Jyoti Bali - Academia.edu (original) (raw)

Papers by Jyoti Bali

3C Empresa, Dec 29, 2022

Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adop... more Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adopting intelligent manufacturing practices in view of Industry 4.0 requirements. Intelligent manufacturing is the process of enhancing production through the use of cutting-edge technologies, sensor integration, analytics, and the Internet of Things (IoT). The proposed paper mainly focuses on the study of the scope and the evolution of quality control techniques from conventional practices to intelligent approaches along with the state of art technologies in place. The challenges faced in building intelligent QC systems, in terms of security, system integration, Interoperability, and Humanrobot collaboration, are highlighted. Surface defect detection has evolved as a critical QC application in modern manufacturing setups to ensure high-quality products with high market demand. Further, the recent trends and issues involved in surface defect detection using intelligent QC techniques are discussed. The methodology of implementing surface defect detection on cement wall surfaces using the Haar Cascade Classifier is discussed.

Advanced Prognostic Predictive Modelling in Healthcare Data Analytics, 2021

Journal of Engineering Education Transformations, 2015

AIP Conference Proceedings

2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)

COMPUSOFT: An International Journal of Advanced Computer Technology, Nov 30, 2018

Lecture Notes in Bioengineering, 2021

The socioeconomic development of a nation depends on the health of the citizens, who contribute t... more The socioeconomic development of a nation depends on the health of the citizens, who contribute towards it. Sleep-health is an essential indicator of the well-being of a person. There are many ailments related to heart and brain reported that are caused by problems of lack of sleep, interrupted sleep, and unhygienic sleep conditions. Several sleep-related disorders are affecting people of various age groups, which reduce the quality of life as well as the physical and mental health of the affected person drastically. Awareness about the problem among medical experts and the general public is poor in countries of lower economy, like India. The Polysomnography (PSG), a gold-standard and a popular test is used to detect sleeprelated disorders. PSG requires a sophisticated Sleep-Lab facility and proves costly and hence not affordable by lower sections of society. Under the proposed work, the focus is on the need for creating awareness on the up-keeping of sleep-health and developing a convenient screening tool for sleep apnea. The development issues of an intelligent and cost-efficient screening tool as an alternative to PSG and the feasibility of using the tool at smaller clinical setups are discussed.

469 Abstract -There is lot of need and demand for portable medical equipments consuming ultra low... more 469 Abstract -There is lot of need and demand for portable medical equipments consuming ultra low-power and operating with higher speeds. Medical equipments need to work with higher speeds in order to process digital processing algorithms and consume lowest possible power in order to extend battery life. This paper is to discuss about the various issues in designing the portable, low-power and high-performance Electrocardiogram (ECG) measuring system. The individual blocks of ECG measuring system are namely modules for Power/battery Management, Control/data processing, Sensor interface, Amplification, Analog-to-digital conversion (ADC), User interface/display and Wireless connectivity. The objectives of design for incorporating features of smaller size, improved battery life, lower cost and faster response has to be implemented across each of the modules chosen for building the system. and the designer faces the challenge of extracting a very small ECG signal of amplitude 1 mV prese...

Journal of Engineering Education Transformations, 2017

Here the efforts of ensuring the effectiveness of team based activity planned under the course An... more Here the efforts of ensuring the effectiveness of team based activity planned under the course Analog and Digital Electronics (ADC) involving Peer Assisted Learning are presented. Course concepts can be effectively conveyed to students by solving problems on a regular basis. The course ADC is an important course under Automation&Robotics program providing fundamental concepts which are prerequisites for studying the higher end subjects prescribed under the program. Developing the skill of problem solving and analysis is the critical need of the course. This was taken up as the objective wherein a team based activity was designed for promoting a high level peer to peer interaction involving students from different grades forming a team to solve problems, analyze the result and summarize. The activity was designed to promote cooperative learning environment in turn boosting the confidence level and problem solving ability of students in a phased manner. The challenge was to address th...

This paper is intended to discuss the active learning practices followed for students of Automati... more This paper is intended to discuss the active learning practices followed for students of Automation and Robotics as a course project activity, evolved through a structured literature survey under subjects like Mechatronics System Design [MSD] and Real-Time Embedded Systems [RTES]. Activity-based learning has always proved that it can foster faster learning by students with enhanced skills essential for their engineering career. Thus aiming at increased student participation and effective learning in line with ABET accreditation requirements, a literature survey-based course project activity was introduced to enable students to acquire some of the prominent competencies like designing, identifying, formulating and solving engineering problems, communicating effectively, professional ethics, using modern engineering tools and lifelong learning capability. Thus the activity involved two important steps: (i) Literature survey of papers for the allotted areas in a group of two to three m...

Algorithms for Intelligent Systems, 2019

Sound sleep is an important parameter of health as it is directly related to the health of the he... more Sound sleep is an important parameter of health as it is directly related to the health of the heart as well of the brain and psychological health of the human. Sleep disorder or sleep apnea (SA) hampers the quality of sleep, which drastically affects the individual’s daytime work. Sleep apnea is caused by interruptions in breathing, causing the shortage of oxygen supply to the heart, in turn affecting the pumping action of the heart. Hence, the heart rate reduces, in turn causing bradycardia, i.e., slow heart condition, and this condition of reduced oxygen level in the blood is sensed by the brain that constricts the arteries to pump blood at a faster rate to supply the deficiency of oxygen level. As a result, the heart rate increases temporarily. Thus, the resulted episode of bradycardia followed by tachycardia is referred to be an apnea event. The adverse conditions of repeated apnea events cause continuous episodes of tachycardia. Heart rate is considered to be an important indicator of sleep apnea, and it can be easily captured from the ECG signal study. Hence, we propose the low-power, high-performance methods of analysis of nighttime recordings of ECG signal to note the deviations of ECG parameters in terms of its amplitudes and time segments of its wave components as compared with their ideal values. The proposed methodology comprises steps, namely, preprocessing for noise removal, QRS complex detection, extraction of features based on QRS complex reference, and classification of features using ANN for sleep apnea detection. The methods are tested using a benchmark dataset as well as own dataset of ECG signals. The experimental results are analyzed and validated by medical experts. A typical ECG signal is preprocessed for noise removal using various filter techniques. QRS detection is done by employing methods, namely, Pan–Tompkins method, Hilbert transform, and wavelet transform methods. The 30 typical ECG features are extracted keeping the QRS complex as a reference and are used for sleep apnea detection. Feature reduction is performed using principal component analysis (PCA). The features extracted from QRS complexes occurring in ECG signal recording are classified using ANN. The training algorithms used for training ANN are Levenberg–Marquardt (LM) algorithm and the scaled conjugate gradient (SCG). The performance of the proposed three algorithms is compared, wherein the wavelet transform-based feature extraction method and SCG trained ANN algorithm emerge as the best.

2021 IEEE India Council International Subsections Conference (INDISCON), 2021

An Autonomous mobile robot needs to be equipped with the intelligence of autonomous navigational ... more An Autonomous mobile robot needs to be equipped with the intelligence of autonomous navigational ability in its operating environment. The ability is mainly decided by the way the robot perceives the environment, the way it plans the navigational path to be traversed, and how it executes its motion actuation. While designing the mobile robots, the accurate perception of the environment is taken care of by intelligent sensing modules. Further, the strategy of navigational path planning is implemented by robust algorithms that ensure the shortest path traversal, hence lesser time consumption and efficient obstacle avoidance capability. The choice of a path planning algorithm depends on the needs of the application employing the mobile robot. The level of autonomy of the mobile robot depends on the way the designer exploits the advantages of the path planning algorithm. The proposed work aims at comparing the intricacies of navigational path planning algorithms, namely, Dijkstra's algorithm, Genetic algorithm and A* algorithm, that can be employed for mobile robots. The demonstrational results of navigational path planning implemented using the A* algorithm is presented

Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2, 2017

The work is focused on detection of Obstructive Sleep apnea (OSA), a condition of cessation of br... more The work is focused on detection of Obstructive Sleep apnea (OSA), a condition of cessation of breathing during night sleep caused by blockage of upper respiratory tract in an individual. ElectroCardioGram (ECG) signal is one of the clinically established procedures that can be relied on for deciding on the presence or absence of sleep apnea along with its severity in the subject at an earlier stage, so that the expert can advise for the relevant treatment. Earlier detection of OSA, can avoid the severe consequences leading to hypertension, Atrial-Fibrillation and day-time sleepiness that can affect the patient. ECG signal recordings from Apnea database from Physiobank, MIT website have been used for the purpose. The ECG signal based methods like QRS complex detection, RR interval variability, Respiratory Variability, Heart rate variability parameters used to detect OSA are compared and evaluated in order to select the most accurate method. Here we present the stepwise procedures, results and analysis of implementation methods used for detection of sleep apnea based on ECG signal using robust dataflow programming feature available in LabVIEW2014. Results indicate that accuracy, specificity and sensitivity of Heart Rate based detection method of OSA are 83%, 75% and 88% respectively and thus rated as one of the simple and reliable ways of detecting OSA.

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), 2021

The proposed work focuses on sensor fusion technology for improving the navigation path in the mo... more The proposed work focuses on sensor fusion technology for improving the navigation path in the mobile robot application. The objective here is to discuss the various issues involved, needs, and advantages of the sensor fusion process. State of the art, sensor fusion based algorithms is discussed. The factors, namely, choice of sensor and the algorithm for a mobile robot and implementation methodologies, are presented. The sensors used in the sensor fusion process are an Inertial Measurement Unit(IMU) and Global Positioning System(GPS). The relevance of selecting the Kalman filter-based sensor fusion process and the implementation steps using the different types of sensors is explained with the flow chart and the algorithmic steps. The systematic analysis of the sensor fusion process is carried out using error estimates of position and orientation achieved for the mobile robot application.

2017 International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT), 2017

The paper discusses the issues involved in designing a ECG signal based Obstructive Sleep Apnea (... more The paper discusses the issues involved in designing a ECG signal based Obstructive Sleep Apnea (OSA)Detection system having low power features and improved battery life. The ECG signal parameters required for the analysis in order to detect OSA are gathered from QRS detection process, following Pan Tompkins algorithm. Heart rate is computed from the data gathered and OSA detection process is implemented with the algorithm providing decision as either normal case without any apnea or presence of Obstructive Sleep Apnea. The algorithm is implemented using MSP430 based MSP430FR6989 launch pad having robust low power and high performance features along with the profiling of power and energy consumption of the entire system. We could improve the code in succession by harnessing the ultra low power capabilities of the controller making use of the Tool features like ULP advisor and Energy trace of Code composer Studio(CCS). The use of Low Power Mode 3 (LPM3) of MSP430 device helped us develop the improved power efficiency of the application code for OSA detection system as compared with the use of other power down modes. Also the life of AA battery is drastically improved for the code using LPM3 as compared with that of CR2032 battery. Here we present the profiles of power and energy in the form of graphs and tabulated data for comparison, using which we have developed a power aware system for OSA detection.

Procedia Computer Science, 2020

Peer-review under responsibility of the scientific committee of the 9th World Engineering Educati... more Peer-review under responsibility of the scientific committee of the 9th World Engineering Education Forum 2019.

Journal of Computational and Theoretical Nanoscience, 2020

The proposed work aims at developing a solution for the detection of sleep apnea disorder using E... more The proposed work aims at developing a solution for the detection of sleep apnea disorder using ECG signal analysis, which is an established diagnostic modality. Under this work, the standard research resource, ECG-Apnea database from MIT’s Physionet.org., having ECG signal night time recordings, is used. The sequential procedure of Preprocessing, Peak or QRS complex detection, Feature extraction, Feature reduction, and Classification is used. Preprocessing of the ECG signal is performed to free it from noise resulted from baseline wander, power-line interference, and muscle artifacts. Thus, the improved signal quality is estimated in terms of its Signal to Noise Ratio (SNR) and entropy value. QRS detection is implemented using the popular Pan-Tompkins algorithm that provides the reference for the feature extraction process. The performance of the detection algorithm is measured in terms of the average values of accuracy and specificity as 98% and 96%, respectively. Feature extracti...

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2018

In this paper, a methodology for sleep apnea detection based on ECG signal analysis using Hilbert... more In this paper, a methodology for sleep apnea detection based on ECG signal analysis using Hilbert transform is proposed. The proposed work comprises a sequential procedure of preprocessing, QRS complex detection using Hilbert Transform, feature extraction from the detected QRS complex and the feature reduction using principal component analysis (PCA). Finally, the classification of the ECG signal recordings has been done using two different artificial neural networks (ANN), one trained with Levenberg-Marquardt (LM) algorithm and the other trained with Scaled Conjugate Gradient (SCG) method guided by K means clustering. The result of classification of the input ECG record is as either belonging to Apnea or Normal category. The performance measures of classification using the two classification algorithms are compared. The experimental results indicate that the SCG algorithm guided by K means clustering (ANN-SCG) has outperformed the LM algorithm (ANN-LM) by attaining accuracy, sensit...

Journal of Engineering Education Transformations, 2015

IOP Conference Series: Materials Science and Engineering, 2021

In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) stan... more In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) standard requirements. Energy efficiency is an essential area of focus. In the production setup, the critical and real-time control systems need to be very efficient while implementing functions, namely, accurate sensing, fast processing and precise actuation. Automated Guided vehicles (AGVs) and Automated Guided Vehicles are an integral part of modern and intelligent manufacturing systems. Power consumption in such systems is directly proportional to the performance level achieved. However, there is a need to evolve strategies to reduce power consumption and attain optimal performance. Field Programmable Gate Array(FPGA) based controller solutions can provide competent performance at optimized power consumption. The proposed work discusses the requirements of I4.0 concerning energy efficiency infrastructures for the intelligent manufacturing setup. The need to develop efficient subsystems f...

3C Empresa, Dec 29, 2022

Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adop... more Quality Control (QC) has recently emerged as a significant global trend among manufacturers, adopting intelligent manufacturing practices in view of Industry 4.0 requirements. Intelligent manufacturing is the process of enhancing production through the use of cutting-edge technologies, sensor integration, analytics, and the Internet of Things (IoT). The proposed paper mainly focuses on the study of the scope and the evolution of quality control techniques from conventional practices to intelligent approaches along with the state of art technologies in place. The challenges faced in building intelligent QC systems, in terms of security, system integration, Interoperability, and Humanrobot collaboration, are highlighted. Surface defect detection has evolved as a critical QC application in modern manufacturing setups to ensure high-quality products with high market demand. Further, the recent trends and issues involved in surface defect detection using intelligent QC techniques are discussed. The methodology of implementing surface defect detection on cement wall surfaces using the Haar Cascade Classifier is discussed.

Advanced Prognostic Predictive Modelling in Healthcare Data Analytics, 2021

Journal of Engineering Education Transformations, 2015

AIP Conference Proceedings

2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)

COMPUSOFT: An International Journal of Advanced Computer Technology, Nov 30, 2018

Lecture Notes in Bioengineering, 2021

The socioeconomic development of a nation depends on the health of the citizens, who contribute t... more The socioeconomic development of a nation depends on the health of the citizens, who contribute towards it. Sleep-health is an essential indicator of the well-being of a person. There are many ailments related to heart and brain reported that are caused by problems of lack of sleep, interrupted sleep, and unhygienic sleep conditions. Several sleep-related disorders are affecting people of various age groups, which reduce the quality of life as well as the physical and mental health of the affected person drastically. Awareness about the problem among medical experts and the general public is poor in countries of lower economy, like India. The Polysomnography (PSG), a gold-standard and a popular test is used to detect sleeprelated disorders. PSG requires a sophisticated Sleep-Lab facility and proves costly and hence not affordable by lower sections of society. Under the proposed work, the focus is on the need for creating awareness on the up-keeping of sleep-health and developing a convenient screening tool for sleep apnea. The development issues of an intelligent and cost-efficient screening tool as an alternative to PSG and the feasibility of using the tool at smaller clinical setups are discussed.

469 Abstract -There is lot of need and demand for portable medical equipments consuming ultra low... more 469 Abstract -There is lot of need and demand for portable medical equipments consuming ultra low-power and operating with higher speeds. Medical equipments need to work with higher speeds in order to process digital processing algorithms and consume lowest possible power in order to extend battery life. This paper is to discuss about the various issues in designing the portable, low-power and high-performance Electrocardiogram (ECG) measuring system. The individual blocks of ECG measuring system are namely modules for Power/battery Management, Control/data processing, Sensor interface, Amplification, Analog-to-digital conversion (ADC), User interface/display and Wireless connectivity. The objectives of design for incorporating features of smaller size, improved battery life, lower cost and faster response has to be implemented across each of the modules chosen for building the system. and the designer faces the challenge of extracting a very small ECG signal of amplitude 1 mV prese...

Journal of Engineering Education Transformations, 2017

Here the efforts of ensuring the effectiveness of team based activity planned under the course An... more Here the efforts of ensuring the effectiveness of team based activity planned under the course Analog and Digital Electronics (ADC) involving Peer Assisted Learning are presented. Course concepts can be effectively conveyed to students by solving problems on a regular basis. The course ADC is an important course under Automation&Robotics program providing fundamental concepts which are prerequisites for studying the higher end subjects prescribed under the program. Developing the skill of problem solving and analysis is the critical need of the course. This was taken up as the objective wherein a team based activity was designed for promoting a high level peer to peer interaction involving students from different grades forming a team to solve problems, analyze the result and summarize. The activity was designed to promote cooperative learning environment in turn boosting the confidence level and problem solving ability of students in a phased manner. The challenge was to address th...

This paper is intended to discuss the active learning practices followed for students of Automati... more This paper is intended to discuss the active learning practices followed for students of Automation and Robotics as a course project activity, evolved through a structured literature survey under subjects like Mechatronics System Design [MSD] and Real-Time Embedded Systems [RTES]. Activity-based learning has always proved that it can foster faster learning by students with enhanced skills essential for their engineering career. Thus aiming at increased student participation and effective learning in line with ABET accreditation requirements, a literature survey-based course project activity was introduced to enable students to acquire some of the prominent competencies like designing, identifying, formulating and solving engineering problems, communicating effectively, professional ethics, using modern engineering tools and lifelong learning capability. Thus the activity involved two important steps: (i) Literature survey of papers for the allotted areas in a group of two to three m...

Algorithms for Intelligent Systems, 2019

Sound sleep is an important parameter of health as it is directly related to the health of the he... more Sound sleep is an important parameter of health as it is directly related to the health of the heart as well of the brain and psychological health of the human. Sleep disorder or sleep apnea (SA) hampers the quality of sleep, which drastically affects the individual’s daytime work. Sleep apnea is caused by interruptions in breathing, causing the shortage of oxygen supply to the heart, in turn affecting the pumping action of the heart. Hence, the heart rate reduces, in turn causing bradycardia, i.e., slow heart condition, and this condition of reduced oxygen level in the blood is sensed by the brain that constricts the arteries to pump blood at a faster rate to supply the deficiency of oxygen level. As a result, the heart rate increases temporarily. Thus, the resulted episode of bradycardia followed by tachycardia is referred to be an apnea event. The adverse conditions of repeated apnea events cause continuous episodes of tachycardia. Heart rate is considered to be an important indicator of sleep apnea, and it can be easily captured from the ECG signal study. Hence, we propose the low-power, high-performance methods of analysis of nighttime recordings of ECG signal to note the deviations of ECG parameters in terms of its amplitudes and time segments of its wave components as compared with their ideal values. The proposed methodology comprises steps, namely, preprocessing for noise removal, QRS complex detection, extraction of features based on QRS complex reference, and classification of features using ANN for sleep apnea detection. The methods are tested using a benchmark dataset as well as own dataset of ECG signals. The experimental results are analyzed and validated by medical experts. A typical ECG signal is preprocessed for noise removal using various filter techniques. QRS detection is done by employing methods, namely, Pan–Tompkins method, Hilbert transform, and wavelet transform methods. The 30 typical ECG features are extracted keeping the QRS complex as a reference and are used for sleep apnea detection. Feature reduction is performed using principal component analysis (PCA). The features extracted from QRS complexes occurring in ECG signal recording are classified using ANN. The training algorithms used for training ANN are Levenberg–Marquardt (LM) algorithm and the scaled conjugate gradient (SCG). The performance of the proposed three algorithms is compared, wherein the wavelet transform-based feature extraction method and SCG trained ANN algorithm emerge as the best.

2021 IEEE India Council International Subsections Conference (INDISCON), 2021

An Autonomous mobile robot needs to be equipped with the intelligence of autonomous navigational ... more An Autonomous mobile robot needs to be equipped with the intelligence of autonomous navigational ability in its operating environment. The ability is mainly decided by the way the robot perceives the environment, the way it plans the navigational path to be traversed, and how it executes its motion actuation. While designing the mobile robots, the accurate perception of the environment is taken care of by intelligent sensing modules. Further, the strategy of navigational path planning is implemented by robust algorithms that ensure the shortest path traversal, hence lesser time consumption and efficient obstacle avoidance capability. The choice of a path planning algorithm depends on the needs of the application employing the mobile robot. The level of autonomy of the mobile robot depends on the way the designer exploits the advantages of the path planning algorithm. The proposed work aims at comparing the intricacies of navigational path planning algorithms, namely, Dijkstra's algorithm, Genetic algorithm and A* algorithm, that can be employed for mobile robots. The demonstrational results of navigational path planning implemented using the A* algorithm is presented

Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2, 2017

The work is focused on detection of Obstructive Sleep apnea (OSA), a condition of cessation of br... more The work is focused on detection of Obstructive Sleep apnea (OSA), a condition of cessation of breathing during night sleep caused by blockage of upper respiratory tract in an individual. ElectroCardioGram (ECG) signal is one of the clinically established procedures that can be relied on for deciding on the presence or absence of sleep apnea along with its severity in the subject at an earlier stage, so that the expert can advise for the relevant treatment. Earlier detection of OSA, can avoid the severe consequences leading to hypertension, Atrial-Fibrillation and day-time sleepiness that can affect the patient. ECG signal recordings from Apnea database from Physiobank, MIT website have been used for the purpose. The ECG signal based methods like QRS complex detection, RR interval variability, Respiratory Variability, Heart rate variability parameters used to detect OSA are compared and evaluated in order to select the most accurate method. Here we present the stepwise procedures, results and analysis of implementation methods used for detection of sleep apnea based on ECG signal using robust dataflow programming feature available in LabVIEW2014. Results indicate that accuracy, specificity and sensitivity of Heart Rate based detection method of OSA are 83%, 75% and 88% respectively and thus rated as one of the simple and reliable ways of detecting OSA.

2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), 2021

The proposed work focuses on sensor fusion technology for improving the navigation path in the mo... more The proposed work focuses on sensor fusion technology for improving the navigation path in the mobile robot application. The objective here is to discuss the various issues involved, needs, and advantages of the sensor fusion process. State of the art, sensor fusion based algorithms is discussed. The factors, namely, choice of sensor and the algorithm for a mobile robot and implementation methodologies, are presented. The sensors used in the sensor fusion process are an Inertial Measurement Unit(IMU) and Global Positioning System(GPS). The relevance of selecting the Kalman filter-based sensor fusion process and the implementation steps using the different types of sensors is explained with the flow chart and the algorithmic steps. The systematic analysis of the sensor fusion process is carried out using error estimates of position and orientation achieved for the mobile robot application.

2017 International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT), 2017

The paper discusses the issues involved in designing a ECG signal based Obstructive Sleep Apnea (... more The paper discusses the issues involved in designing a ECG signal based Obstructive Sleep Apnea (OSA)Detection system having low power features and improved battery life. The ECG signal parameters required for the analysis in order to detect OSA are gathered from QRS detection process, following Pan Tompkins algorithm. Heart rate is computed from the data gathered and OSA detection process is implemented with the algorithm providing decision as either normal case without any apnea or presence of Obstructive Sleep Apnea. The algorithm is implemented using MSP430 based MSP430FR6989 launch pad having robust low power and high performance features along with the profiling of power and energy consumption of the entire system. We could improve the code in succession by harnessing the ultra low power capabilities of the controller making use of the Tool features like ULP advisor and Energy trace of Code composer Studio(CCS). The use of Low Power Mode 3 (LPM3) of MSP430 device helped us develop the improved power efficiency of the application code for OSA detection system as compared with the use of other power down modes. Also the life of AA battery is drastically improved for the code using LPM3 as compared with that of CR2032 battery. Here we present the profiles of power and energy in the form of graphs and tabulated data for comparison, using which we have developed a power aware system for OSA detection.

Procedia Computer Science, 2020

Peer-review under responsibility of the scientific committee of the 9th World Engineering Educati... more Peer-review under responsibility of the scientific committee of the 9th World Engineering Education Forum 2019.

Journal of Computational and Theoretical Nanoscience, 2020

The proposed work aims at developing a solution for the detection of sleep apnea disorder using E... more The proposed work aims at developing a solution for the detection of sleep apnea disorder using ECG signal analysis, which is an established diagnostic modality. Under this work, the standard research resource, ECG-Apnea database from MIT’s Physionet.org., having ECG signal night time recordings, is used. The sequential procedure of Preprocessing, Peak or QRS complex detection, Feature extraction, Feature reduction, and Classification is used. Preprocessing of the ECG signal is performed to free it from noise resulted from baseline wander, power-line interference, and muscle artifacts. Thus, the improved signal quality is estimated in terms of its Signal to Noise Ratio (SNR) and entropy value. QRS detection is implemented using the popular Pan-Tompkins algorithm that provides the reference for the feature extraction process. The performance of the detection algorithm is measured in terms of the average values of accuracy and specificity as 98% and 96%, respectively. Feature extracti...

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2018

In this paper, a methodology for sleep apnea detection based on ECG signal analysis using Hilbert... more In this paper, a methodology for sleep apnea detection based on ECG signal analysis using Hilbert transform is proposed. The proposed work comprises a sequential procedure of preprocessing, QRS complex detection using Hilbert Transform, feature extraction from the detected QRS complex and the feature reduction using principal component analysis (PCA). Finally, the classification of the ECG signal recordings has been done using two different artificial neural networks (ANN), one trained with Levenberg-Marquardt (LM) algorithm and the other trained with Scaled Conjugate Gradient (SCG) method guided by K means clustering. The result of classification of the input ECG record is as either belonging to Apnea or Normal category. The performance measures of classification using the two classification algorithms are compared. The experimental results indicate that the SCG algorithm guided by K means clustering (ANN-SCG) has outperformed the LM algorithm (ANN-LM) by attaining accuracy, sensit...

Journal of Engineering Education Transformations, 2015

IOP Conference Series: Materials Science and Engineering, 2021

In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) stan... more In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) standard requirements. Energy efficiency is an essential area of focus. In the production setup, the critical and real-time control systems need to be very efficient while implementing functions, namely, accurate sensing, fast processing and precise actuation. Automated Guided vehicles (AGVs) and Automated Guided Vehicles are an integral part of modern and intelligent manufacturing systems. Power consumption in such systems is directly proportional to the performance level achieved. However, there is a need to evolve strategies to reduce power consumption and attain optimal performance. Field Programmable Gate Array(FPGA) based controller solutions can provide competent performance at optimized power consumption. The proposed work discusses the requirements of I4.0 concerning energy efficiency infrastructures for the intelligent manufacturing setup. The need to develop efficient subsystems f...