by means of literature review in determining the association between emotions, mainly worry, and the various physiological signals with special attention on the exclusive patterns of the electrocardiogram or ECG waveform. An initial investigation was carried out to evaluate which aspects in the ECG waveform can be most suitably related with worry, except from those. Hence, it has been observed that emotion identification utilizing particular aspects of ECG is investigated to a lesser degree compared to other physiological reactions like speech signals, skin conductance and temperature, facial expression, heart rate and blood pressure. With the initial investigation, it was further discovered that the T waves levels out consequently and there is some likelihood of P waves.
A NALYSIS OF P AIN H EMODYNAMIC R ESPONSE U SING N EAR -I NFRARED S PECTROSCOPYijma
Despite recent advances in brain research, understa
nding the various signals for pain and pain intensi
ties
in the brain cortex is still a complex task due to
temporal and spatial variations of brain haemodynam
ics.
In this paper we have investigated pain based on ce
rebral hemodynamics via near-infrared spectroscopy
(NIRS). This study presents a pain stimulation expe
riment that uses three acupuncture manipulation
techniques to safely induce pain in healthy subject
s. Acupuncture pain response was presented and
Haemodynamic pain signal analysis showed the presence of dominant channels and their relationship
among surrounding channels, which contribute the fu
rther pain research area.
PERFORMANCE EVALUATION OF VARIOUS EMOTION CLASSIFICATION APPROACHES FROM PHYS...ijaia
This paper aims at evaluating the performance of various emotion classification approaches from psychophysiological signals. The goal is to identify the combinations of approaches that are most relevant for assessing human affective states. A classification analysis of various combinations of feature
selection techniques, classification algorithms and evaluation methods is presented. The emotion recognition is conducted based on four physiological signals: two electromyograms, skin conductivity and respiration sensors. Affective states are classified into three different emotion classes: 2-categoryclass
(Arousal), 3-category-class (Valence) and 5-category-class (Valence/Arousal). The performance of the various combinations of approaches is evaluated by comparing the resulting recognition rates. For all the category-classes, the best results are obtained when considering skin conductivity combined with the respiration signals. Highest rates when fusing all physiological channels resulted when applying the SFS feature selection, the LDA classifier and the normal split evaluation approach, showing a robust combination of approaches leading to good performance.
Analysis of emotion disorders based on EEG signals ofHuman BrainIJCSEA Journal
In this research, the emotions and the patterns of EEG signals of human brain are studied. The aim of this research is to study the analysis of the changes in the brain signals in the domain of different emotions. The observations can be analysed for its utility in the diagnosis of psychosomatic disorders like anxiety and depression in economical way with higher precision.
Stress detection during job interview using physiological signalIJECEIAES
A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through electrocardiogram (ECG) signals. The Augsburg biosignal toolbox (AUBT) dataset was used to obtain the state-of-art results. Only five selected features are significant to the stress level were fed into neural network multi-layer perceptron (MLP) as the optimum classifier. This stress detection achieved an accuracy of 92.93% when tested over the video interview dataset of 10 male subjects who were recording the video resume for the analysis purposes.
Design and development of a method for detecting sleep roll-over counts usin...IJECEIAES
Sleep plays an important role as it helps human body to rejuvenate, boosts mental function and manage stress. Sleep is restorative function which enhances muscle growth, repairs tissues, maintains health and make physical appearance look or feel better. The lack of sleep in human body can increase the risk of diseases which are asthma, diabetes, depression. For healthy physiological function, sleep is essential and has strong relation to mental condition. Easy way of sleep management is considered for maintaining good mental health. Numerous scientists, doctors and researchers have proposed various ways to monitor sleep, some of those best tests are polysomnography test and actigraphy test. However, taking sleep test covering the whole body with wires and electrodes which is polysomnography test is uncomfortable for patients, and sensors used for different approaches like this are costly and often require overnight treatment and expert monitoring in clinics. Therefore, easy way of detecting roll-over movements which is convenient for patients to wear is proposed. Accelerometer ADXL335 sensor is taped on socks during sleep which is comfortable for patients to wear and do not cause any inconvenience during sleep. Algorithm is proposed to read the dataset and count the roll-over during the sleep based on threshold. Resulting the number of roll-over detected during a sleep period.
Machine learning-based stress classification system using wearable sensor dev...IAESIJAI
University students often become victims of high-stress levels due to the highly competitive work environment. Unmonitored stress levels in students can inflict severe physiological health problems. This work aims to build a stress classification framework using wearable sensor devices to predict mental stress levels for undergraduate engineering students. It comprises a study to collect a data set of 23 university students using wearable devices for four physiological signals, i.e., electroencephalogram (EEG), electrodermal activity (EDA), skin temperature (SKT), and heart rate (HR), when the students perform the montreal imaging stress task (MIST) for the mental workload. The machine learning models proposed in this work help classify stress into three levels: rest, moderate, and high. The models achieve a classification accuracy of 99.98% using the EEG signals’ time-frequency domain features and an accuracy of 99.51% using the EDA, HR, and SKT signals. The proposed models achieve better scores than all the previous studies on stress classification, using EEG signals and EDA, HR, and SKT signals. This study is novel since it also demonstrates the applicability and proficiency of wearable sensor devices in developing accurate stress classification models to help build real-time stress monitoring systems.
Stress detection and relief using wearable physiological sensorsTELKOMNIKA JOURNAL
The aim of the paper was to present a concept and to develop a prototype in the form of a cap
which uses a combination of physiological sensors that work in concert to not only detect high stress levels
in a person during his daily routine and working env ironment, but also initiate immediate relief measures.
The parameters used to detect stress were compared with resting heart rate and brainwave activity to
determine whether the person wearing the cap is in a stressed condition. Stress alleviation was achieved
using Auditory Stimulation and a Scalp Massage. Early detection of stress and its immediate remedy or
reduction can play an important role in preventing mental health disorders. In order to make the product
cost effective, the concept of sensing optimum amount of data to trigger a remedial action was given more
importance than extensive data collection using large number of sensors. Integrating an IOT device will
further allow information to be recorded and transmitted to a caregiver/doctor to prescribe remedial action
and thus prevent the condition to take a pathological form or get complicated. The detailed analysis of the
collected data can help people identify the precipitating factors for stress and thus aims at reduction of
stress related illnesses.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
A Review of ECG signals for Human Emotion Detectionrahulmonikasharma
This article evaluates the present development by means of literature review in determining the association between emotions, mainly worry, and the various physiological signals with special attention on the exclusive patterns of the electrocardiogram or ECG waveform. An initial investigation was carried out to evaluate which aspects in the ECG waveform can be most suitably related with worry, except from those. Hence, it has been observed that emotion identification utilizing particular aspects of ECG is investigated to a lesser degree compared to other physiological reactions like speech signals, skin conductance and temperature, facial expression, heart rate and blood pressure. With the initial investigation, it was further discovered that the T waves levels out consequently and there is some likelihood of P waves.
A NALYSIS OF P AIN H EMODYNAMIC R ESPONSE U SING N EAR -I NFRARED S PECTROSCOPYijma
Despite recent advances in brain research, understa
nding the various signals for pain and pain intensi
ties
in the brain cortex is still a complex task due to
temporal and spatial variations of brain haemodynam
ics.
In this paper we have investigated pain based on ce
rebral hemodynamics via near-infrared spectroscopy
(NIRS). This study presents a pain stimulation expe
riment that uses three acupuncture manipulation
techniques to safely induce pain in healthy subject
s. Acupuncture pain response was presented and
Haemodynamic pain signal analysis showed the presence of dominant channels and their relationship
among surrounding channels, which contribute the fu
rther pain research area.
PERFORMANCE EVALUATION OF VARIOUS EMOTION CLASSIFICATION APPROACHES FROM PHYS...ijaia
This paper aims at evaluating the performance of various emotion classification approaches from psychophysiological signals. The goal is to identify the combinations of approaches that are most relevant for assessing human affective states. A classification analysis of various combinations of feature
selection techniques, classification algorithms and evaluation methods is presented. The emotion recognition is conducted based on four physiological signals: two electromyograms, skin conductivity and respiration sensors. Affective states are classified into three different emotion classes: 2-categoryclass
(Arousal), 3-category-class (Valence) and 5-category-class (Valence/Arousal). The performance of the various combinations of approaches is evaluated by comparing the resulting recognition rates. For all the category-classes, the best results are obtained when considering skin conductivity combined with the respiration signals. Highest rates when fusing all physiological channels resulted when applying the SFS feature selection, the LDA classifier and the normal split evaluation approach, showing a robust combination of approaches leading to good performance.
Analysis of emotion disorders based on EEG signals ofHuman BrainIJCSEA Journal
In this research, the emotions and the patterns of EEG signals of human brain are studied. The aim of this research is to study the analysis of the changes in the brain signals in the domain of different emotions. The observations can be analysed for its utility in the diagnosis of psychosomatic disorders like anxiety and depression in economical way with higher precision.
Stress detection during job interview using physiological signalIJECEIAES
A job interview can be challenging and stressful even when one has gone through it many times. Failure to handle the stress may lead to unsuccessful delivery of their best throughout the interview session. Therefore, an alternative method which is preparing a video resume and interview before the actual interview could reduce the level of stress. An intelligent stress detection is proposed to classify individuals with different stress levels by understanding the physiological signal through electrocardiogram (ECG) signals. The Augsburg biosignal toolbox (AUBT) dataset was used to obtain the state-of-art results. Only five selected features are significant to the stress level were fed into neural network multi-layer perceptron (MLP) as the optimum classifier. This stress detection achieved an accuracy of 92.93% when tested over the video interview dataset of 10 male subjects who were recording the video resume for the analysis purposes.
Design and development of a method for detecting sleep roll-over counts usin...IJECEIAES
Sleep plays an important role as it helps human body to rejuvenate, boosts mental function and manage stress. Sleep is restorative function which enhances muscle growth, repairs tissues, maintains health and make physical appearance look or feel better. The lack of sleep in human body can increase the risk of diseases which are asthma, diabetes, depression. For healthy physiological function, sleep is essential and has strong relation to mental condition. Easy way of sleep management is considered for maintaining good mental health. Numerous scientists, doctors and researchers have proposed various ways to monitor sleep, some of those best tests are polysomnography test and actigraphy test. However, taking sleep test covering the whole body with wires and electrodes which is polysomnography test is uncomfortable for patients, and sensors used for different approaches like this are costly and often require overnight treatment and expert monitoring in clinics. Therefore, easy way of detecting roll-over movements which is convenient for patients to wear is proposed. Accelerometer ADXL335 sensor is taped on socks during sleep which is comfortable for patients to wear and do not cause any inconvenience during sleep. Algorithm is proposed to read the dataset and count the roll-over during the sleep based on threshold. Resulting the number of roll-over detected during a sleep period.
Machine learning-based stress classification system using wearable sensor dev...IAESIJAI
University students often become victims of high-stress levels due to the highly competitive work environment. Unmonitored stress levels in students can inflict severe physiological health problems. This work aims to build a stress classification framework using wearable sensor devices to predict mental stress levels for undergraduate engineering students. It comprises a study to collect a data set of 23 university students using wearable devices for four physiological signals, i.e., electroencephalogram (EEG), electrodermal activity (EDA), skin temperature (SKT), and heart rate (HR), when the students perform the montreal imaging stress task (MIST) for the mental workload. The machine learning models proposed in this work help classify stress into three levels: rest, moderate, and high. The models achieve a classification accuracy of 99.98% using the EEG signals’ time-frequency domain features and an accuracy of 99.51% using the EDA, HR, and SKT signals. The proposed models achieve better scores than all the previous studies on stress classification, using EEG signals and EDA, HR, and SKT signals. This study is novel since it also demonstrates the applicability and proficiency of wearable sensor devices in developing accurate stress classification models to help build real-time stress monitoring systems.
Stress detection and relief using wearable physiological sensorsTELKOMNIKA JOURNAL
The aim of the paper was to present a concept and to develop a prototype in the form of a cap
which uses a combination of physiological sensors that work in concert to not only detect high stress levels
in a person during his daily routine and working env ironment, but also initiate immediate relief measures.
The parameters used to detect stress were compared with resting heart rate and brainwave activity to
determine whether the person wearing the cap is in a stressed condition. Stress alleviation was achieved
using Auditory Stimulation and a Scalp Massage. Early detection of stress and its immediate remedy or
reduction can play an important role in preventing mental health disorders. In order to make the product
cost effective, the concept of sensing optimum amount of data to trigger a remedial action was given more
importance than extensive data collection using large number of sensors. Integrating an IOT device will
further allow information to be recorded and transmitted to a caregiver/doctor to prescribe remedial action
and thus prevent the condition to take a pathological form or get complicated. The detailed analysis of the
collected data can help people identify the precipitating factors for stress and thus aims at reduction of
stress related illnesses.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
1. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
DOI:10.5121/ijcsa.2014.4602 19
DATA ANALYSIS BY USING MACHINE
LEARNING ALGORITHM ON CONTROLLER
FOR ESTIMATING EMOTIONS
Tanu Sharma and Dr.Bhanu Kapoor
Department of Computer Engineering, Chitkara University, Baddi,Solan
ABSTRACT
Emotions are an unstoppable and uncontrollable aspect of mental state of human. Some bad situations give
stress and leads to different sufferings. One can’t avoid situation but can have awareness when body feel
stress or any other emotion. It becomes easy for doctors whose patient is not in condition to speak. In that
case person’s physiological parameters are measured to decide emotional status. While experiencing
different emotion, there are also physiological changes taking place in the human body, like variations in
the heart rate (ECG/HRV), skin conductance (GSR), breathing rate(BR), blood volume pulse(BVP),brain
waves (EEG), temperature and muscle tension. These were some of the metrics to sense emotive co-
efficient. This research paper objective is to design and develop a portable, cost effective and low power
embedded system that can predict different emotions by using Naïve Bayes classifiers which are based on
probability models that incorporate class conditional independence assumptions. Inputs to this system are
various physiological signals and are extracted by using different sensors. Portable microcontroller used
in this embedded system is MSP430F2013 to automatically monitor the level of stress in computer. This
paper reports on the hardware and software instrumentation development and signal processing approach
used to detect the stress level of a subject.To check the device's performance, few experiments were done in
which 20 adults (ten women and ten men) who completed different tests requiring a certain degree of effort,
such as showing facing intense interviews in office.
KEYWORDS
Emotions, Model, equation, Result, pattern, GSR, BVP, Temperature, Microcontroller
1.INTRODUCTION
Human experiencing emotions in a higher magnitude differ from those who can regulate these
emotional experiences; such type of factor is named as Emotional Intelligence (EI).Emotional
intelligence has four aspects that are also known as branches. These branches perceive emotion to
facilitate thoughts, understanding emotions and managing emotions[2].
This paper explains contribution to work in perceiving emotions. As perceiving emotion has
ability to identify emotion in oneself and others. With this it also has ability to tell difference
between honest and dishonest emotions. Recognizing emotions is not just dependent upon facial
expressions rather many more kinds of cues are there now like: voice, gestures, actions and
biofeedback modalities. Various biofeedback modalities which exist are electromyography
(EMG) in which muscle contraction and relaxation is measured, temperature change is accessed
via fingertip thermometers. Resistance of skin influenced by sweat is evaluated (GSR),
2. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
20
Cardiovascular activity is measured via heart rate [3]. Emotion depends upon ANS (autonomic
nervous system) of the person. As emotion varies and it bring changes in sympathetic nerve of the
ANS in excited condition, the sweat is secreted form the sweat gland and it decreases the GSR
and heart rate is also under continuous control of autonomic nervous system which also increase
heart rate [9].
This paper targets on the GSR with parallel work based upon BVP and temperature analysis.
Measuring instrument was designed and developed by authors. It is based on low power
consuming microcontroller(MSP430F2013).This measuring instrument can measure different
biofeedback modalities and can also predict emotion of a person. In particular, popular learning
algorithm was employed: Naïve Bayes Classifier. The Bayesian Classification represents a
supervised learning method as well as a statistical method. It assumes a probabilistic model and it
allows us to capture uncertainty about the model in a principled way by determining probabilities
of the outcomes.
Through this healthcare application certain experiments was conducted on different people
working in same office, by stimulating them with different scenarios like in meetings, before
presentations, in breaks, people appearing for interview etc. Monitoring and analyzing emotions
is important as it contains information that can help in improving human wellbeing. Emotions
which were observer by system are joyful, anxiety, calm and will also reflect illness in case of
high temperature. Twenty subjects were chosen to take part in this experiment with age from 23-
55.This was carried out for 10 male and 10 female subjects with consistent experimental setup.
When there is variation in ANS, it gives changes in biofeedback modalities as result emotions are
observed. Table 1[4] gives an example of same.
Table I.Example of biofeedback modalities In autonomic activity
Emotions GSR BVP Temperature
Anxiety Decreases Decreases Decreases
Joyful Increases Normal Normal
Calm Normal Normal Normal
Illness Normal Increases Increases
2.State of art
There exist different studies which try to detect with subject emotions in different manner. Study
for blind people [5] Analyze autonomic nervous system activity is a subject. Estimation of
emotion on one modality (GSR) [6] has shown possibilities to achieve outcome. Varying Heart
Rate is another parameter used to measure different stress levels [7].Analysis of Emotion
Recognition from GSR Based on PSO [8] is an application, which came up with different idea. A
stress sensor has implemented different algorithm techniques on GSR [4].
3.Architecture of Emotion Estimation System
The architecture of emotion estimation monitoring system is shown (fig1), which has mechanism
to measure different bio- modalities or bio-signals (GSR/BVP/Temperature). In this system
validation of subject is done at priority. It sense biosignals from human and then sends it to
3. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
21
microcontroller (MSP430F2013). This is a new model which is solution to previous conventional
models, with more portability low cost and more power efficient.
Fig.2.Biofeedback monitoring system which display different parameters connected to microcontroller [6]
Firstly system starts sensing galvanic skin response (GSR).GSR is based on sweat gland activity.
The autonomic nervous system (ANS) controls eccrine sweating, with this skin conductance
reflects arousal of the sympathetic ANS which accompanies different psychological processes.
GSR is measured by passing a small current through a pair of electrodes placed on a surface of
skin.
Fig. 2 Electrodes used as sensor for GSR
That measured value can be in form of conductance, resistance, current value or voltage value.
By placing two fingers on the surface of electrodes Galvanic Skin Response (GSR) was
measured. To have value, resistance was used. To voltage divider was formed to calculate
resistance.
4. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
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Fig. 3 GSR Input setup
Where, Rs/R1 is the resistance of the skin.
The GSR resistance oscillates between 10 k and 10 M [4].As ADC in MSP430 is 12 bits so it
has been observed that ADC saturates at 2.30V and resolution is 0.570mv.A minimum tension
level a human can have is 136mv, this helped to avoid operational amplifier and it was not
included. By avoiding operational amplifier, efficiency of system got improved because it became
less power consuming sensor system.
Blood volume pulse varies when heart rate variation is observed. It is due to the synergistic action
of the two branches of the autonomic nervous system (ANS) - vagus nerve and sympathetic
nerve. Vagus nerve: Vagal nerves innervate the S-A node, the atrioventricular node and the atrial
muscle. The stimulation of the vagus nerve slows down the heart rate. Sympathetic nerve:
Sympathetic nerve fibers innervate the entire heart, including the sinus node and A-V node.
Increased activity of the sympathetic nerves results in the increase in heart rate of human
body.BVP is recorded by technique known as a photoplethysmography.
Photoplethysmography (PPG) works by placing an individual’s finger tip or ear-lobe between two
parts of a transducer consisting of a light source and a light sensitive detector. A beam of infrared
light is projected towards the detector. The blood in the finger or ear-lobe scatters the light in the
infrared range, and the amount of light reaching the detector is inversely related to the volume of
blood in the skin periphery. This is shown in fig 3.
Fig 4 Arrangement of plethysmograph components
(1)
5. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
23
Heart rate is derived by measuring either the average or instantaneous time interval between two
successive pulses. An average rate i.e. beats/min. is calculated by counting the number of pulses
in a given time. The true picture of the heart’s responds to exercise, stress and environment. This
is done by measuring the time (T) in seconds, between the two consecutive pulses and converting
this time into beats/min. [9]
Fig .5 Beats/min. = 60/T, calculates beat per minute in human body
Heart rate reserve is the difference of the maximum heart rate and the resting heart rate. Heart
Rate Reserve = Maximum HR – Resting HR.
(HR is Heart Rate of a human body) (2)
For temperature when we feel stress muscles get contracted (tense), with this temperature of body
get reduced because of less blood reaches the fingers of the patient. This coldness can be
experienced in our hands when we are stressed. An example for the same can be, when appearing
for job interview that nervousness can be experienced by anyone. It is common for human
temperature to have readings as low as 70 to 80 degrees Fahrenheit
The eZ430-F2013 is a complete MSP430 development tool providing all the hardware and
software to evaluate the MSP430F2013 and complete an entire project in a convenient USB stick
form factor. All 14-pins on the MSP430F2013 are accessible on the MSP-EZ430D target board
for easy debugging and interfacing with peripherals. Using the integrated 16-bit SigmaDelta
analog-to digital converter, the MSP430F2013 provides all the required elements for interfacing
.Following algorithm help to prepare AD-converter:
SD16CTL = SD16REFON + SD16SSEL_1 + SD16XDIV_2 + SD16DIV_1; VREF=1.2V,
Clock=SMCLK, Clock-Divider2=16, Clock-Divider1=2 500kHz MF)
P1SEL |= BIT3; (internal reference voltage at P1.3 (Pin5) )
SD16INCTL0 = SD16INCH_4; (using input A4 (P1.1=A4+, P1.2=A4-))
SD16AE = SD16AE1 ;( negative inputs are internally connected to Vss (GND); P1.1 an A4+)
SD16CCTL0 = SD16IE + SD16UNI ;( Interrupt + unipolar Input, and continues mode)
SD16CCTL0 |= SD16XOSR; oversample rate
SD16CCTL0 |= SD16OSR_512; (over sample rate is 512)
SD16CCTL0 |= SD16SC; (start conversion)
_BIS_SR (GIE); (enter global interrupt)
The result sample rate is clock frequency divided by modulation frequency of the SD16, divided
by the oversampling rate
T
Time
6. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
24
3.1 Signals Processing
In GSR resistance calculation of Body is done using Voltage Divider Circuit with 10K variable
resistance. That variable voltage according to the body resistance is fed into the msp430
microcontroller for analogue processing which is send to the 8051 microcontroller via 3 wire self
designed protocol which is further send to the pc from serial port using UART Communication.
In BVP Sensor it measure Blood Volume Pulse Rate we are using a sensor that gives us the high
pulse in synchronization with the heart rate. A light is fed into the human finger using a LED
which is reflected back from the amount of blood accordingly the phototransistor receives the
amount of light and gives the output voltage that is fed into the msp430 microcontroller for
analogue processing which is send to the 8051 microcontroller via 3 wire self designed protocol
which is further send to the pc from serial port using UART Communication. In Temp Sensor
(LM-35) MSP microcontroller has temperature sensor inbuilt with which temp is measured
directly using the internal SD16 of MSP. The digital output value is send to the 8051
microcontroller via 3 wire self designed protocol which is further send to the pc from serial port
using UART Communication.
The architecture of emotion estimation with Biofeedback (biosignals) monitoring system is given
below (fig.1), which is having the mechanism of stimulation and measuring (with self designed
instrument) and then finally the estimation of the emotional state (anger/happy etc) of person,
which is the variation of the objective evaluation (experimental value) and ideal or expected
values (subjective).
Fig 6 Emotion Estimation block diagram [6]
3.2Hardware/Software Requirements
To design and implement the actual device, main components used are listed below:
• Electrodes (silver)
• light emitting diode (LED)
• phototransistor
• LM35
• MSP430F2013
• Display (LCD )( 16 Character x 2 Line) /Personal Computer
• IAR/Code studio compiler
Emotions
Induction
Measurement
Of Different ANS
values
Emotion
Estimation
Subjective
Assessment
7. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
25
4.Mapping of emotion Model with Emotions
The main objective is this work was to design and develop real time monitoring system which is
capable to estimate different emotions, specially for the people who all can’t express their
emotions like suffering from paralyzed body etc. This system will be user friendly as it will be
following diagram shown in fig 5.
Emotion Physiological Feeling of producing response
Emotion
stimulus
Fig 6 Sequence of emotion
The expected values of different biofeedback modalities are mapping with different ranges of
emotions are as mentioned in the table given below [10].
TABLE II. values and emotions
Stressed calm Joy Fear/
Aroused
GSR
Amplitud
e
0.28 0.15-
0.25
0.15 0.29
BVP 63 72 73 85
Temp 98 98.2 98.4 96.4
Stress is seen as a state of emergency that is preceded by arousal due to an external stimulus.
External stimulus can be considered anything which is creating distractions. After the factor
causing stress (the stressor) disappears; the body relaxes get calm and returns to a normal state.
Figure 6 shows the general case with more relationships between the four different states
depicting the inner process of emotions. These states are interrelated by each other and are also
associated by external stimuli. Emotion varies when input parameter GSR/TEM/BVP varies,
depending upon input values result (emotions) are detected.
Fig.7 Relation between different states
Normal
Arousing
Joy
Stress
8. International Journal on Computational Sciences & Applications (I
In this paper we consider a simplified setting assuming that a person is either in the normal state
or in a stressed state. The change between the two states can be sudden or incr
arousal is more rapid and relaxation takes considerably longer. [11] In following fig 3 we can see
various emotions are categorized which are based upon the degree of arousal from low to high
and valence i.e. positive to negative of emo
Fig. 8 Two dimensional emotion models with four quadrants
Following are observation from various Activities:
• when anxiety will increases then at same time with skin conductivity GSR will decreases
and HR/BVP will increase
• When parson will be joyful then with skin conductivity GSR will increases and HR/BVP
will (increase/decrease)
• When person is calm no change is observed
All features were extracted from experiment held by author, and then they were provided as input
to learning systems, which were trained to differentiate the stress from the different state of a
person.
Bayesian reasoning was applied to predict the emotional state. Bayesian is responsible for
decision making and inferential statistics by using probabilities techniques [11].
Bayes Theorem:
Method above computes the conditional probabilities of the different classes given the values of
attributes of an unknown sample and then the classifier will predict that the sample belongs to the
class having the highest posterior probability in that case. Insta
ndimensional feature vector, (x1,x2,…,xn), sample is classified to a class c from a set of possible
classes C according to the maximum a posteriori (MAP) decision rule:
Classify(x1,x2,…..xn)=argmax p(C=c)
D: Set of tuples
Each Tuple is an ‘n’ dimensional attribute vector
International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
In this paper we consider a simplified setting assuming that a person is either in the normal state
or in a stressed state. The change between the two states can be sudden or incremental; typically,
arousal is more rapid and relaxation takes considerably longer. [11] In following fig 3 we can see
various emotions are categorized which are based upon the degree of arousal from low to high
and valence i.e. positive to negative of emotions.[10]
Fig. 8 Two dimensional emotion models with four quadrants
Following are observation from various Activities:
when anxiety will increases then at same time with skin conductivity GSR will decreases
and HR/BVP will increase
ll be joyful then with skin conductivity GSR will increases and HR/BVP
will (increase/decrease)
When person is calm no change is observed
All features were extracted from experiment held by author, and then they were provided as input
s, which were trained to differentiate the stress from the different state of a
Bayesian reasoning was applied to predict the emotional state. Bayesian is responsible for
decision making and inferential statistics by using probabilities techniques [11].
(3)
above computes the conditional probabilities of the different classes given the values of
attributes of an unknown sample and then the classifier will predict that the sample belongs to the
class having the highest posterior probability in that case. Instance is represented by an
ndimensional feature vector, (x1,x2,…,xn), sample is classified to a class c from a set of possible
classes C according to the maximum a posteriori (MAP) decision rule:
Classify(x1,x2,…..xn)=argmax p(C=c) (4)
Each Tuple is an ‘n’ dimensional attribute vector
6, December 2014
26
In this paper we consider a simplified setting assuming that a person is either in the normal state
emental; typically,
arousal is more rapid and relaxation takes considerably longer. [11] In following fig 3 we can see
various emotions are categorized which are based upon the degree of arousal from low to high
when anxiety will increases then at same time with skin conductivity GSR will decreases
ll be joyful then with skin conductivity GSR will increases and HR/BVP
All features were extracted from experiment held by author, and then they were provided as input
s, which were trained to differentiate the stress from the different state of a
Bayesian reasoning was applied to predict the emotional state. Bayesian is responsible for
above computes the conditional probabilities of the different classes given the values of
attributes of an unknown sample and then the classifier will predict that the sample belongs to the
nce is represented by an
ndimensional feature vector, (x1,x2,…,xn), sample is classified to a class c from a set of possible
9. International Journal on Computational Sciences & Applications (I
X : (x1,x2,x3,…. xn)
Let there be ‘m’ Classes : C1,C2,C3…Cm
Classifier predicts X belongs to Class Ci if
P (Ci/X) > P(Cj/X) for 1<= j <= m , j <> i
Maximum Posteriori Hypothesis
P(Ci/X) = P(X/Ci) P(Ci) / P(X)
Maximize P(X/Ci) P(Ci) as P(X) is constant With many attributes, computing of this is
expensive to evaluate P(X/Ci).Naïve Assumption of “class conditional independence”
P (X |Ci)=
P(X/Ci) = P(x1/CI) * P(x2/CI) *…* P(xn/ CI)
The conditional probability in the given above formula is obtained from the estimates of the
probability mass function using training data of that
assumption may not be a realistic model of the probabilities involved; it may still permit
relatively accurate classification performance [6].
5.PROCEDURE FOR EXPERIMENTATION
Prerequisites to start the experiment are
1. The author arrived with a setup to various areas of office where different activities were
going on like meeting, interviews, lunch break, official work, tea time and official
presentations.
2. Readings were taken three times before the task,
3. Experiment was done with age from 23
4. As circuit is portable designed and was also helping with feature with low power supply,
having 1.8V of power supply.
5. Before performing above experiment, permission was granted by offi
6. Different emotions were detected, as it also helped in professional growth ( by building
strong emotions).
7. While experiment, subject was not allowed to have water as it can change emotion.
5.1.The experiment
All the events or activities were found to trigger specific emotions. Both genders were
considered 20 odd male and female. Sample was taken from various people were involved in
different activities and reading were taken suddenly to avoid manipulated emoti
to put their left and right fingers, one each on to the sensors and also check each parameter turn
wise. Then according to the connections showed in diagram (fig.2,3) the GSR,BVP and
temperature values are sensed by sensors , on the basis
Initially, the person’, under neutral conditions is measured, that serves as the reference for us to
International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
Let there be ‘m’ Classes : C1,C2,C3…Cm
Classifier predicts X belongs to Class Ci if
P (Ci/X) > P(Cj/X) for 1<= j <= m , j <> i
Hypothesis
P(Ci/X) = P(X/Ci) P(Ci) / P(X)
Maximize P(X/Ci) P(Ci) as P(X) is constant With many attributes, computing of this is
expensive to evaluate P(X/Ci).Naïve Assumption of “class conditional independence”
(5)
P(X/Ci) = P(x1/CI) * P(x2/CI) *…* P(xn/ CI) (6)
The conditional probability in the given above formula is obtained from the estimates of the
probability mass function using training data of that scenario. Moreover the independence
assumption may not be a realistic model of the probabilities involved; it may still permit
relatively accurate classification performance [6].
5.PROCEDURE FOR EXPERIMENTATION
Prerequisites to start the experiment are given below:
The author arrived with a setup to various areas of office where different activities were
going on like meeting, interviews, lunch break, official work, tea time and official
Readings were taken three times before the task, within task and after task.
Experiment was done with age from 23-55.
As circuit is portable designed and was also helping with feature with low power supply,
having 1.8V of power supply.
Before performing above experiment, permission was granted by officials.
Different emotions were detected, as it also helped in professional growth ( by building
While experiment, subject was not allowed to have water as it can change emotion.
All the events or activities were found to trigger specific emotions. Both genders were
considered 20 odd male and female. Sample was taken from various people were involved in
different activities and reading were taken suddenly to avoid manipulated emotions. Person need
to put their left and right fingers, one each on to the sensors and also check each parameter turn
wise. Then according to the connections showed in diagram (fig.2,3) the GSR,BVP and
temperature values are sensed by sensors , on the basis of these values emotions are predicted.
Initially, the person’, under neutral conditions is measured, that serves as the reference for us to
6, December 2014
27
Maximize P(X/Ci) P(Ci) as P(X) is constant With many attributes, computing of this is
expensive to evaluate P(X/Ci).Naïve Assumption of “class conditional independence”
The conditional probability in the given above formula is obtained from the estimates of the
scenario. Moreover the independence
assumption may not be a realistic model of the probabilities involved; it may still permit
The author arrived with a setup to various areas of office where different activities were
going on like meeting, interviews, lunch break, official work, tea time and official
within task and after task.
As circuit is portable designed and was also helping with feature with low power supply,
cials.
Different emotions were detected, as it also helped in professional growth ( by building
While experiment, subject was not allowed to have water as it can change emotion.
All the events or activities were found to trigger specific emotions. Both genders were
considered 20 odd male and female. Sample was taken from various people were involved in
ons. Person need
to put their left and right fingers, one each on to the sensors and also check each parameter turn
wise. Then according to the connections showed in diagram (fig.2,3) the GSR,BVP and
of these values emotions are predicted.
Initially, the person’, under neutral conditions is measured, that serves as the reference for us to
10. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
28
estimate the variance of the values, in different emotional states. Once the state is reached,
person tends to be in that state for a finite amount of time. The total time of stimulus for each
emotion is in between 5 to10 minutes and with a gap of 2-3 minutes is must between different
emotions, so to full fill these criteria emotion was estimated thrice. This design is not suitable for
people having Hyperhidrosis. This is disease of excessive sweating, which becomes drawback of
system.
5.2Observations and Results
Values of GSR between < 5 K ohms indicates high level of brain arousal, and >25Kohms
indicates low arousal (calm level).The normal heart rate of an adult varies between 60 to
90bpm.At rest, an adult has an average heart rate of 72bpm [7].
Table 3. Values of different people
PERSON GSR
BVP TEMPERATURE Emotions
Subject 1
Low Low Low Anxiety
Subject 2
Low High Low Anxiety
Subject 3
High Low Low RELAX
Subject 4
High High Low JOYFULL
Subject 5
Normal High Low RELAX
Subject 6
Normal Low Low RELAX
Subject 7
High Normal Low JOYPULL
Subject 8
Low Normal Low Anxiety
Subject 9
High High Normal JOYFULL
Subject 10
High Low Normal RELAX
Subject 11
Normal Normal Normal RELAX
Subject 12
Low Low Low Anxiety
Subject 13
Normal Normal Normal RELAX
Subject 14
High High Low JOYFULL
Subject 15
Low Low Normal Anxiety
Subject 16
Low High Normal Anxiety
Subject 17
Normal Normal Normal RELAX
Subject 18
Low Low Low Anxiety
11. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
29
Subject 19
High High Low JOYFULL
Subject 20
Normal Normal Normal RELAX
6.CONCLUSION
Emotion regulation is a capability of emotional Intelligence. The work finds its
application in the domains for personnel usage especially for people who are paralyzed.
Situations and emotions where there is great arousal like anger, fear, horror and
melancholy could be easily identified, while lower arousal emotions like calm and sad
were meagerly distinguishable. Research also talks of emotions like joy as high arousal
emotions and hence easily distinguishable. The heart rate varies between individuals and
gives different reading according to their emotions. The normal human heart rate at rest is
60 to 80 bpm. At rest, an adult has an average heart rate of 72bpm and GSR varies from 0
to 35 K ohms’. Further empirical studies need to be conducted to give a clearer picture on
this aspect. However the present work is an attempt to such an end and hopes to find out
methods and ways to achieve the goal of affective communication. Future working is also
being done parallel by adding more input parameters to the same.
6.ACKNOWLEDGEMENTS
This research paper got possible through the help and support from: My guide, parents,
family, friends, and god. Especially, I would like to acknowledge my gratitude toward the
following significant advisor of my work:
Foremost, I would like to thank Dr. Bhanu Kapoor for his most support and
encouragement. With this my sincere thank to my parents, family who provide all
essential support. This research paper would not be successful without all support.
Fig 9 Variation in GSR Fig 10 Variation in BVP
12. International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.6, December 2014
30
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