Bikash Pradhan - Academia.edu (original) (raw)

Papers by Bikash Pradhan

Research paper thumbnail of Can statistical and entropy-based features extracted from ECG signals efficiently differentiate the cannabis-consuming women population from the non-consumer?

Research paper thumbnail of Investigating the effect of sound in horror clip on the cardiac electrophysiology of young adults using wavelet packet decomposition and machine learning classifiers

Biomedical Engineering Advances

Research paper thumbnail of Automated Detection of Caffeinated Coffee-Induced Short-Term Effects on ECG Signals Using EMD, DWT, and WPD

Nutrients, 2022

The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched... more The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched. In the current study, the occurrence of coffee-induced short-term changes in electrocardiogram (ECG) signals was examined. Further, a machine learning model that can efficiently detect coffee-induced alterations in cardiac activity is proposed. The ECG signals were decomposed using three different joint time–frequency decomposition methods: empirical mode decomposition, discrete wavelet transforms, and wavelet packet decomposition with varying decomposition parameters. Various statistical and entropy-based features were computed from the decomposed coefficients. The statistical significance of these features was computed using Wilcoxon’s signed-rank (WSR) test for significance testing. The results of the WSR tests infer a significant change in many of these parameters after the consumption of coffee (caffeinated). Further, the analysis of the frequency bands of the decomposed coefficie...

Research paper thumbnail of The Internet of Things in Geriatric Healthcare

Journal of Healthcare Engineering, 2021

There is a significant increase in the geriatric population across the globe. With the increase i... more There is a significant increase in the geriatric population across the globe. With the increase in the number of geriatric people and their associated health issues, the need for larger healthcare resources is inevitable. Because of this, healthcare service-providing industries are facing a severe challenge. However, technological advancement in recent years has enabled researchers to develop intelligent devices to deal with the scarcity of healthcare resources. In this regard, the Internet of things (IoT) technology has been a boon for healthcare services industries. It not only allows the monitoring of the health parameters of geriatric patients from a remote location but also lets them live an independent life in a cost-efficient way. The current paper provides up-to-date comprehensive knowledge of IoT-based technologies for geriatric healthcare applications. The study also discusses the current trends, issues, challenges, and future scope of research in the area of geriatric hea...

Research paper thumbnail of Chitosan-Based Gels for Regenerative Medicine Applications

Polysaccharides of Microbial Origin, 2021

Research paper thumbnail of IoT-Based Applications in Healthcare Devices

Journal of Healthcare Engineering, 2021

The last decade has witnessed extensive research in the field of healthcare services and their te... more The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding...

Research paper thumbnail of Analysis of heart rate variability to understand the effect of cannabis consumption on Indian male paddy-field workers

Biomedical Signal Processing and Control, 2020

This paper examines how the interaction between gender, religion, and ethnic differences influenc... more This paper examines how the interaction between gender, religion, and ethnic differences influence the key determinants of individual investment behavior, which are different types of risk taking, luck, overconfidence, happiness, maximization, regret, and trust. We find that in gender-ethnic groups there are significant differences among Malaysian Malay and Malaysian Chinese but not among Malaysian Indian. With regard to gender-religion groups there are significant differences among Malaysian Muslims, Christians, and Buddhists but not among Malaysian Hindus. These gender-ethnic and gender-religion groups differ in range of variables such as luck, maximization, overconfidence, trust and risk. In addition, foreign students living in Malaysia were included in the study and we found that there is significant difference between male and females in term of luck and lifetime income risk.

Research paper thumbnail of Development of a low‐cost food color monitoring system

Color Research & Application, 2020

Research paper thumbnail of Statistical and entropy-based features can efficiently detect the short-term effect of caffeinated coffee on the cardiac physiology

Medical Hypotheses, 2020

An electrocardiograph (ECG) is the most effective way to find the changes in cardiac physiology. ... more An electrocardiograph (ECG) is the most effective way to find the changes in cardiac physiology. It is the representation of the electrical activities of the heart and can be understood using different waves, peaks, and intervals. Several factors affect the functionality of the heart that includes lifestyle, stress, daily diet, etc. Coffee, the most widely consumed beverage in the world, is an integral part of everyday life. Caffeine, the prime constituent of coffee, is believed to affect the heart physiology. However, the effect of consumption of caffeinated coffee on the cardiac electrophysiological changes, estimated from the morphological features (e.g., peaks, waves, intervals), is controversial. This has led to the exploration of other feature extraction methods to detect the changes accurately. In recent years, the statistical and entropy-based features have emerged as an efficient method to extract hidden patterns from the ECG signal. These features have been successfully explored in arrhythmia detection, noise removal, biometric identification, etc. Hence, we hypothesized that the statistical and entropy-based features could be efficiently used in detecting the changes in the ECG signal after coffee consumption. For the evaluation of our hypothesis, 5-sec ECG segments were extracted from the recorded ECG signals from 14 volunteers in pre-and post-coffee consumption conditions. From each segment, the statistical and entropy-based features were computed. Then, the statistically significant features were extracted using Wilcoxon's signed-rank test. The results showed a significant difference in the statistical parameters post-consumption of coffee. Further, to validate our findings, several machine learning models were used for the automatic detection of these changes, and the results show the highest classification accuracy of 75%. The results support our hypothesis that the statistical and entropy-based features can efficiently detect the changes in the ECG signals, which is induced by coffee consumption. The findings of the proposed hypothesis may open up a new research arena of detecting the presence of different drugs and alcohol in the human body by analyzing the ECG signals.

Research paper thumbnail of Dataset for EEG signals used to detect the effect of coffee consumption on the activation of SSVEP signal

Data in Brief, 2020

from six individuals in the presence of seven photic stimuli of different frequencies (range: 3 H... more from six individuals in the presence of seven photic stimuli of different frequencies (range: 3 Hze30 Hz). The EEG data were recorded prior to, and post-consumption of caffeinated coffee for detecting the influence of coffee consumption on the initiation of steady-state visual evoked potential (SSVEP) signals in different regions of the brain. The data supports the article: "Data mining-based approach to study the effect of consumption of caffeinated coffee on the generation of steady-state visual evoked potential signals" [1]. The obtained dataset can also be used to have more insight into the brain response during the post-consumption of coffee using different feature extraction, classification, and SSVEP signal detection techniques.

Research paper thumbnail of Internet-of-Things-Enabled Dual-Channel Iontophoretic Drug Delivery System for Elderly Patient Medication Management

Journal of Medical Devices, 2020

Wireless controllers have found its application in the supervision of the patients in the hospita... more Wireless controllers have found its application in the supervision of the patients in the hospitals. It is not only a valid issue for the developing countries but also for the developed countries. For this reason, scientists are working on the advancement of medical devices that are capable of decreasing the workload of health caregivers. In this study, the development of an iontophoretic drug delivery device that could be controlled using a mobile is described. For the purpose, hardware and a software module were developed. The hardware module consisted of a two-channel voltage-controlled constant current sources that were used for driving the iontophoretic device. A mobile app was developed to control the two-channel iontophoretic device and to monitor the loose lead of the active and the passive patches. In the case of detection of the loose lead, the specific iontophoretic channel was stopped. Further, the audio-visual indicator was developed for the detection of the detachment ...

Research paper thumbnail of Internet of Things and Robotics in Transforming Current-Day Healthcare Services

Journal of Healthcare Engineering, 2021

Technology has become an integral part of everyday lives. Recent years have witnessed advancement... more Technology has become an integral part of everyday lives. Recent years have witnessed advancement in technology with a wide range of applications in healthcare. However, the use of the Internet of Things (IoT) and robotics are yet to see substantial growth in terms of its acceptability in healthcare applications. The current study has discussed the role of the aforesaid technology in transforming healthcare services. The study also presented various functionalities of the ideal IoT-aided robotic systems and their importance in healthcare applications. Furthermore, the study focused on the application of the IoT and robotics in providing healthcare services such as rehabilitation, assistive surgery, elderly care, and prosthetics. Recent developments, current status, limitations, and challenges in the aforesaid area have been presented in detail. The study also discusses the role and applications of the aforementioned technology in managing the current pandemic of COVID-19. A comprehe...

Research paper thumbnail of Can statistical and entropy-based features extracted from ECG signals efficiently differentiate the cannabis-consuming women population from the non-consumer?

Research paper thumbnail of Investigating the effect of sound in horror clip on the cardiac electrophysiology of young adults using wavelet packet decomposition and machine learning classifiers

Biomedical Engineering Advances

Research paper thumbnail of Automated Detection of Caffeinated Coffee-Induced Short-Term Effects on ECG Signals Using EMD, DWT, and WPD

Nutrients, 2022

The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched... more The effect of coffee (caffeinated) on electro-cardiac activity is not yet sufficiently researched. In the current study, the occurrence of coffee-induced short-term changes in electrocardiogram (ECG) signals was examined. Further, a machine learning model that can efficiently detect coffee-induced alterations in cardiac activity is proposed. The ECG signals were decomposed using three different joint time–frequency decomposition methods: empirical mode decomposition, discrete wavelet transforms, and wavelet packet decomposition with varying decomposition parameters. Various statistical and entropy-based features were computed from the decomposed coefficients. The statistical significance of these features was computed using Wilcoxon’s signed-rank (WSR) test for significance testing. The results of the WSR tests infer a significant change in many of these parameters after the consumption of coffee (caffeinated). Further, the analysis of the frequency bands of the decomposed coefficie...

Research paper thumbnail of The Internet of Things in Geriatric Healthcare

Journal of Healthcare Engineering, 2021

There is a significant increase in the geriatric population across the globe. With the increase i... more There is a significant increase in the geriatric population across the globe. With the increase in the number of geriatric people and their associated health issues, the need for larger healthcare resources is inevitable. Because of this, healthcare service-providing industries are facing a severe challenge. However, technological advancement in recent years has enabled researchers to develop intelligent devices to deal with the scarcity of healthcare resources. In this regard, the Internet of things (IoT) technology has been a boon for healthcare services industries. It not only allows the monitoring of the health parameters of geriatric patients from a remote location but also lets them live an independent life in a cost-efficient way. The current paper provides up-to-date comprehensive knowledge of IoT-based technologies for geriatric healthcare applications. The study also discusses the current trends, issues, challenges, and future scope of research in the area of geriatric hea...

Research paper thumbnail of Chitosan-Based Gels for Regenerative Medicine Applications

Polysaccharides of Microbial Origin, 2021

Research paper thumbnail of IoT-Based Applications in Healthcare Devices

Journal of Healthcare Engineering, 2021

The last decade has witnessed extensive research in the field of healthcare services and their te... more The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding...

Research paper thumbnail of Analysis of heart rate variability to understand the effect of cannabis consumption on Indian male paddy-field workers

Biomedical Signal Processing and Control, 2020

This paper examines how the interaction between gender, religion, and ethnic differences influenc... more This paper examines how the interaction between gender, religion, and ethnic differences influence the key determinants of individual investment behavior, which are different types of risk taking, luck, overconfidence, happiness, maximization, regret, and trust. We find that in gender-ethnic groups there are significant differences among Malaysian Malay and Malaysian Chinese but not among Malaysian Indian. With regard to gender-religion groups there are significant differences among Malaysian Muslims, Christians, and Buddhists but not among Malaysian Hindus. These gender-ethnic and gender-religion groups differ in range of variables such as luck, maximization, overconfidence, trust and risk. In addition, foreign students living in Malaysia were included in the study and we found that there is significant difference between male and females in term of luck and lifetime income risk.

Research paper thumbnail of Development of a low‐cost food color monitoring system

Color Research & Application, 2020

Research paper thumbnail of Statistical and entropy-based features can efficiently detect the short-term effect of caffeinated coffee on the cardiac physiology

Medical Hypotheses, 2020

An electrocardiograph (ECG) is the most effective way to find the changes in cardiac physiology. ... more An electrocardiograph (ECG) is the most effective way to find the changes in cardiac physiology. It is the representation of the electrical activities of the heart and can be understood using different waves, peaks, and intervals. Several factors affect the functionality of the heart that includes lifestyle, stress, daily diet, etc. Coffee, the most widely consumed beverage in the world, is an integral part of everyday life. Caffeine, the prime constituent of coffee, is believed to affect the heart physiology. However, the effect of consumption of caffeinated coffee on the cardiac electrophysiological changes, estimated from the morphological features (e.g., peaks, waves, intervals), is controversial. This has led to the exploration of other feature extraction methods to detect the changes accurately. In recent years, the statistical and entropy-based features have emerged as an efficient method to extract hidden patterns from the ECG signal. These features have been successfully explored in arrhythmia detection, noise removal, biometric identification, etc. Hence, we hypothesized that the statistical and entropy-based features could be efficiently used in detecting the changes in the ECG signal after coffee consumption. For the evaluation of our hypothesis, 5-sec ECG segments were extracted from the recorded ECG signals from 14 volunteers in pre-and post-coffee consumption conditions. From each segment, the statistical and entropy-based features were computed. Then, the statistically significant features were extracted using Wilcoxon's signed-rank test. The results showed a significant difference in the statistical parameters post-consumption of coffee. Further, to validate our findings, several machine learning models were used for the automatic detection of these changes, and the results show the highest classification accuracy of 75%. The results support our hypothesis that the statistical and entropy-based features can efficiently detect the changes in the ECG signals, which is induced by coffee consumption. The findings of the proposed hypothesis may open up a new research arena of detecting the presence of different drugs and alcohol in the human body by analyzing the ECG signals.

Research paper thumbnail of Dataset for EEG signals used to detect the effect of coffee consumption on the activation of SSVEP signal

Data in Brief, 2020

from six individuals in the presence of seven photic stimuli of different frequencies (range: 3 H... more from six individuals in the presence of seven photic stimuli of different frequencies (range: 3 Hze30 Hz). The EEG data were recorded prior to, and post-consumption of caffeinated coffee for detecting the influence of coffee consumption on the initiation of steady-state visual evoked potential (SSVEP) signals in different regions of the brain. The data supports the article: "Data mining-based approach to study the effect of consumption of caffeinated coffee on the generation of steady-state visual evoked potential signals" [1]. The obtained dataset can also be used to have more insight into the brain response during the post-consumption of coffee using different feature extraction, classification, and SSVEP signal detection techniques.

Research paper thumbnail of Internet-of-Things-Enabled Dual-Channel Iontophoretic Drug Delivery System for Elderly Patient Medication Management

Journal of Medical Devices, 2020

Wireless controllers have found its application in the supervision of the patients in the hospita... more Wireless controllers have found its application in the supervision of the patients in the hospitals. It is not only a valid issue for the developing countries but also for the developed countries. For this reason, scientists are working on the advancement of medical devices that are capable of decreasing the workload of health caregivers. In this study, the development of an iontophoretic drug delivery device that could be controlled using a mobile is described. For the purpose, hardware and a software module were developed. The hardware module consisted of a two-channel voltage-controlled constant current sources that were used for driving the iontophoretic device. A mobile app was developed to control the two-channel iontophoretic device and to monitor the loose lead of the active and the passive patches. In the case of detection of the loose lead, the specific iontophoretic channel was stopped. Further, the audio-visual indicator was developed for the detection of the detachment ...

Research paper thumbnail of Internet of Things and Robotics in Transforming Current-Day Healthcare Services

Journal of Healthcare Engineering, 2021

Technology has become an integral part of everyday lives. Recent years have witnessed advancement... more Technology has become an integral part of everyday lives. Recent years have witnessed advancement in technology with a wide range of applications in healthcare. However, the use of the Internet of Things (IoT) and robotics are yet to see substantial growth in terms of its acceptability in healthcare applications. The current study has discussed the role of the aforesaid technology in transforming healthcare services. The study also presented various functionalities of the ideal IoT-aided robotic systems and their importance in healthcare applications. Furthermore, the study focused on the application of the IoT and robotics in providing healthcare services such as rehabilitation, assistive surgery, elderly care, and prosthetics. Recent developments, current status, limitations, and challenges in the aforesaid area have been presented in detail. The study also discusses the role and applications of the aforementioned technology in managing the current pandemic of COVID-19. A comprehe...