An electrocardiogram (ECG) is a test that records the electrical activity of the heart. ECG is also
used to measure the rate and regularity of heart beats and can be correlated to blood pressure
measurement. This paper describes a technique of the determination of systole and diastole cycle
duration from the RR-cycle using speech parameters. The formant F2 and F3 characterize
different emotional states like anger and fear. One heart beat includes one systole and one
diastole cycle. In an electrocardiogram, electrical systole of the ventricles begins at the
beginning of the QRS complex. Diastolic variation occurs after the systole cycle. RT interval
describes systole cycle duration. The ECG, and the speech sample of several informants have been recorded simultaneously to obtain the required relationship.
Phonocardiogram based diagnostic systemijbesjournal
A Phonocardiogram or PCG is a plot of high fidelity recording of the sounds and murmurs made by the
heart with the help of the machine called phonocardiograph. It has developed continuously to perform an
important role in the proper and accurate diagnosis of the defects of the heart. As usually with the
stethoscope, it requires highly and experienced physicians to read the phonocardiogram. A diagnostic
system based on Artificial Neural Networks (ANN) is implemented as a detector and classifier of heart
diseases. The output of the system is the classification of the sound as either normal or abnormal, if it is
abnormal what type of abnormality is present. In this paper, Based on the extracted time domain and
frequency domain features such as energy, mean, variance and Mel Frequency Cepstral Coefficients
(MFCC) various heart sound samples are classified using Support Vector Machine (SVM), K Nearest
Neighbour (KNN), Bayesian and Gaussian Mixture Model (GMM) Classifiers. The data used in this paper
was obtained from Michigan university website.
The assessment of cardiac function is essential in the athletic population not only as part of the screening process for underlying cardiac disease, but also to longitudinally assess performance and training adaptations - Source: Toshiba's VISIONS Magazine #26 | www.toshiba-medical.eu/visions
Effect of Body Posture on Heart Rate Variability Analysis of ECG Signal.pdfIJEACS
An assessment of cardiac function derived from the
ECG signal is known as heart charge variability (HRV). The
evaluation of HRV provides ways for analyzing entry into the
heart rhythm non-invasively, which can be used to guide
treatment. For the prevailing study, records of ten members in
two one-of-a-kind frame postures have been taken. Sets of
records have been received in sleeping and sitting positions. In
addition, The R-peak produced from the ECG is employed in the
evaluation of the RR interval. It is also applied for the evaluation
of HRV. In the context of coronary heart rate (HR), HRV is
linked to tachycardia (HR > 100 bpm) and bradycardia (HR 60
bpm). Linear HRV characteristics with unique time-domain and
frequency-domain indices are interpreted into two distinct
postures. As a result, it is possible to conclude that the RR
interval increases for the supine position during all two poses, as
sitting appears to be a more comfortable situation than the
alternative one. Also, as the frequency-area evaluation result
proposes, the LF/HF ratio is better in the supine position, i.e.,
better sympathetic has an effect. Consequently, supine has a
higher resting circumstance than that sitting. A non-linear
Poincare plot has also been incorporated for accessing variability.
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.
MEDITATION: ITS TREMENDOUS IMPACT ON HEART RATE VARIABILITYcscpconf
The heart is connected through the nervous system directly to major organs and is able to sense
their need. The heart also responds to adrenaline in the blood flowing through it. With these
inputs the heart is able to adjust its rate to accommodate the needs of the whole body. By its
heartbeat, it is able to broadcast a common signal to every cell. One measure of heart health is
Heart Rate Variability (HRV). HRV is defined in terms of how different the lengths of time
between each heart beat is. The greater the difference in times between heart beats, the
healthier is the heart thought to be. Individuals may be able to learn to increase their own HRV
and become healthier by a daily meditation practice. This paper uses Heart Variability as the
base signal for studying the impact of meditation on it. The paper brings out the difference
between pre and post meditation conditions in terms qualitative measure of Power Spectral
Density (PSD) variations using Smoothed Pseudo Wigner Ville (SPWVD) distribution method.The simulations highlight the meditation effects overtime period in PSDs
Phonocardiogram based diagnostic systemijbesjournal
A Phonocardiogram or PCG is a plot of high fidelity recording of the sounds and murmurs made by the
heart with the help of the machine called phonocardiograph. It has developed continuously to perform an
important role in the proper and accurate diagnosis of the defects of the heart. As usually with the
stethoscope, it requires highly and experienced physicians to read the phonocardiogram. A diagnostic
system based on Artificial Neural Networks (ANN) is implemented as a detector and classifier of heart
diseases. The output of the system is the classification of the sound as either normal or abnormal, if it is
abnormal what type of abnormality is present. In this paper, Based on the extracted time domain and
frequency domain features such as energy, mean, variance and Mel Frequency Cepstral Coefficients
(MFCC) various heart sound samples are classified using Support Vector Machine (SVM), K Nearest
Neighbour (KNN), Bayesian and Gaussian Mixture Model (GMM) Classifiers. The data used in this paper
was obtained from Michigan university website.
The assessment of cardiac function is essential in the athletic population not only as part of the screening process for underlying cardiac disease, but also to longitudinally assess performance and training adaptations - Source: Toshiba's VISIONS Magazine #26 | www.toshiba-medical.eu/visions
Effect of Body Posture on Heart Rate Variability Analysis of ECG Signal.pdfIJEACS
An assessment of cardiac function derived from the
ECG signal is known as heart charge variability (HRV). The
evaluation of HRV provides ways for analyzing entry into the
heart rhythm non-invasively, which can be used to guide
treatment. For the prevailing study, records of ten members in
two one-of-a-kind frame postures have been taken. Sets of
records have been received in sleeping and sitting positions. In
addition, The R-peak produced from the ECG is employed in the
evaluation of the RR interval. It is also applied for the evaluation
of HRV. In the context of coronary heart rate (HR), HRV is
linked to tachycardia (HR > 100 bpm) and bradycardia (HR 60
bpm). Linear HRV characteristics with unique time-domain and
frequency-domain indices are interpreted into two distinct
postures. As a result, it is possible to conclude that the RR
interval increases for the supine position during all two poses, as
sitting appears to be a more comfortable situation than the
alternative one. Also, as the frequency-area evaluation result
proposes, the LF/HF ratio is better in the supine position, i.e.,
better sympathetic has an effect. Consequently, supine has a
higher resting circumstance than that sitting. A non-linear
Poincare plot has also been incorporated for accessing variability.
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.
MEDITATION: ITS TREMENDOUS IMPACT ON HEART RATE VARIABILITYcscpconf
The heart is connected through the nervous system directly to major organs and is able to sense
their need. The heart also responds to adrenaline in the blood flowing through it. With these
inputs the heart is able to adjust its rate to accommodate the needs of the whole body. By its
heartbeat, it is able to broadcast a common signal to every cell. One measure of heart health is
Heart Rate Variability (HRV). HRV is defined in terms of how different the lengths of time
between each heart beat is. The greater the difference in times between heart beats, the
healthier is the heart thought to be. Individuals may be able to learn to increase their own HRV
and become healthier by a daily meditation practice. This paper uses Heart Variability as the
base signal for studying the impact of meditation on it. The paper brings out the difference
between pre and post meditation conditions in terms qualitative measure of Power Spectral
Density (PSD) variations using Smoothed Pseudo Wigner Ville (SPWVD) distribution method.The simulations highlight the meditation effects overtime period in PSDs
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.
Heart Rate Variability (HRV) is the measure of time difference between two successive heart beats and its
variation occurring due to internal and external stimulation causes. HRV is a non-invasive tool for indirect
investigation of both cardiac and autonomic system function in both healthy and diseased condition. It has
been speculated that HRV analysis by nonlinear method might bring potentially useful prognosis
information into light which will be helpful for assessment of cardiac condition. In this study, HRV from
two types of data sets are analyzed which are collected from different subjects in the age group of 18 to 22.
Then parameters of linear methods and three nonlinear methods, approximate entropy (ApEn), detrended
fluctuation analysis (DFA) and Poincare plot have been applied to analyze HRV among 158 subjects of
which 79 are control study and 79 are alcoholics. It has been clearly shown that the linear and nonlinear
parameters obtained from these two methods reflect the opposite heart condition of the two types of data
under study among alcoholics non-alcoholic’s by HRV measures. Poincare plot clearly distinguishes
between the alcoholics by analysing the location of points in the ellipse of the Poincare plot. In alcoholics
the points of the Poincare plot will be concentrated at the centre of the ellipse and in nonalchoholics the
points will be much concentrated along the periphery of the ellipse. The Approximate Entropy value will be
lesser than one in alcoholics and in nonalcoholics the entropy shows values greater than one. The
increased LF/HF value in alcoholics denotes the increase in sympathetic nervous system activities and
decrease of the parasympathetic activity which will be lesser in alcoholics subjects.
Sleep Apnea Identification using HRV Features of ECG Signals IJECEIAES
Sleep apnea is a common sleep disorder that interferes with the breathing of a person. During sleep, people can stop breathing for a moment that causes the body lack of oxygen that lasts for several seconds to minutes even until the range of hours. If it happens for a long period, it can result in more serious diseases, e.g. high blood pressure, heart failure, stroke, diabetes, etc. Sleep apnea can be prevented by identifying the indication of sleep apnea itself from ECG, EEG, or other signals to perform early prevention. The purpose of this study is to build a classification model to identify sleep disorders from the Heart Rate Variability (HRV) features that can be obtained with Electrocardiogram (ECG) signals. In this study, HRV features were processed using several classification methods, i.e. ANN, KNN, N-Bayes and SVM linear Methods. The classification is performed using subjectspecific scheme and subject-independent scheme. The simulation results show that the SVM method achieves higher accuracy other than three other methods in identifying sleep apnea. While, time domain features shows the most dominant performance among the HRV features.
A typical Realization of the process with linear recovery of AldosteroneIJERA Editor
Hypercortisolism as a sign of hypothamamus-pituitary-adrenocortical (HPA) axis overactivity and sleep EEG
changes are frequently observed in depression. Closely related to the
HPA axis is the renin-angiotensin-aldosterone system (RAAS) as 1. adrenocorticotropic hormone (ACTH) is a
common stimulus for cortisol and aldosterone, 2. cortisol release is suppressed by mineralocorticoid receptor
(MR) agonists 3. angiotensin II (ATII) releases CRH and vasopressin from the hypothalamus. The first passage
time and the bounds of the survival functions for the application are also obtained
A STUDY ON IMPACT OF ALCOHOL AMONG YOUNG INDIAN POPULATION USING HRV ANALYSISijcseit
Heart Rate Variability (HRV) is the measure of time difference between two successive heart beats and its
variation occurring due to internal and external stimulation causes. HRV is a non-invasive tool for indirect
investigation of both cardiac and autonomic system function in both healthy and diseased condition. It has
been speculated that HRV analysis by nonlinear method might bring potentially useful prognosis
information into light which will be helpful for assessment of cardiac condition. In this study, HRV from
two types of data sets are analyzed which are collected from different subjects in the age group of 18 to 22.
Then parameters of linear methods and three nonlinear methods, approximate entropy (ApEn), detrended
fluctuation analysis (DFA) and Poincare plot have been applied to analyze HRV among 158 subjects of
which 79 are control study and 79 are alcoholics. It has been clearly shown that the linear and nonlinear
parameters obtained from these two methods reflect the opposite heart condition of the two types of data
under study among alcoholics non-alcoholic’s by HRV measures. Poincare plot clearly distinguishes
between the alcoholics by analysing the location of points in the ellipse of the Poincare plot. In alcoholics
the points of the Poincare plot will be concentrated at the centre of the ellipse and in nonalchoholics the
points will be much concentrated along the periphery of the ellipse. The Approximate Entropy value will be
lesser than one in alcoholics and in nonalcoholics the entropy shows values greater than one. The
increased LF/HF value in alcoholics denotes the increase in sympathetic nervous system activities and
decrease of the parasympathetic activity which will be lesser in alcoholics subjects.
Data Collection & Analysis in Human Autonomic Research: How to Guide to Succe...InsideScientific
In this American Physiological Society (APS) webinar produced in partnership with ADInstruments, Jackie Limberg, PhD discusses the basics of human autonomic research as well as some tips and tricks for successful human testing. Implementing key experimental controls and understanding nuances in data collection and analysis during human autonomic testing have important implications for the accuracy and reliability of your findings.
Dr. Limberg introduces the gold standards for measuring both basal and reflex autonomic responses in humans, what equipment is required, and how to minimize variability in your data. The focus of the webinar is on data collection, including recommendations for study design as well as data analysis and interpretation.
Key Topics Include:
- Identify tests appropriate for measuring basal versus reflex autonomic control
- Describe the pros and cons of tests used in human autonomic research
- Create a research setting that is conducive to reliable and accurate human autonomic data
- Select equipment appropriate for the research questions being addressed
- Anticipate and avoid areas that may increase data variability and reduce your ability to interpret results
The term Arrhythmia refers to any change from the normal sequence in the electrical impulses. It is also treated as abnormal heart rhythms or irregular heartbeats. The rate of growth of Cardiac Arrhythmia disease is very high & its effects can be observed in any age group in society. Arrhythmia detection can be done in many ways but effective & simple method for detection & diagnosis of Cardiac Arrhythmia is by doing analysis of Electrocardiogram signals from ECG sensors. ECG signal can give us the detail information of heart activities, so we can use ECG signals to detect the rhythm & behaviour of heart beats resulting into detection & diagnosis of Cardiac Arrhythmia. In this paper new & improved methodology for early Detection & Classification of Cardiac Arrhythmia has been proposed. In this paper ECG signals are captured using ECG sensors & this ECG signals are used & processed to get the required data regarding heart beats of the human being & then proposed methodology applies for Detection & Classification of Cardiac Arrhythmia. Detection of Cardiac Arrhythmia using ECG signals allows us for easy & reliable way with low cost solution to diagnose Arrhythmia in its prior early stage.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Home Care Heart Diagnosis and Measurement of Biological Signals Using Intelli...ijsrd.com
the importance behind this work is the development of intelligent, accurate diagnosis of heart rate using blood pressure. BP is the parameter which does not abide by a single range, but it depends upon the factors like age, family history. By using blood pressure system, heart rate of a person is measured. At the present situation the mortality rate has been increased due to rise in blood pressure and heart malfunctions. A Biosensor is used in forth to detect the range of heart rate. Intelligent system used here is fuzzy system which takes age, gender, BMI for the verification. Lab view is other end of the project which is used to connect the hardware to show the progress of measurement. Parameters such as Smoke detection, Temperature measurement, unauthorized entry were are included for additional facilities.
Abstract: Electrocardiogram is a machine that is used for the detection and the analysis of the peaks of the ECG signal. ECG signal is used for the detection of various diseases related to the heart. The cardiac arrhythmia shows abnormalities of heart that is considered as the major threat to the human. The peaks that are present in the ECG signal are used for detection of the disease. The R peak of the ECG signal is used for the detection of the disease, the arrhythmia is detected as Tachycardia and Bradycardia. This paper presents a study of the ECG signal, peaks and of the various techniques that are used for the detection of disease.
NADI PARIKSHA: A NOVEL MACHINE LEARNING BASED WRIST PULSE ANALYSIS THROUGH PU...IAEME Publication
The Nadi pariksha technique, which dates to ancient Ayurveda, is a fabulous approach for detecting imbalances in the human body. The pulse, or Nadi (old term), is a vital movement of energy, or life, that moves through the delicate medium of the human body, allowing the physician to feel and understand the blood flow into and out of the heart. It is a traditional method for identifying physical, mental, and emotional imbalances in the body, as well as diseases. A technique for measuring the pressure in pulses like this is useful for disease detection. For any disease diagnosis, however, Nadi pariksha requires experts with vast experience and pulse reading skills. In this paper, an ultrasound microphone sensor is used to identify three Ayurveda doshas, namely, Vata, Pitta, and Kapha, from a collected Nadi signal at a single place. Different statistical features are retrieved for each signal and categorized using the K-NN classifier to identify these three doshas. The proposed work has been tested and validated in a clinical setting with several patients, and we observed that this method results in a higher identification rate for all three doshas.
Guidelines heart rate_variability_ft_1996[1]ES-Teck India
Guidelines
Heart rate variability
Standards of measurement, physiological interpretation, and
clinical use
Task Force of The European Society of Cardiology and The North American
Society of Pacing and Electrophysiology (Membership of the Task Force listed in
the Appendix)
Machine-Learning Estimation of Body Posture and Physical Activity by Wearable...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method.
MACHINE-LEARNING ESTIMATION OF BODY POSTURE AND PHYSICAL ACTIVITY BY WEARABLE...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
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Similar to Assessment of systolic and diastolic cycle duration from speech analysis in the state of anger and fear.
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.
Heart Rate Variability (HRV) is the measure of time difference between two successive heart beats and its
variation occurring due to internal and external stimulation causes. HRV is a non-invasive tool for indirect
investigation of both cardiac and autonomic system function in both healthy and diseased condition. It has
been speculated that HRV analysis by nonlinear method might bring potentially useful prognosis
information into light which will be helpful for assessment of cardiac condition. In this study, HRV from
two types of data sets are analyzed which are collected from different subjects in the age group of 18 to 22.
Then parameters of linear methods and three nonlinear methods, approximate entropy (ApEn), detrended
fluctuation analysis (DFA) and Poincare plot have been applied to analyze HRV among 158 subjects of
which 79 are control study and 79 are alcoholics. It has been clearly shown that the linear and nonlinear
parameters obtained from these two methods reflect the opposite heart condition of the two types of data
under study among alcoholics non-alcoholic’s by HRV measures. Poincare plot clearly distinguishes
between the alcoholics by analysing the location of points in the ellipse of the Poincare plot. In alcoholics
the points of the Poincare plot will be concentrated at the centre of the ellipse and in nonalchoholics the
points will be much concentrated along the periphery of the ellipse. The Approximate Entropy value will be
lesser than one in alcoholics and in nonalcoholics the entropy shows values greater than one. The
increased LF/HF value in alcoholics denotes the increase in sympathetic nervous system activities and
decrease of the parasympathetic activity which will be lesser in alcoholics subjects.
Sleep Apnea Identification using HRV Features of ECG Signals IJECEIAES
Sleep apnea is a common sleep disorder that interferes with the breathing of a person. During sleep, people can stop breathing for a moment that causes the body lack of oxygen that lasts for several seconds to minutes even until the range of hours. If it happens for a long period, it can result in more serious diseases, e.g. high blood pressure, heart failure, stroke, diabetes, etc. Sleep apnea can be prevented by identifying the indication of sleep apnea itself from ECG, EEG, or other signals to perform early prevention. The purpose of this study is to build a classification model to identify sleep disorders from the Heart Rate Variability (HRV) features that can be obtained with Electrocardiogram (ECG) signals. In this study, HRV features were processed using several classification methods, i.e. ANN, KNN, N-Bayes and SVM linear Methods. The classification is performed using subjectspecific scheme and subject-independent scheme. The simulation results show that the SVM method achieves higher accuracy other than three other methods in identifying sleep apnea. While, time domain features shows the most dominant performance among the HRV features.
A typical Realization of the process with linear recovery of AldosteroneIJERA Editor
Hypercortisolism as a sign of hypothamamus-pituitary-adrenocortical (HPA) axis overactivity and sleep EEG
changes are frequently observed in depression. Closely related to the
HPA axis is the renin-angiotensin-aldosterone system (RAAS) as 1. adrenocorticotropic hormone (ACTH) is a
common stimulus for cortisol and aldosterone, 2. cortisol release is suppressed by mineralocorticoid receptor
(MR) agonists 3. angiotensin II (ATII) releases CRH and vasopressin from the hypothalamus. The first passage
time and the bounds of the survival functions for the application are also obtained
A STUDY ON IMPACT OF ALCOHOL AMONG YOUNG INDIAN POPULATION USING HRV ANALYSISijcseit
Heart Rate Variability (HRV) is the measure of time difference between two successive heart beats and its
variation occurring due to internal and external stimulation causes. HRV is a non-invasive tool for indirect
investigation of both cardiac and autonomic system function in both healthy and diseased condition. It has
been speculated that HRV analysis by nonlinear method might bring potentially useful prognosis
information into light which will be helpful for assessment of cardiac condition. In this study, HRV from
two types of data sets are analyzed which are collected from different subjects in the age group of 18 to 22.
Then parameters of linear methods and three nonlinear methods, approximate entropy (ApEn), detrended
fluctuation analysis (DFA) and Poincare plot have been applied to analyze HRV among 158 subjects of
which 79 are control study and 79 are alcoholics. It has been clearly shown that the linear and nonlinear
parameters obtained from these two methods reflect the opposite heart condition of the two types of data
under study among alcoholics non-alcoholic’s by HRV measures. Poincare plot clearly distinguishes
between the alcoholics by analysing the location of points in the ellipse of the Poincare plot. In alcoholics
the points of the Poincare plot will be concentrated at the centre of the ellipse and in nonalchoholics the
points will be much concentrated along the periphery of the ellipse. The Approximate Entropy value will be
lesser than one in alcoholics and in nonalcoholics the entropy shows values greater than one. The
increased LF/HF value in alcoholics denotes the increase in sympathetic nervous system activities and
decrease of the parasympathetic activity which will be lesser in alcoholics subjects.
Data Collection & Analysis in Human Autonomic Research: How to Guide to Succe...InsideScientific
In this American Physiological Society (APS) webinar produced in partnership with ADInstruments, Jackie Limberg, PhD discusses the basics of human autonomic research as well as some tips and tricks for successful human testing. Implementing key experimental controls and understanding nuances in data collection and analysis during human autonomic testing have important implications for the accuracy and reliability of your findings.
Dr. Limberg introduces the gold standards for measuring both basal and reflex autonomic responses in humans, what equipment is required, and how to minimize variability in your data. The focus of the webinar is on data collection, including recommendations for study design as well as data analysis and interpretation.
Key Topics Include:
- Identify tests appropriate for measuring basal versus reflex autonomic control
- Describe the pros and cons of tests used in human autonomic research
- Create a research setting that is conducive to reliable and accurate human autonomic data
- Select equipment appropriate for the research questions being addressed
- Anticipate and avoid areas that may increase data variability and reduce your ability to interpret results
The term Arrhythmia refers to any change from the normal sequence in the electrical impulses. It is also treated as abnormal heart rhythms or irregular heartbeats. The rate of growth of Cardiac Arrhythmia disease is very high & its effects can be observed in any age group in society. Arrhythmia detection can be done in many ways but effective & simple method for detection & diagnosis of Cardiac Arrhythmia is by doing analysis of Electrocardiogram signals from ECG sensors. ECG signal can give us the detail information of heart activities, so we can use ECG signals to detect the rhythm & behaviour of heart beats resulting into detection & diagnosis of Cardiac Arrhythmia. In this paper new & improved methodology for early Detection & Classification of Cardiac Arrhythmia has been proposed. In this paper ECG signals are captured using ECG sensors & this ECG signals are used & processed to get the required data regarding heart beats of the human being & then proposed methodology applies for Detection & Classification of Cardiac Arrhythmia. Detection of Cardiac Arrhythmia using ECG signals allows us for easy & reliable way with low cost solution to diagnose Arrhythmia in its prior early stage.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Home Care Heart Diagnosis and Measurement of Biological Signals Using Intelli...ijsrd.com
the importance behind this work is the development of intelligent, accurate diagnosis of heart rate using blood pressure. BP is the parameter which does not abide by a single range, but it depends upon the factors like age, family history. By using blood pressure system, heart rate of a person is measured. At the present situation the mortality rate has been increased due to rise in blood pressure and heart malfunctions. A Biosensor is used in forth to detect the range of heart rate. Intelligent system used here is fuzzy system which takes age, gender, BMI for the verification. Lab view is other end of the project which is used to connect the hardware to show the progress of measurement. Parameters such as Smoke detection, Temperature measurement, unauthorized entry were are included for additional facilities.
Abstract: Electrocardiogram is a machine that is used for the detection and the analysis of the peaks of the ECG signal. ECG signal is used for the detection of various diseases related to the heart. The cardiac arrhythmia shows abnormalities of heart that is considered as the major threat to the human. The peaks that are present in the ECG signal are used for detection of the disease. The R peak of the ECG signal is used for the detection of the disease, the arrhythmia is detected as Tachycardia and Bradycardia. This paper presents a study of the ECG signal, peaks and of the various techniques that are used for the detection of disease.
NADI PARIKSHA: A NOVEL MACHINE LEARNING BASED WRIST PULSE ANALYSIS THROUGH PU...IAEME Publication
The Nadi pariksha technique, which dates to ancient Ayurveda, is a fabulous approach for detecting imbalances in the human body. The pulse, or Nadi (old term), is a vital movement of energy, or life, that moves through the delicate medium of the human body, allowing the physician to feel and understand the blood flow into and out of the heart. It is a traditional method for identifying physical, mental, and emotional imbalances in the body, as well as diseases. A technique for measuring the pressure in pulses like this is useful for disease detection. For any disease diagnosis, however, Nadi pariksha requires experts with vast experience and pulse reading skills. In this paper, an ultrasound microphone sensor is used to identify three Ayurveda doshas, namely, Vata, Pitta, and Kapha, from a collected Nadi signal at a single place. Different statistical features are retrieved for each signal and categorized using the K-NN classifier to identify these three doshas. The proposed work has been tested and validated in a clinical setting with several patients, and we observed that this method results in a higher identification rate for all three doshas.
Guidelines heart rate_variability_ft_1996[1]ES-Teck India
Guidelines
Heart rate variability
Standards of measurement, physiological interpretation, and
clinical use
Task Force of The European Society of Cardiology and The North American
Society of Pacing and Electrophysiology (Membership of the Task Force listed in
the Appendix)
Machine-Learning Estimation of Body Posture and Physical Activity by Wearable...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method.
MACHINE-LEARNING ESTIMATION OF BODY POSTURE AND PHYSICAL ACTIVITY BY WEARABLE...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
Using social media in education provides learners with an informal way for communication. Informal communication tends to remove barriers and hence promotes student engagement. This paper presents our experience in using three different social media technologies in teaching software project management course. We conducted different surveys at the end of every semester to evaluate students’ satisfaction and engagement. Results show that using social media enhances students’ engagement and satisfaction. However, familiarity with the tool is an important factor for student satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The amount of piracy in the streaming digital content in general and the music industry in specific is posing a real challenge to digital content owners. This paper presents a DRM solution to monetizing, tracking and controlling online streaming content cross platforms for IP enabled devices. The paper benefits from the current advances in Blockchain and cryptocurrencies. Specifically, the paper presents a Global Music Asset Assurance (GoMAA) digital currency and presents the iMediaStreams Blockchain to enable the secure dissemination and tracking of the streamed content. The proposed solution provides the data owner the ability to control the flow of information even after it has been released by creating a secure, selfinstalled, cross platform reader located on the digital content file header. The proposed system provides the content owners’ options to manage their digital information (audio, video, speech, etc.), including the tracking of the most consumed segments, once it is release. The system benefits from token distribution between the content owner (Music Bands), the content distributer (Online Radio Stations) and the content consumer(Fans) on the system blockchain.
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This paper discusses the importance of verb suffix mapping in Discourse translation system. In
discourse translation, the crucial step is Anaphora resolution and generation. In Anaphora
resolution, cohesion links like pronouns are identified between portions of text. These binders
make the text cohesive by referring to nouns appearing in the previous sentences or nouns
appearing in sentences after them. In Machine Translation systems, to convert the source
language sentences into meaningful target language sentences the verb suffixes should be
changed as per the cohesion links identified. This step of translation process is emphasized in
the present paper. Specifically, the discussion is on how the verbs change according to the
subjects and anaphors. To explain the concept, English is used as the source language (SL) and
an Indian language Telugu is used as Target language (TL)
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The using of information technology resources is rapidly increasing in organizations,
businesses, and even governments, that led to arise various attacks, and vulnerabilities in the
field. All resources make it a must to do frequently a penetration test (PT) for the environment
and see what can the attacker gain and what is the current environment's vulnerabilities. This
paper reviews some of the automated penetration testing techniques and presents its
enhancement over the traditional manual approaches. To the best of our knowledge, it is the
first research that takes into consideration the concept of penetration testing and the standards
in the area.This research tackles the comparison between the manual and automated
penetration testing, the main tools used in penetration testing. Additionally, compares between
some methodologies used to build an automated penetration testing platform.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
In order to treat and analyze real datasets, fuzzy association rules have been proposed. Several
algorithms have been introduced to extract these rules. However, these algorithms suffer from
the problems of utility, redundancy and large number of extracted fuzzy association rules. The
expert will then be confronted with this huge amount of fuzzy association rules. The task of
validation becomes fastidious. In order to solve these problems, we propose a new validation
method. Our method is based on three steps. (i) We extract a generic base of non redundant
fuzzy association rules by applying EFAR-PN algorithm based on fuzzy formal concept analysis.
(ii) we categorize extracted rules into groups and (iii) we evaluate the relevance of these rules
using structural equation model.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
2. 138 Computer Science & Information Technology (CS & IT)
B. Blood Pressure
Our heart pumps the blood in our body with some pressure[3,4]. Blood pressure (BP) is the
pressure exerted by circulating blood upon the walls of blood vessels and is one of the
principal vital signs. When used without further specification, "blood pressure" usually refers to
the arterial pressure of the systemic circulation. During each heartbeat, BP varies between a
maximum (systolic) and a minimum (diastolic) pressure.
Heart contracts to achieve a maximum blood pressure as required for proper circulation in our
body. This pressure is called systolic blood pressure and the duration is called systole cycle. After
the systole cycle completed the heart comes in the relaxing position by exerting minimum blood
pressure called diastolic blood pressure. This resting period of heart is called diastole cycle. The
systole and diastole cycle duration make one RR cycle duration (0.8 sec.).
Electrocardiogram (ECG) is a measure of the functioning of human heart The ECG pattern
comprises of P, Q, R, S & T components as shown in the lower curve in Fig1.[1] .Since one RR
cycle has duration of (0.6-0.8) sec. in normal persons at rest. And the heart beats @ 60-80 beats
per min [7,8].
Cardiac cycle (0.8sec) can be divided into three stages as follows-
1. diastole (relaxation 0.6 sec)
2. atrial systole (contraction of atria 0.06 sec)
3. ventricular systole (contraction of ventricals 0.2sec)
In an electrocardiogram electrical systole of the ventricles begins at the beginning of the QRS
complex. Cardiac Diastole is the period of time when the heart relaxes after contraction in
preparation for refilling with circulating blood. Ventricular diastole is when the ventricles are
relaxing, while atrial diastole is when the atria are relaxing. Together they are known as complete
cardiac diastole[7,8].
During ventricular diastole, the pressure in the (left and right) ventricles drops from the peak that
it reaches in systole. When the pressure in the left ventricle drops to below the pressure in the left
atrium, the mitral valve opens, and the left ventricle fills with blood that was accumulating in the
left atrium.
The standard ECG along with Blood Pressure waveform is shown in Fig. 1.
3. Computer Science & Information Technology (CS & IT) 139
Fig 1. Standard ECG with blood pressure waveform[9]
II. METHODOLOGY
The ECG of the several informants have been recorded. At the same time the utterances of Hindi
consonants of same informants were recorded through a microphone and subjected to digitization.
Further the formant frequency analysis has been carried out with a DSP Tool (PRAAT) to obtain
the various formant frequencies [2] and F1, F2 and F3 formant frequency vs utterances duration
response is plotted to observe the RR-cycle in the state of anger and fear[4,10-15] .
Since QRS complex corresponds to the systolic cycle & RT interval describes diastolic
cycle[7,8]. The observation table ,TABLE I provides the systolic and diastole cycle duration in
the normal state and in the state of anger and fear.
TABLE I. Determination of diastole and systole duration from RR-cycle
S.
N.
Age
Yrs
Medical
Conditi
on
RR cycle in
Different mental states
(sec)
Systole cycle in
Different mental states
(sec)
Diastole cycle in
Different mental states
(sec)
Nor
mal
Anger Fear Nor
mal
Anger Fear Norm
al
Anger Fear
1 25 Normal .89 .75 .74 .29 .29 .28 .60 .46 .46
2 32 Normal .76 .70 .69 .26 .27 .27 .50 .43 .42
3 34 Normal .75 .69 .68 .25 .25 .27 .50 .44 .41
4 23 Normal .85 .80 .60 .28 .26 .29 .59 .54 .31
5 34 Normal .82 .78 .72 .29 .26 .29 .53 .52 .43
4. 140 Computer Science & Information Technology (CS & IT)
III. RESULT & CONCLUSION
From the observations it becomes possible to determine the diastole and systole duration from
the RR- cycle through speech parameter in the state of anger and fear . The present work
provides the variation in systole and diastole duration in the state of anger and fear . As the
physiological study shows that the anger and fear emotions can be dangerous for heart up to some
extent . The proposed framework provides the facility to observe the effect of anger and fear on
the heart .
IV. ACKNOWLEDGEMENT
Authors are very much thankful to all the informants ,doctors and the people who have been
directly or indirectly involved in writing this paper.
References:
[1] Jacob Benesty, “Springer handbook of speech processing”, Springer’s publication, 2008, Page 511-
512.
[2] Deshpande Anjali, Zadgaonkar A.S. & Thakur K., “Determination of heart beat rate form the formant
frequency analysis”, NSA India (2007).
[3] Zadgaonkar A.S. & Thakur K., Formant frequency analysis of mentally retarded, International
Symposium on Frontiers of Research on Speech & Music(FRSM2006), Lucknow, U.P., India, p31-
35 (2006).
[4] Neeta Tripathi(2006), Study of face and speech parameters and identification of their relationship for
emotional status recognition. Ph.D. Thesis, Pt.R.S.S.U.
[5] Berstein A. & Cohen A, “Speech processing applied for chest diagnosis, 14’th conv. Of Elect. &
Electronics Engg”, Tel Aviv, Israel, p2.4.4 (1985).
[6] Marleen H.Schut, Kees Tuinenbreijer, Egon L. Vanden Brock, Joyce H.D.M. Westerink ,”Biometrics
for emotion detection (BED): exploring the combination of speech and ECG”, B-Interface -2010, pp
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