In this paper a novel methodology is proposed to identify and to compare the
frequency range of different Vedic chantings from Rig Veda, Yajur Veda,
Atharva Veda and Sama Veda. Nowadays in spite of busy schedule and
hectic work, the human beings are mostly stressed. To get rid from this
stressed state, one of the best solutions is listening Vedic chantings. The
alpha brainwaves are in the frequency range of 8-12 Hz under giving
relaxation to stressed human being. Three selected samples from each Veda
have been processed through the simulation compiler Praat and the
parameters like spectral response, pitch, intensity, formants and pulses have
observed. In the above identified parameters, the frequency in intensity
calculation is taken for each sample. This frequency is compared with the
brainwaves for which the frequencies are in the ranges of 0 Hz to >27 Hz
(alpha, beta, gamma, theta and delta). The extracted signal frequencies from
Vedic chantings are compared with frequencies of brainwaves. Among the four Vedas, the frequencies extracted from Sama Veda lies in alpha frequency range. The remaining is fluctuating from alpha.
Iaetsd detection of addiction of an individual andIaetsd Iaetsd
This document proposes a device to detect addiction and avoid addiction using embedded systems. It works by using EEG sensors to detect high beta brainwaves associated with stress or addiction. If high beta waves are detected, the device produces binaural beats within the alpha or theta range using two oscillators played through headphones. This is intended to entrain the brainwaves to a lower, more relaxed frequency using the brain's natural "frequency following response" to binaural beats, thus helping avoid addiction. The device is intended to be lightweight and portable for personal use in treating psychological addictions.
This document summarizes a study on analyzing EEG signals during meditation using wavelet transforms. It begins by providing background on meditation and EEG signals. It then discusses previous research showing meditation affects physical and mental relaxation. The study aims to analyze changes in EEG signals during meditation using wavelet transforms, as EEG signals are non-stationary and nonlinear. It describes collecting EEG data from subjects during meditation and non-meditation, and using Daubechies wavelets to decompose the signals into frequency bands. The study will calculate statistical parameters of the frequency bands to analyze differences in EEG signals during meditation versus non-meditation states.
This article is a review of neurofeedback techniques in the broad context of various clinical implications. Authors presented the neurophysiological background of these developing methods in relation to the state-of-the-art techniques. The broad range of methods of neurofeedback were reviewed, comprising the transfer of information, automation, brain-computer interface, multichannel Z-Score neurofeedback and slow cortical potentials. Neurofeedback may be an effective tool for self-regulation, useful for achieving better selfknowledge and enhanced cognitive skills. A tailored, dedicated program, based on quantitative electroencephalographic (QEEG) assessment and/or Z-Score should be implemented for a given patient in order to gain trust and fulfill the compliance. The proven clinical benefits of multi-channel neurofeedback, targeting regulation of particular brain regions, or inducing specific neural patterns, may be an alternative method for treating diseases in a non-invasive, introspective way. Effective modulation of the physiological functions which may affect various neural mechanisms of cognition and behavior seems to be the future perspective of neurofeedback
This document discusses different types of neural oscillations observed in the brain, including alpha waves, delta waves, theta rhythm, mu waves, beta waves, and gamma waves. It provides details on the frequency ranges and functions of each type of wave. For example, it states that alpha waves originate from the occipital lobe during relaxation with closed eyes, delta waves are associated with deep sleep, and gamma waves may be implicated in creating unified conscious perception. The document also discusses how neural oscillations are involved in cognitive functions and can be used to transmit information across brain regions in a radio-like fashion on different frequencies.
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
This document discusses different types of brain waves and neural oscillations, including their frequencies and functions. It provides information on alpha, delta, theta, mu, beta, and gamma waves. Key points include:
- Different types of brain waves are associated with different cognitive states, like relaxation vs concentration. They facilitate processes like memory and perception.
- Neural oscillations occur throughout the nervous system and can be measured by EEG. Their synchronization is linked to cognitive functions.
- Frequencies of gamma oscillations route information flow in the hippocampus. The brain uses different wave frequencies to transmit different kinds of information between regions.
1. Music has physiological and psychological benefits for the mind and body. It can induce relaxation and alter brain wave activity.
2. Various types of brain waves are associated with different mental states, such as delta waves during deep sleep and beta waves during active thinking. Music can induce alpha and theta waves associated with relaxation, creativity, and reduced stress.
3. Traditional practices from cultures around the world have incorporated music to promote mental and physical well-being. Music therapy is an effective treatment for various mental health conditions and can improve focus, decision-making, and performance.
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.
Iaetsd detection of addiction of an individual andIaetsd Iaetsd
This document proposes a device to detect addiction and avoid addiction using embedded systems. It works by using EEG sensors to detect high beta brainwaves associated with stress or addiction. If high beta waves are detected, the device produces binaural beats within the alpha or theta range using two oscillators played through headphones. This is intended to entrain the brainwaves to a lower, more relaxed frequency using the brain's natural "frequency following response" to binaural beats, thus helping avoid addiction. The device is intended to be lightweight and portable for personal use in treating psychological addictions.
This document summarizes a study on analyzing EEG signals during meditation using wavelet transforms. It begins by providing background on meditation and EEG signals. It then discusses previous research showing meditation affects physical and mental relaxation. The study aims to analyze changes in EEG signals during meditation using wavelet transforms, as EEG signals are non-stationary and nonlinear. It describes collecting EEG data from subjects during meditation and non-meditation, and using Daubechies wavelets to decompose the signals into frequency bands. The study will calculate statistical parameters of the frequency bands to analyze differences in EEG signals during meditation versus non-meditation states.
This article is a review of neurofeedback techniques in the broad context of various clinical implications. Authors presented the neurophysiological background of these developing methods in relation to the state-of-the-art techniques. The broad range of methods of neurofeedback were reviewed, comprising the transfer of information, automation, brain-computer interface, multichannel Z-Score neurofeedback and slow cortical potentials. Neurofeedback may be an effective tool for self-regulation, useful for achieving better selfknowledge and enhanced cognitive skills. A tailored, dedicated program, based on quantitative electroencephalographic (QEEG) assessment and/or Z-Score should be implemented for a given patient in order to gain trust and fulfill the compliance. The proven clinical benefits of multi-channel neurofeedback, targeting regulation of particular brain regions, or inducing specific neural patterns, may be an alternative method for treating diseases in a non-invasive, introspective way. Effective modulation of the physiological functions which may affect various neural mechanisms of cognition and behavior seems to be the future perspective of neurofeedback
This document discusses different types of neural oscillations observed in the brain, including alpha waves, delta waves, theta rhythm, mu waves, beta waves, and gamma waves. It provides details on the frequency ranges and functions of each type of wave. For example, it states that alpha waves originate from the occipital lobe during relaxation with closed eyes, delta waves are associated with deep sleep, and gamma waves may be implicated in creating unified conscious perception. The document also discusses how neural oscillations are involved in cognitive functions and can be used to transmit information across brain regions in a radio-like fashion on different frequencies.
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
This document discusses different types of brain waves and neural oscillations, including their frequencies and functions. It provides information on alpha, delta, theta, mu, beta, and gamma waves. Key points include:
- Different types of brain waves are associated with different cognitive states, like relaxation vs concentration. They facilitate processes like memory and perception.
- Neural oscillations occur throughout the nervous system and can be measured by EEG. Their synchronization is linked to cognitive functions.
- Frequencies of gamma oscillations route information flow in the hippocampus. The brain uses different wave frequencies to transmit different kinds of information between regions.
1. Music has physiological and psychological benefits for the mind and body. It can induce relaxation and alter brain wave activity.
2. Various types of brain waves are associated with different mental states, such as delta waves during deep sleep and beta waves during active thinking. Music can induce alpha and theta waves associated with relaxation, creativity, and reduced stress.
3. Traditional practices from cultures around the world have incorporated music to promote mental and physical well-being. Music therapy is an effective treatment for various mental health conditions and can improve focus, decision-making, and performance.
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.
Brain wave, neuroscience, brain activity, EEG technology, understanding brain waves
Understanding the complexities of the human brain has been a longstanding challenge for scientists and researchers. One fascinating aspect of studying the brain is analyzing its electrical activity, known as brain waves. These rhythmic patterns of neural activity provide valuable insights into various cognitive processes and emotional states.
An EEG detects electrical activity in the brain through electrodes placed on the scalp. Brainwaves are produced by synchronized electrical pulses from neuron communication and are divided into bands based on frequency and function: delta (1-3 Hz) occur during deep sleep; theta (4-7 Hz) during light sleep or daydreaming; alpha (8-12 Hz) during relaxation; beta (13-38 Hz) during focused mental activity; and gamma (39-42 Hz) associated with perception and consciousness. EEGs and brainwave activity provide information about brain states from deep sleep to high alertness.
This document describes a brainwave-controlled robotic arm. The arm is designed to help disabled individuals express themselves. Brainwaves are detected by a Neurosky headset and transmitted via Bluetooth to an Arduino microcontroller. The microcontroller maps the brainwave signals to control servo motors that move the artificial arm. Specifically, different levels of attention and meditation detected in the brainwaves will trigger opening and closing of the hand or elbow movement of the arm. The system was tested on 10 people with promising but imperfect results, suggesting it needs further development to achieve full control of the arm's movements.
FIELD TESTED IP/TECHNOLOGY THAT DISRUPTS THE BRAIN-COMPUTER INTERFACE MARKETMichael Tansey
The Brain-Computer Interface market is estimated to reach a 2 billion dollar valuation by 2020. The 'Tansey Technique' resolves current measurements of brainwave activity.
Estimate the Activation of EEG Bands from Different Brain Lobes with Classifi...CSCJournals
Physiological research with human brain is getting more popular because it is the center of human nervous system. Music is a popular source of entertainment in modern era which affects differently in different brain lobes for having different frequency and pitch. The brain lobes are divided into frontal, central and parietal lobe. In this paper, an approach has been proposed to identify the activated brain lobes by using spectral analysis from EEG signal due to music evoked stimulation. In later phase, the impact of music on the EEG bands (alpha, beta, delta, theta) originating from different brain lobes is analyzed. Music has both positive and negative impact on human brain activity. According to linguistic variation, subject age and preference, volume level of songs, the impact on different EEG bands varies. In this work, music is categorized as mild, pop, rock song at different volume level (low, comfortable and high) based on Power Spectral Density (PSD) analysis. The average PSD value is 0.21 W/Hz, 0.32W/Hz and 0.84W/Hz for mild, pop and rock song respectively. The volume levels are considered as 0%-15% volume level for low volume, 16%- 55% volume level for comfortable volume and 56%-100% volume level for high volume. At comfortable volume level the central lobe of the brain is more activated for mild song and parietal lobe is activated for both pop and rock songs based on logarithmic power and PSD analysis. A statistical test two- way ANOVA has been conducted to indicate the variation in EEG band. For two-way ANOVA analysis, the P-value was taken as 0.05. A topographical representation has been performed for effective brain mapping to show the effects of music on the EEG bands for mild, pop and rock songs at the mentioned volume level. The maximum percentage of alpha band activation is 60% in comfortable volume which decreases with high volume and it indicates that, when the music stimuli moved towards the high-volume level, human cognition state moves from relax to stress condition due to the activeness of beta band. A Graphical User Interface (GUI) has been designed in MATLAB platform for the entire work.
This study analyzed EEG recordings from 9 experienced Isha Yoga practitioners before and after performing Shambhavi Maha Mudra practice. The analysis found increases in delta and theta band power across most brain regions, indicating a higher level of mental consciousness. It also found decreases in beta band power, suggesting lower anxiety levels. Coherence between brain hemispheres increased significantly. The results demonstrate specific neurophysiological changes associated with the meditative practice.
The Science of iAwake's Profound Meditation ProgramPam Dupuy, LMFT
This document discusses brainwaves, brainwave entrainment technologies, and iAwake's Integrated Neural Entrainment Technology (iNET). It describes the different types of brainwaves (gamma, beta, alpha, theta, delta), how brainwave entrainment works using binaural beats, and how iNET improves upon traditional binaural beats by utilizing additional entrainment strategies like exhaustive binaural beats, dual-pulse binaural, harmonic layering, rhythmic panning, temporal entrainment, carrier wave therapy, and energetic entrainment. The benefits of iNET for meditators are said to include deeper meditation, accelerated spiritual growth, emotional release, stress relief, improved focus and cognition
Top 24 team in the High School Utah Entrepreneur Challenge 2017. The program is managed by the Lassonde Entrepreneur Institute at the University of Utah. Learn more at lassonde.utah.edu/hsuec.
This document discusses vibrational telepathy and energy healing. It defines telepathy as communicating information from one mind to another without traditional senses, involving electromagnetic fields. There are two main types: global, without sight between subjects, usually feelings; and mental, sending/receiving thoughts between those in sight, involving strong emotion. Vibrational therapy can heal through resonating life-force energy between practitioner and client's frequencies to facilitate healing on quantum levels. Studying aura through quantizing electromagnetic field energies reveals mental activity characteristics. Harmonizing object and subject frequencies through emitted waves of varying harmonious frequencies can improve memory and concentration for those suffering lapses.
The document summarizes a study that investigated whether auditory attention is necessary for the cortical propagation of binaural beats. The study found that binaural beats were detected at the proposed brain location even with a distractor task, indicating the signal propagation is independent of attentional control. This suggests binaural beats could be used for applications like relaxation or hypnosis without requiring attention.
The document discusses the brain and brain waves. It describes how the brain communicates electrochemically through electrical impulses produced by the movement of neurotransmitters between neurons. These electrical impulses produce brain waves that can be measured by EEG. There are different types of brain waves (delta, theta, alpha, beta) associated with different mental states. Brainwave entrainment uses stimuli like binaural beats or isochronic tones to consciously alter brain wave patterns and access different states of mind.
BRAIN MACHINE INTERFACE SYSTEM FOR PERSON WITH QUADRIPLEGIA DISEASEEditor IJCATR
Brain Machine Interface (BMI) system is very
helpful technique for the disabled and handicapped
person to express their emotion and feeling to someone
else with the help of EEG Signals coming out of our
brain. As we know that, the human brain is made up of
billions of interconnected neurons about the size of a
pinhead. As neurons interact with each other, patterns
manifest as singular thoughts such as a math calculation.
As a by-product, every interaction between neurons
creates a miniscule electrical discharge, measurable by
EEG (electroencephalogram) machines. This system
enables people with severe motor disabilities to send
command to electronic devices by help of their brain
waves. These signals can be used to control any
electronic devices like mouse cursor of the computer, a
wheel chair, a robotic arm etc. The research in this area of
BCI system (or BMI) uses the sequence of 256 channel
EEG data for the analysis of the EEG signals coming out
of our brain by using tradition gel based multi sensor
system, which is very bulky and not convenient to use in
real time application. So this particular work proposes a
convenient system to analyze the EEG signals, which
uses few dry sensors as compared to the tradition gel
based multi sensor system with wireless transmission
technique for capturing the brain wave patterns and
utilizing them for their application. The goal of this
research is to improve quality of life for those with severe
disabilities.
This document provides a summary and analysis of psychological concepts found in ancient Vedic texts from India. It discusses three hymns (suktas) from the Vedas - the Mana-āvartana-sūkta, Śivasamkalpa-sūkta, and Śraddhā-Sūkta. These hymns address topics like controlling one's wandering mind, having noble resolve, and the power of faith, respectively. The document argues that the Vedic seers intuitively understood psychological phenomena like self-fulfilling prophecies, placebo effects, and techniques like autosuggestion that are part of modern psychology. It concludes that integrating ancient Indian and modern viewpoints
This document discusses mindfulness and intrinsic leadership. It argues that happiness leads to success, not vice versa, and explores techniques for cultivating mindfulness like breath watching and observing inside and outside. It discusses how mindfulness practices combined with emotional intelligence and neuroscience can help with leadership. Mindfulness is said to reduce brain activity associated with fear and anxiety while increasing activity associated with awareness and learning. The document also explores how other practices like pranayama, yoga, mudras, sound, and Sanskrit can impact the human energy system and discusses viewing the human body as an energy system rather than just physical.
This document discusses neuromarkers and neurosignals that could be used for robotic control. It covers:
1. Different tactile receptors in the skin and their properties, as well as pathways from the periphery to the cortex.
2. Paradigms for tactile stimulation including evoked responses, entrained responses, and naturalistic frequency-varying stimuli.
3. Relevant frequency bands in the EEG that encode tactile information processing and sensorimotor coordination, such as theta, mu, alpha, beta, gamma, kappa, and sigma.
4. Tools that could help study dynamics in the wild frontier, including cross-correlograms between tactile signals and brain signals.
This document discusses brain waves and neurofeedback. It describes the different types of brain waves (delta, theta, alpha, beta, gamma) and what states each is associated with. It then discusses classic EEG which is used to diagnose neurological issues like seizures. Next, it covers neurofeedback (EEG biofeedback) which is used for diagnostics and therapy by teaching patients to regulate their brain waves. It also discusses 3D neurofeedback using LORETA which provides more advanced brain imaging and targeting of networks during neurofeedback training. Midbrain activation and the Shichida method of right brain training is briefly covered.
This document provides an overview of music and color therapy. It begins with definitions of music therapy from various organizations and discusses the theoretical foundations, including vibrational tuning theory, brain waves theory, chakra theory, and endorphin theory. It then covers the history of music therapy and categorizes where it fits within medical treatment. The document outlines several models and methods of music therapy, including improvisational music therapy, singing and discussion, guided imagery and music (GIM), and clinical Orff Schulwerk. It provides details on the theoretical basis and procedures for several of these methods.
The document discusses the Gayatri Mantra and the effects of chanting it based on a study. It provides background on the mantra and its meaning. It then describes a study that measured the blood pressure of hypertensive and normal individuals before and after chanting the mantra 108 times. The study found a significant decrease in blood pressure for hypertensives after chanting, bringing it closer to normal levels, while normals only saw a decrease in diastolic pressure. The document concludes the preliminary results are encouraging but a larger study is needed to better assess the benefits.
The document discusses the neurological and psychological perceptions of sound. It explains that sounds can cause physiological responses and affect brain waves. It describes research showing that filtering and gating sounds through specialized processing can improve auditory functioning and skills by exercising the muscles of the inner ear. The concepts of resonance, entrainment, and sonic neurotechnologies are also introduced for intentionally applying sounds to bring about changes in the mind and body.
Understand brain waves and master you lifeAbdelaziz52
With Mental Waves, find your personal access to well-being! Did you know that sounds, vibrations and music take us on deep journeys of infinite therapeutic and spiritual possibilities?
Our new tools based on neuroscience and the powers of sound make it easy for everyone to achieve tranquility, healing and awakening
Because of the rapid growth in technology breakthroughs, including
multimedia and cell phones, Telugu character recognition (TCR) has recently
become a popular study area. It is still necessary to construct automated and
intelligent online TCR models, even if many studies have focused on offline
TCR models. The Telugu character dataset construction and validation using
an Inception and ResNet-based model are presented. The collection of 645
letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34×16
Guninthamulu, and 10 Ankelu. The proposed technique aims to efficiently
recognize and identify distinctive Telugu characters online. This model's main
pre-processing steps to achieve its goals include normalization, smoothing,
and interpolation. Improved recognition performance can be attained by using
stochastic gradient descent (SGD) to optimize the model's hyperparameters.
Scientific workload execution on a distributed computing platform such as a
cloud environment is time-consuming and expensive. The scientific workload
has task dependencies with different service level agreement (SLA)
prerequisites at different levels. Existing workload scheduling (WS) designs
are not efficient in assuring SLA at the task level. Alongside, induces higher
costs as the majority of scheduling mechanisms reduce either time or energy.
In reducing, cost both energy and makespan must be optimized together for
allocating resources. No prior work has considered optimizing energy and
processing time together in meeting task level SLA requirements. This paper
presents task level energy and performance assurance-workload scheduling
(TLEPA-WS) algorithm for the distributed computing environment. The
TLEPA-WS guarantees energy minimization with the performance
requirement of the parallel application under a distributed computational
environment. Experiment results show a significant reduction in using energy
and makespan; thereby reducing the cost of workload execution in comparison
with various standard workload execution models.
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Brain wave, neuroscience, brain activity, EEG technology, understanding brain waves
Understanding the complexities of the human brain has been a longstanding challenge for scientists and researchers. One fascinating aspect of studying the brain is analyzing its electrical activity, known as brain waves. These rhythmic patterns of neural activity provide valuable insights into various cognitive processes and emotional states.
An EEG detects electrical activity in the brain through electrodes placed on the scalp. Brainwaves are produced by synchronized electrical pulses from neuron communication and are divided into bands based on frequency and function: delta (1-3 Hz) occur during deep sleep; theta (4-7 Hz) during light sleep or daydreaming; alpha (8-12 Hz) during relaxation; beta (13-38 Hz) during focused mental activity; and gamma (39-42 Hz) associated with perception and consciousness. EEGs and brainwave activity provide information about brain states from deep sleep to high alertness.
This document describes a brainwave-controlled robotic arm. The arm is designed to help disabled individuals express themselves. Brainwaves are detected by a Neurosky headset and transmitted via Bluetooth to an Arduino microcontroller. The microcontroller maps the brainwave signals to control servo motors that move the artificial arm. Specifically, different levels of attention and meditation detected in the brainwaves will trigger opening and closing of the hand or elbow movement of the arm. The system was tested on 10 people with promising but imperfect results, suggesting it needs further development to achieve full control of the arm's movements.
FIELD TESTED IP/TECHNOLOGY THAT DISRUPTS THE BRAIN-COMPUTER INTERFACE MARKETMichael Tansey
The Brain-Computer Interface market is estimated to reach a 2 billion dollar valuation by 2020. The 'Tansey Technique' resolves current measurements of brainwave activity.
Estimate the Activation of EEG Bands from Different Brain Lobes with Classifi...CSCJournals
Physiological research with human brain is getting more popular because it is the center of human nervous system. Music is a popular source of entertainment in modern era which affects differently in different brain lobes for having different frequency and pitch. The brain lobes are divided into frontal, central and parietal lobe. In this paper, an approach has been proposed to identify the activated brain lobes by using spectral analysis from EEG signal due to music evoked stimulation. In later phase, the impact of music on the EEG bands (alpha, beta, delta, theta) originating from different brain lobes is analyzed. Music has both positive and negative impact on human brain activity. According to linguistic variation, subject age and preference, volume level of songs, the impact on different EEG bands varies. In this work, music is categorized as mild, pop, rock song at different volume level (low, comfortable and high) based on Power Spectral Density (PSD) analysis. The average PSD value is 0.21 W/Hz, 0.32W/Hz and 0.84W/Hz for mild, pop and rock song respectively. The volume levels are considered as 0%-15% volume level for low volume, 16%- 55% volume level for comfortable volume and 56%-100% volume level for high volume. At comfortable volume level the central lobe of the brain is more activated for mild song and parietal lobe is activated for both pop and rock songs based on logarithmic power and PSD analysis. A statistical test two- way ANOVA has been conducted to indicate the variation in EEG band. For two-way ANOVA analysis, the P-value was taken as 0.05. A topographical representation has been performed for effective brain mapping to show the effects of music on the EEG bands for mild, pop and rock songs at the mentioned volume level. The maximum percentage of alpha band activation is 60% in comfortable volume which decreases with high volume and it indicates that, when the music stimuli moved towards the high-volume level, human cognition state moves from relax to stress condition due to the activeness of beta band. A Graphical User Interface (GUI) has been designed in MATLAB platform for the entire work.
This study analyzed EEG recordings from 9 experienced Isha Yoga practitioners before and after performing Shambhavi Maha Mudra practice. The analysis found increases in delta and theta band power across most brain regions, indicating a higher level of mental consciousness. It also found decreases in beta band power, suggesting lower anxiety levels. Coherence between brain hemispheres increased significantly. The results demonstrate specific neurophysiological changes associated with the meditative practice.
The Science of iAwake's Profound Meditation ProgramPam Dupuy, LMFT
This document discusses brainwaves, brainwave entrainment technologies, and iAwake's Integrated Neural Entrainment Technology (iNET). It describes the different types of brainwaves (gamma, beta, alpha, theta, delta), how brainwave entrainment works using binaural beats, and how iNET improves upon traditional binaural beats by utilizing additional entrainment strategies like exhaustive binaural beats, dual-pulse binaural, harmonic layering, rhythmic panning, temporal entrainment, carrier wave therapy, and energetic entrainment. The benefits of iNET for meditators are said to include deeper meditation, accelerated spiritual growth, emotional release, stress relief, improved focus and cognition
Top 24 team in the High School Utah Entrepreneur Challenge 2017. The program is managed by the Lassonde Entrepreneur Institute at the University of Utah. Learn more at lassonde.utah.edu/hsuec.
This document discusses vibrational telepathy and energy healing. It defines telepathy as communicating information from one mind to another without traditional senses, involving electromagnetic fields. There are two main types: global, without sight between subjects, usually feelings; and mental, sending/receiving thoughts between those in sight, involving strong emotion. Vibrational therapy can heal through resonating life-force energy between practitioner and client's frequencies to facilitate healing on quantum levels. Studying aura through quantizing electromagnetic field energies reveals mental activity characteristics. Harmonizing object and subject frequencies through emitted waves of varying harmonious frequencies can improve memory and concentration for those suffering lapses.
The document summarizes a study that investigated whether auditory attention is necessary for the cortical propagation of binaural beats. The study found that binaural beats were detected at the proposed brain location even with a distractor task, indicating the signal propagation is independent of attentional control. This suggests binaural beats could be used for applications like relaxation or hypnosis without requiring attention.
The document discusses the brain and brain waves. It describes how the brain communicates electrochemically through electrical impulses produced by the movement of neurotransmitters between neurons. These electrical impulses produce brain waves that can be measured by EEG. There are different types of brain waves (delta, theta, alpha, beta) associated with different mental states. Brainwave entrainment uses stimuli like binaural beats or isochronic tones to consciously alter brain wave patterns and access different states of mind.
BRAIN MACHINE INTERFACE SYSTEM FOR PERSON WITH QUADRIPLEGIA DISEASEEditor IJCATR
Brain Machine Interface (BMI) system is very
helpful technique for the disabled and handicapped
person to express their emotion and feeling to someone
else with the help of EEG Signals coming out of our
brain. As we know that, the human brain is made up of
billions of interconnected neurons about the size of a
pinhead. As neurons interact with each other, patterns
manifest as singular thoughts such as a math calculation.
As a by-product, every interaction between neurons
creates a miniscule electrical discharge, measurable by
EEG (electroencephalogram) machines. This system
enables people with severe motor disabilities to send
command to electronic devices by help of their brain
waves. These signals can be used to control any
electronic devices like mouse cursor of the computer, a
wheel chair, a robotic arm etc. The research in this area of
BCI system (or BMI) uses the sequence of 256 channel
EEG data for the analysis of the EEG signals coming out
of our brain by using tradition gel based multi sensor
system, which is very bulky and not convenient to use in
real time application. So this particular work proposes a
convenient system to analyze the EEG signals, which
uses few dry sensors as compared to the tradition gel
based multi sensor system with wireless transmission
technique for capturing the brain wave patterns and
utilizing them for their application. The goal of this
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Analysis of frequency dependent Vedic chanting and its influence on neural activity of humans
1. International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol. 12, No. 2, July 2023, pp. 230~239
ISSN: 2089-4864, DOI: 10.11591/ijres.v12.i2.pp230-239 230
Journal homepage: http://ijres.iaescore.com
Analysis of frequency dependent Vedic chanting and its
influence on neural activity of humans
Veera Raghava Swamy Nalluri, V. J. K. Kishor Sonti, G. Sundari
Department of Electronics and Communication Engineering, Sathyabama Institute of Science and Technology, Chennai, India
Article Info ABSTRACT
Article history:
Received Oct 20, 2022
Revised Dec 12, 2022
Accepted Jan 17, 2023
In this paper a novel methodology is proposed to identify and to compare the
frequency range of different Vedic chantings from Rig Veda, Yajur Veda,
Atharva Veda and Sama Veda. Nowadays in spite of busy schedule and
hectic work, the human beings are mostly stressed. To get rid from this
stressed state, one of the best solutions is listening Vedic chantings. The
alpha brainwaves are in the frequency range of 8-12 Hz under giving
relaxation to stressed human being. Three selected samples from each Veda
have been processed through the simulation compiler Praat and the
parameters like spectral response, pitch, intensity, formants and pulses have
observed. In the above identified parameters, the frequency in intensity
calculation is taken for each sample. This frequency is compared with the
brainwaves for which the frequencies are in the ranges of 0 Hz to >27 Hz
(alpha, beta, gamma, theta and delta). The extracted signal frequencies from
Vedic chantings are compared with frequencies of brainwaves. Among the
four Vedas, the frequencies extracted from Sama Veda lies in alpha
frequency range. The remaining is fluctuating from alpha.
Keywords:
Atharva veda
Brain waves
Rig veda
Sama veda
Vedic chantings
Yajur veda
This is an open access article under the CC BY-SA license.
Corresponding Author:
Veera Raghava Swamy Nalluri
Department of Electronics and Communication Engineering
Sathyabama Institute of Science and Technology
Chennai-600119, Tamil Nadu, India
Email: raghavaswamynv@gmail.com
1. INTRODUCTION
Different challenges are faced by the people work in the industries, offices and even in business, our
attentiveness and concentration are decreased and increasing their stress and anxiety. This situation creates
health problems like increasing stress, blood pressure, and stress management is gaining importance day by
day [1]. Vedas as authority of Sabda pramana [2], Shabda hints to words expressed verbally as a mantra. This
Shabda or sound or acoustic signal that generates out by the pronunciation of Vedic texts and mantras is
believed to have a profound effect on our mental system [3]. The sound of traditional patters produces
vibrations that have a beneficial psychological effect on both the chanters and listeners.
Vedic melodies produce incredible sonic vibrations that can change vitality at all stages of
development [4]. They affect the psyche and reach subliminal levels where our karmic patterns are preserved.
The best possible recitation of the mantras can diminish stress and pressure [5].
Hindu and Buddhist practitioners utilize meditation to focus the mind and shut out extraneous
distractions that interfere with concentration [6]. Sound-based Vedic chanting (such as a powerful mantra)
has the potential to heal and elevate consciousness [7]. Speech and chanting are old religious traditions used
to assist people increase their ability to move energy to the body and mind [8].
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Neuroscientists are fascinated by the mental process that occurs during probing. Equipped with
technology to analyse brain activity such as emotions induced by brainwave activation alpha wave, beta
wave, gamma wave, delta wave and theta wave [9]–[12]. Electroencephalogram (EEG) stimuli such as sound
have been shown in experiments to alter the brain [13]–[15]. Some researchers they practice and listen Vedic
sounds like ‘OM’, Om Namah shivaya, observed stress, anxiety and blood pressure before and after. They
observed levels of these parameters decreased [16]–[19].
The brain waves work almost like musical notes. Some are low frequency; others are high
frequency. Together they have the power to create harmony and brain relaxation. The thoughts, emotions and
sensations are in perfect balance, cantered and open to everything that surrounds a human being [1], [20]–
[25]. The classification of brain waves is as follows shown in Figure 1.
Table 1 shows the frequency and its effect on brain. As per the survey of literature alpha waves
gives more relaxation to brain and improves the critical thinking. “I want to train my Alpha brain waves to be
more relaxed and get more inner peace”. The alpha waves will be generated in those in-between, twilight
times when a human being is calm but not asleep. The frequency range of alpha waves may vary from 8-12
Hz. Classification of Alpha waves and their effects are shown in Table 2 [15], [19].
Figure 1. Brain wave frequency range
Table 1. Segregation of frequency for brain wave
Frequency
range (Hz)
Name Brain activity and effect Waveforms
> 27 Gamma
waves
Higher mental activity, including
perception, problem solving, and
consciousness
Time (sec)
Frequency
(Hz)
12-27 Beta
waves
Active, busy thinking, active
processing, active concentration,
arousal, and cognition
Time (sec)
Frequency
(Hz)
8-12 Alpha
waves
Calm relaxed yet alert state
Time (sec)
Frequency
(Hz)
3-8 Theta
waves
Deep meditation /relaxation, REM
sleep
Time (sec)
Frequency
(Hz)
0.2-3 Delta
waves
Deep dreamless sleep, loss of body
awareness
Time (sec)
Frequency
(Hz)
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Table 2. Classification of alpha (α) brain wave
Frequency range (Hz) Effect on brain
8-8.3 Music, art, invention, and problem solution all require creative thought. Overcoming difficult issues or
problems due to simplicity with which answers can be found through re-evaluation. This is a form of self-
purpose inter-awareness.
Schumann’s resonance it’s very grounding because it’s the same frequency as the earth’s magnetic field.
To treat drug, alcohol, and food addictions, among other things. Provides the "satisfied" feeling that a
person would ordinarily obtain from their addiction.
8.3 Enhances clairvoyance in the presence of visual images and metal items.
8-8.6 Reduced stress and anxiety
9 Brings awareness of body imbalances
8-10 Start of "super learning", your passive ability to memorise and learn new information. It stimulates
problem-solving creativity and intuitive ideas. This is not active learning, but rather a calm state in which
your mind absorbs information without active concentration.
10.5 Blood pressure is reduced. The Thymus, heart, blood, and circulatory system are all connected to the Heart
Chakra.
10.6 Relaxed and alert.
11 Relaxes you while keeping you alert. Can be a lucid condition (day dreaming) but not from weariness.
Thoughts and feelings may float through your mind, calming you down. It can be a bridge between the
conscious mind and the unconscious mind. Reduces stress levels.
12 Gives mental stability
2. METHOD
The voice clips of Vedic chantings (Rig Veda, Yajur Veda, Sama Veda, and Atharva Veda) have
been processed thorough Praat simulation tool. The parameters like sound spectrum (spectrogram), pitch,
intensity, pulses, formants have observed for all the four Vedas chantings. From the spectrogram the
frequency ranges of the sound waves have been identified. These frequency ranges are classified and divided
as delta, theta, alpha, beta, gamma range of frequencies. In the above observed frequency ranges, the voice
clips having frequency in the range of Alpha have taken and make it listen by the listener and observed their
emotions by using MATLAB (emotion recognition). The process flow to identify the frequency range of
Vedic chanting is shown in Figure 2.
Figure 2. Process flow to identify the frequency range of Vedic chanting
The speech signals of four Vedas (Rig Veda, Atharva Veda, Yajur Veda and Sama Veda) has been
analysed using the simulation tool Praat. The time duration of the speech signal for which the analysis has
been done is below 10 sec. Three different speech signals with different types of mantras (Chanting) from
each Veda has considered for analysis. The spectral response of the input speech signal (Vedic chanting) is
observed within the spectral frequency range of 1 to 20 Hz. The parameters spectral frequency, pitch,
intensity, formants and pulses for a speech signal (Vedic chanting) were investigated in this research. The
frequency range detected in the analysed speech stream is compared to the frequency range of brain waves
(delta, theta, alpha, beta and gamma).
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3. RESULTS AND DISCUSSION
Veda is defined as a collection of hymns and mantras. These are chanted during rituals. When
listening chantings by neuro transmission, human brain will excite and generate brain waves (delta, theta,
alpha, beta and gamma). Vedas are mainly classified into four Vedas. They are Rig Veda, Yajur Veda,
Atharva Veda and Sama Veda. Analysing these four Vedas chanting, checking of their frequencies are done
with in alpha frequency range.
3.1. Atharva veda
The Atharva Veda is filled with a number of enchantments, charms, and spells. This sets it apart
from other Vedas, which place more of an emphasis on ceremonial and sacrifice. Figure 3 shows the analysis
of three specimens taken from Atharva Veda and recording of EEG signals. Analysing these three signals
frequency ranges by using Praat simulation tool, most of these specimen frequency ranges are in alpha
brainwave frequency range. From Table 3 it is evident that most of the selected Vedic chanting is in the range
of alpha brain waves which gives the relaxation to the brain of human being (listener).
Figure 3. Analysis of Atharva Veda sound files AV-01, AV-03 and AV-07
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Table 3. Analysis and frequency range of chanting in Atharva Veda
Specimen No. Frequency range (Hz) Band Brain activity and effect
AV-01 4.676-12.83 Theta and alpha i). Deep meditation /relaxation
ii). Calm relaxed yet alert state
AV-03 1-12.57 Delta, theta, and alpha i). Deep meditation /relaxation
ii). Calm relaxed yet alert state
iii). Dreamless Sleep and loss of body awareness
AV-07 1-13.74 Delta, theta, and alpha
3.2. Rig veda
Rig Veda contains hymns about their mythology. A collection of Vedic Sanskrit hymns from
ancient India is known as the Rigveda or Rig Veda. It is one of the four revered Vedic scriptures that Hindus
consider to be canonical. The earliest known Vedic Sanskrit text is the Rigveda. The earliest texts in any
Indo-European language are found in its early strata. Figure 4 shows the analysis of three specimens taken
from Rig Veda and recording of EEG signals. Analyzing these three signals frequency by using Praat
simulation tool, most of these frequency ranges are in alpha brainwave frequency range. From Table 4 it is
evident that most of the selected Vedic chanting is in the range of theta and alpha brain waves which gives
the relaxation and alertness to the human brain (listener).
Figure 4. Analysis of Rig Veda sound files RV-01, RV-02 and RV-08
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Table 4. Analysis and frequency range of chanting in Rig Veda
Specimen No. Frequency range (Hz) Band Brain activity and effect
RV-01 3.952-13.123 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
RV-02 3.952-13.96 Theta and alpha
RV-08 2.11-13.49 Delta, theta, and alpha
i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
ii). Dreamless sleep and loss of body awareness
3.3. Yajur veda
Yajur means worship and Veda means knowledge. It contains Veda primarily of prose mantras for
worship rituals/mantras. It is one of the four Vedas and one of the scriptures of Hinduism. It has ritual-
offering formula that was said by a priest, an individual performed ritual actions in front of the yagna fire. It
is mainly grouped into two i.e., Krishna Yajur Veda and Shukla Yajur Veda.
3.3.1. Krishna Yajur veda
Krishna Yajur Veda means motley collection of verses. The Brahmana scriptures are incorporated
into the samhitas of Krishna Yajur Veda. Figure 5 shows the analysis of three specimens taken from Krishna
Yajur Veda and recording of EEG signals. Analyzing these three specimens by using Praat simulation tool,
most of these frequency ranges are in range of alpha brainwave frequency. From Table 5 it is evident that
most of the selected Vedic chanting is in the range of delta, theta and alpha brain waves which gives the
relaxation, alertness, dreamless sleep and loss of body awareness to human being (listener).
Figure 5. Analysis of Krishna Yajur Veda sound files KYV-01, KYV-02 and KYV-03
Table 5. Frequency range of chanting in Krishna Yajur Veda
Specimen No. Frequency range (Hz) Band Brain activity and effect
KYV-01 1-13.03 Delta, theta, and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
iii). Dreamless sleep and loss of body awareness
KYV-02 1.8-13.49
KYV-03 2.939-14.04
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3.3.2. Shukla Yajur veda
Shukla Yajur Veda means well-arranged verses. The phrase "white" or "bright" refers to the Shukla
Yajur Veda, which is the "well-arranged, clear" Yajur Veda. Figure 6 shows the analysis of three specimens
taken from Shukla Yajur Veda and recording of EEG signals. Analyzing these three specimen signals by
using Praat simulation tool, most of these frequency ranges are in alpha brainwave frequency range. From
Table 6 it is evident that most of the selected Vedic chanting is in the range of theta and alpha brain waves
which gives the relaxation and alertness to the human brain (listener).
Figure 6. Analysis of Sukla Yajur Veda sound files SYV-01, SYV-02 and SYV-03
Table 6. Frequency range of chanting in Sukla Yajur Veda
Specimen No. Frequency range (Hz) Band Brain activity and effect
SYV-01 6.638-14.33 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
SYV-02 4.23-13.4 Theta and alpha
SYV-03 5.156-13.86 Theta and alpha
3.4. Sama veda
Sama Veda consists mainly of hymns about rituals with swaras (Raagas). The Sama Veda is known
as the Veda of chants and songs. Hinduism's sacred texts include this old Vedic Sanskrit literature. It is a
liturgical text with 1,875 verses and is one of the four Vedas. Only 75 verses were not taken directly from the
Rig Veda. Figure 7 shows the analysis of three specimens taken from Sama Veda and recording of EEG
signals. Analyzing these three specimen signals frequency range by using Praat simulation tool, most of these
frequency ranges are in alpha brainwave frequency range.
From Table 7 it is very clear that most of the selected Vedic chanting is in the range of Alpha brain
waves which gives the relaxation to human brain (listener). From the Table 8, all the selected speech signals
(Vedic chanting’s) have compared and identified the range of frequencies which fall in brain wave frequency.
Their effect on brain is also observed and tabulated. Among all the Vedic chanting’s, the chanting’s taken
from Sama Veda fall in the alpha brain wave range which effects the human brain and keep the brain in
relaxed state which are in the frequency range of 8-12 Hz.
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Figure 7. Analysis of Sama Veda sound files
Table 7. Frequency range of chanting in Sama Yajur Veda
Specimen No. Frequency range (Hz) Band Brain activity and effect
SV- 01 8.861-13.4 Alpha
Deep meditation/relaxation
SV- 02 7.696-14.51 Alpha
SV- 03 8.583-13.86 Alpha
SV-04 2.62-14.14 Theeta and alpha i). Deep meditation/relaxation
ii.) Calm relaxed yet alert state
Table 8. Consolidated frequency range of Vedic chanting
Chanting taken from Specimen No. Min. freq. (Hz) Max. freq. (Hz) Band Brain activity and effect
Atharva Veda AV-01 4.676 12.83 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
AV-03 1 12.57 Delta, theta, and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
iii). Dreamless sleep and loss
of body awareness
AV-07 1 13.74 Delta, theta, and alpha
Rig Veda RV-01 3.952 13.123 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
RV-02 3.952 13.96 Theta and alpha
RV-08 2.11 13.49 Delta, theta, and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
iii). Dreamless sleep and loss
of body awareness
Krishna Yajur Veda KYV-01 1 13.03 Delta, theta, and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
iii). Dreamless sleep and loss
of body awareness
KYV-02 1.8 13.49
KYV-03 2.939 14.04
Sukla Yajur Veda SYV-01 6.638 14.33 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
SYV-02 4.23 13.4
SYV-03 5.156 13.86
Sama Veda SV- 01 8.861 13.4 Alpha Deep meditation/relaxation
SV- 02 7.696 14.51 Alpha
SV- 03 8.583 13.86 Alpha
SV-04 2.62 14.14 Theta and alpha i). Deep meditation/relaxation
ii). Calm relaxed yet alert state
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4. CONCLUSION
A novel methodology has been proposed to identify and compare the frequency range of different
Vedic chantings from Rig Veda, Yajur Veda, Atharva Veda, and Sama Veda. Three selected specimens of
duration 10 min. From each Veda has been processed through the simulation compiler Praat and the
parameters like a spectral response, pitch, intensity, formants, and pulses have been observed. In the above-
identified parameters, the frequency in intensity calculation is taken for each sample. This frequency is
compared with the brainwaves for which the frequencies are in the ranges of 0 to >27 Hz (alpha, beta,
gamma, theta, and delta). The extracted signal frequencies from Vedic chantings are compared with
frequencies of brainwaves. As per the literature, the brainwaves in the frequency range of 8-12 Hz (alpha)
give more relaxation to the human brain. Among the four Vedas, the frequencies extracted from Sama Veda
lies in the alpha frequency range. The remaining Vedic chanting frequencies are fluctuating from the alpha
frequency range and the relaxation rate is varying. So, it is concluded that from the proposed work, by
listening Sama Veda the human brain changes its state from stressed to reclined.
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BIOGRAPHIES OF AUTHORS
Veera Raghava Swamy Nalluri received the M.Sc. degree in Electronics
Nagarjuna University, Guntur in 1995 and the M.Tech. degrees in VLSI Design from
Sathyabama University Chennai in 2009. Currently, he is pursuing Ph.D. in Sathyabama
University, Chennai, Tamil Nadu, India and Associate Professor at the Department of
Elcetronics and Communication Engineering in St.Ann’s College of Engineering and
Technology-Autonomous, Nayunipally, Vetapalem, affiliated to Jawaharlal Nehru
Technological University, Kakinada. His research interests include speech processing. He can
be contacted at email: raghavaswamynv@gmail.com.
Dr. V. J. K. Kishor Sonti is a Professor in Department of ECE, Sathyabama
Institute of Science and Technology with more than 18 years of experience in handling
undergraduate and postgraduate courses in Electronics. He has 3 postgraduate degrees in the
fields of electronics and psychology and Ph.D. in Micro Electronics. Thrice the best faculty
awardee from CTS and Sathyabama University, Erasmus plus grant recipient with international
exposure, Mentor for Change under NITI Ayog-AIM, Author and co-author of 8 book/book
chapters and 1 monograph, 38 research papers in peer-reviewed journals, experienced student
development coordinator, and he is the convener of Institute Innovation Council, Sathyabama
Institute of Science and Technology. With good administrative exposure in student affairs,
motivational speaker, trained Python programmer, multidisciplinary researcher in areas such as
micro-electronics, vedic mathematics, neuroscience and psychology. He can be contacted at
email: kishoresonti.ece@sathyabama.ac.in.
Dr. G. Sundari is the Professor in the Department of Electronics and
Communication Engineering and Director Administration, Sathyabama Institute of Science
and Technology. She is actively involved in Teaching, Research and Administration activities
and served at various capacity for the past twenty-four years at Sathyabama Institute of
Science and Technology. She has done her Ph.D. research in the field of wireless sensor
networks at Sathyabama institute of science and technology and graduated in the year 2011.
She was the Principal Investigator of the Research Project funded by CVRDE, DRDO and has
received grants from AICTE, DST, and TNSCST for conducting short term training program
and National level seminars. She has more than 45 research publications in various
International and national journals and conferences. Her research area of interest includes
wireless sensor networks and image processing. She is presently guiding 5 Ph.D. scholars and
produced 3 Doctorates. She can be contacted at email: director.admin@sathyabama.ac.in.