Advances in Intelligent Systems and Computing, 2018
This work presents the cloud-assisted secure WBAN for healthcare application. There are various s... more This work presents the cloud-assisted secure WBAN for healthcare application. There are various security issues associated with WBAN, which need to be solved to provide a secure real-time health monitoring system. Through this implementation, the patient’s vital signals can be accessed in a secure manner in real time remotely by sensors and networks without visiting doctor’s clinic or hospital. Here, we provide the cost-effective solution for the transmission of the patient’s health data to doctor with proper confidentiality, authenticity, freshness, and security using cloud computing. In this work, the biosignals of patients and doctors are used to provide authenticity and vital signals are encrypted by using Advanced Encryption Standard (AES) for the secure m-health application. We have experimentally analyzed the average end-to-end delay for secure healthcare application is 14.59 and 19.31 ms in off-peak hours and peak hours respectively. This delay is only 5.84% in off-peak hours and 7.72% in peak hours of permissible delay of 250 ms for medical application.
With rapid and successful advancement in communication technology and semiconductor devices Inter... more With rapid and successful advancement in communication technology and semiconductor devices Internet of Things based smart healthcare is not a concept, but reality. Patients’ vital information sensed by sensing devices is transmitted through heterogeneous communication links to fog/cloud layer for processing, storage, and decision-making or knowledge extraction. Sensitive health data is vulnerable to various security attacks and threats of different levels and impact while getting sensed, are saved or getting transmitted. Off-the-shelf security techniques such as encryption, trust can be applied for privacy and security of data but application-specific demands such as latency/end to end delay in data transmission, additional overhead in terms of computation time, etc., must be taken care of, especially in time-critical healthcare application. This work implements encryption-decryption algorithms and hashing techniques on ECG signals of varying size for secure transmission through co...
International Journal of Biomedical and Clinical Engineering, 2021
Remote health monitoring framework using wireless body area network with ubiquitous support is ga... more Remote health monitoring framework using wireless body area network with ubiquitous support is gaining popularity. However, faulty sensor data may prove to be critical. Hence, faulty sensor detection is necessary in sensor-based health monitoring. In this paper, an artificial neural network (ANN)-based framework for learning about health condition of patients as well as fault detection in the sensors is proposed. This experiment is done based on human cardiac condition monitoring setup. Related physiological parameters have been collected using wearable sensors from different people. These data are then analyzed using ANN for health condition identification and faulty node detection. Libelium MySignals HW (eHealth Medical Development Shield for Arduino) v2 sensors such as ECG sensor, pulse oximeter sensor, and body temperature sensor have been used for data collection and ARDINO UNO R3 as microcontroller device. ANN method detects faulty sensor data with classification accuracy of 9...
Advances in Intelligent Systems and Computing, 2018
Medical body sensor network (MBSN), a three-tier architectural network, has been in wide use on d... more Medical body sensor network (MBSN), a three-tier architectural network, has been in wide use on demand for remote health monitoring and support in both urban and rural areas. Primary concern of such system is security of sensitive health data along with low end-to-end delay and energy consumption among others. This paper implements secure patient data transmission between tier 2 and tier 3 by ensuring confidentiality and integrity. Man-in-middle attack and distributed denial of service attack can be detected based on end-to-end delay in data transmission. Hash-based secret key is used for encryption which is generated using extracted biological information of user at coordinator PDA of MBSN. Using shared extracted biological information, secret key is regenerated at cloud-based medical server for decryption of data. Experimental results show using different symmetric key encryption techniques, maximum end-to-end delay is only 11.82% of 250 ms which is the maximum permissible delay l...
2018 Fifth International Conference on Emerging Applications of Information Technology (EAIT), 2018
Wireless Body Area Network (WBAN) is becoming popular gradually and is showing better performance... more Wireless Body Area Network (WBAN) is becoming popular gradually and is showing better performance in health monitoring. In WBAN nodes are placed on or inside human body that collect information and send them to remote server wirelessly. Strict security is required to protect patient’s personal data. In this paper we made a detailed survey of the state-of-the art security works in WBAN. We propose a security framework by applying Advanced Encryption Standard (AES) technique using secret key derived from biological data of the patients as well as doctors for ensuring data confidentiality and authentication of users. We have implemented our proposed method in a cloud based environment to analyze end-to-end delay of patient data transmission using different keys derived from different biological information of users. Simulation setup and experimental results are given for detailed view and better understanding of our work.
Sensor-based health data collection, remote access to health data to render real-time advice have... more Sensor-based health data collection, remote access to health data to render real-time advice have been the key advantages of smart and remote healthcare. Such health monitoring and support are getting immensely popular among both patients and doctors as it does not require physical movement which is always not possible for elderly people who lives mostly alone in current socio-economic situations. Healthcare Informatics plays a key role in such circumstances. The huge amount of raw data emanating from sensors needs to be processed applying machine learning and deep learning algorithms for useful information extraction to develop an intelligent knowledge base for providing an appropriate solution as and when required. The real challenge lies in data storage and retrieval preserving security, privacy, reliability and availability requirements. Health data saved in Electronic medical record (EMR) is generally saved in a client-server database where central coordinator does access contr...
This work presents the cloud-assisted secure WBAN for healthcare application. There are various s... more This work presents the cloud-assisted secure WBAN for healthcare application. There are various security issues associated with WBAN, which need to be solved to provide a secure real-time health monitoring system. Through this implementation, the patient’s vital signals can be accessed in a secure manner in real time remotely by sensors and networks without visiting doctor’s clinic or hospital. Here, we provide the cost-effective solution for the transmission of the patient’s health data to doctor with proper confidentiality, authenticity, freshness, and security using cloud computing. In this work, the biosignals of patients and doctors are used to provide authenticity and vital signals are encrypted by using Advanced Encryption Standard (AES) for the secure m-health application. We have experimentally analyzed the average end-to-end delay for secure healthcare application is 14.59 and 19.31 ms in off-peak hours and peak hours respectively. This delay is only 5.84% in off-peak hours and 7.72% in peak hours of permissible delay of 250 ms for medical application.
In India, the first confirmed case of novel corona virus (COVID-19) was discovered on 30 January,... more In India, the first confirmed case of novel corona virus (COVID-19) was discovered on 30 January, 2020. The number of confirmed cases is increasing day by day and it crossed 21,53,010 on 09 August, 2020. In this paper a hybrid forecasting model has been proposed to determine the number of confirmed cases for upcoming 10 days based on the earlier confirmed cases found in India. The proposed modelis based on adaptive neuro-fuzzy inference system (ANFIS) and mutation based Bees Algorithm (mBA). ThemetaheuristicBees Algorithm (BA) has been modified applying 4 types of mutation and Mutation based Bees Algorithm (mBA) is applied to enhance the performance of ANFIS by optimizing its parameters. Proposed mBA-ANFIS model has been assessed using COVID-19 outbreak dataset for India and USAand the number of confirmed cases in next 10 days in Indiahas been forecasted. Proposed mBA-ANFIS model has been compared to standard ANFIS model as well as other hybrid models such as GA-ANFIS, DE-ANFIS, HS-...
Wearable or implantable sensor based remote health monitoring and support systems are gaining hug... more Wearable or implantable sensor based remote health monitoring and support systems are gaining huge popularity because of its accuracy, affordability, mobility support and remote nature. For seamless monitoring, energy efficiency of Medical Body Sensor Network (MBSN) must be high to stretch out network lifetime. For single hop MBSN with STAR topology, sensor nodes send signal directly to the sink node whereas in multi-hop MBSN sensor nodes may act as a forwarder besides data acquisition. This drain out energy of sensor nodes in concern rapidly in case of repeated data forwarding which causes death of node, break of a route or path between sources and sink leading to unsuccessful data transmission. If it is a critical data then it may have life threatening impact on patient. Exclusive forwarder nodes, termed as relay node may be deployed in convenient positions inside the network for intelligent routing which will reduce burden of sensor nodes in terms of energy consumption. Here the nodes considered in the network are divided into different clusters. Relay nodes are placed at the position of cluster heads applying k- means algorithm which analyzes effectiveness of this framework in terms of energy efficiency. Comparison of energy consumptions in three different routing scenarios are considered: through relay node only, direct source to sink without relay node and using shortest path between source to sink irrespective of relay node position. The simulation results show that for varying network configurations in terms of number and position of nodes on human body, scenario of routing with relay nodes only proves to be energy efficient in comparison.
IoT based applications such as smart healthcare, transportation, surveillance etc. lead to more c... more IoT based applications such as smart healthcare, transportation, surveillance etc. lead to more convenient and healthy lifestyle to human being nowadays. Biosensors sense health vitals and send acquired data to cloud server for processing. These huge sensory health data need to be processed and analyzed efficiently and intelligently for knowledge extraction with high accuracy and low resource requirements. Here comes the inevitable role of artificial intelligence, machine learning and deep learning. Here a comprehensive study and analysis on application of IoT and AI in smart healthcare has been done to present recent developments in this emerging research domain supported with few case studies. Issues and challenges in dealing with big health data applying data science and data analytics have also been highlighted. Case studies help to get insight in recent developments on drug discovery, chronic disease prediction such as heart disease, kidney related ailments etc. applying ML, DL.
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Advances in Intelligent Systems and Computing, 2018
This work presents the cloud-assisted secure WBAN for healthcare application. There are various s... more This work presents the cloud-assisted secure WBAN for healthcare application. There are various security issues associated with WBAN, which need to be solved to provide a secure real-time health monitoring system. Through this implementation, the patient’s vital signals can be accessed in a secure manner in real time remotely by sensors and networks without visiting doctor’s clinic or hospital. Here, we provide the cost-effective solution for the transmission of the patient’s health data to doctor with proper confidentiality, authenticity, freshness, and security using cloud computing. In this work, the biosignals of patients and doctors are used to provide authenticity and vital signals are encrypted by using Advanced Encryption Standard (AES) for the secure m-health application. We have experimentally analyzed the average end-to-end delay for secure healthcare application is 14.59 and 19.31 ms in off-peak hours and peak hours respectively. This delay is only 5.84% in off-peak hours and 7.72% in peak hours of permissible delay of 250 ms for medical application.
With rapid and successful advancement in communication technology and semiconductor devices Inter... more With rapid and successful advancement in communication technology and semiconductor devices Internet of Things based smart healthcare is not a concept, but reality. Patients’ vital information sensed by sensing devices is transmitted through heterogeneous communication links to fog/cloud layer for processing, storage, and decision-making or knowledge extraction. Sensitive health data is vulnerable to various security attacks and threats of different levels and impact while getting sensed, are saved or getting transmitted. Off-the-shelf security techniques such as encryption, trust can be applied for privacy and security of data but application-specific demands such as latency/end to end delay in data transmission, additional overhead in terms of computation time, etc., must be taken care of, especially in time-critical healthcare application. This work implements encryption-decryption algorithms and hashing techniques on ECG signals of varying size for secure transmission through co...
International Journal of Biomedical and Clinical Engineering, 2021
Remote health monitoring framework using wireless body area network with ubiquitous support is ga... more Remote health monitoring framework using wireless body area network with ubiquitous support is gaining popularity. However, faulty sensor data may prove to be critical. Hence, faulty sensor detection is necessary in sensor-based health monitoring. In this paper, an artificial neural network (ANN)-based framework for learning about health condition of patients as well as fault detection in the sensors is proposed. This experiment is done based on human cardiac condition monitoring setup. Related physiological parameters have been collected using wearable sensors from different people. These data are then analyzed using ANN for health condition identification and faulty node detection. Libelium MySignals HW (eHealth Medical Development Shield for Arduino) v2 sensors such as ECG sensor, pulse oximeter sensor, and body temperature sensor have been used for data collection and ARDINO UNO R3 as microcontroller device. ANN method detects faulty sensor data with classification accuracy of 9...
Advances in Intelligent Systems and Computing, 2018
Medical body sensor network (MBSN), a three-tier architectural network, has been in wide use on d... more Medical body sensor network (MBSN), a three-tier architectural network, has been in wide use on demand for remote health monitoring and support in both urban and rural areas. Primary concern of such system is security of sensitive health data along with low end-to-end delay and energy consumption among others. This paper implements secure patient data transmission between tier 2 and tier 3 by ensuring confidentiality and integrity. Man-in-middle attack and distributed denial of service attack can be detected based on end-to-end delay in data transmission. Hash-based secret key is used for encryption which is generated using extracted biological information of user at coordinator PDA of MBSN. Using shared extracted biological information, secret key is regenerated at cloud-based medical server for decryption of data. Experimental results show using different symmetric key encryption techniques, maximum end-to-end delay is only 11.82% of 250 ms which is the maximum permissible delay l...
2018 Fifth International Conference on Emerging Applications of Information Technology (EAIT), 2018
Wireless Body Area Network (WBAN) is becoming popular gradually and is showing better performance... more Wireless Body Area Network (WBAN) is becoming popular gradually and is showing better performance in health monitoring. In WBAN nodes are placed on or inside human body that collect information and send them to remote server wirelessly. Strict security is required to protect patient’s personal data. In this paper we made a detailed survey of the state-of-the art security works in WBAN. We propose a security framework by applying Advanced Encryption Standard (AES) technique using secret key derived from biological data of the patients as well as doctors for ensuring data confidentiality and authentication of users. We have implemented our proposed method in a cloud based environment to analyze end-to-end delay of patient data transmission using different keys derived from different biological information of users. Simulation setup and experimental results are given for detailed view and better understanding of our work.
Sensor-based health data collection, remote access to health data to render real-time advice have... more Sensor-based health data collection, remote access to health data to render real-time advice have been the key advantages of smart and remote healthcare. Such health monitoring and support are getting immensely popular among both patients and doctors as it does not require physical movement which is always not possible for elderly people who lives mostly alone in current socio-economic situations. Healthcare Informatics plays a key role in such circumstances. The huge amount of raw data emanating from sensors needs to be processed applying machine learning and deep learning algorithms for useful information extraction to develop an intelligent knowledge base for providing an appropriate solution as and when required. The real challenge lies in data storage and retrieval preserving security, privacy, reliability and availability requirements. Health data saved in Electronic medical record (EMR) is generally saved in a client-server database where central coordinator does access contr...
This work presents the cloud-assisted secure WBAN for healthcare application. There are various s... more This work presents the cloud-assisted secure WBAN for healthcare application. There are various security issues associated with WBAN, which need to be solved to provide a secure real-time health monitoring system. Through this implementation, the patient’s vital signals can be accessed in a secure manner in real time remotely by sensors and networks without visiting doctor’s clinic or hospital. Here, we provide the cost-effective solution for the transmission of the patient’s health data to doctor with proper confidentiality, authenticity, freshness, and security using cloud computing. In this work, the biosignals of patients and doctors are used to provide authenticity and vital signals are encrypted by using Advanced Encryption Standard (AES) for the secure m-health application. We have experimentally analyzed the average end-to-end delay for secure healthcare application is 14.59 and 19.31 ms in off-peak hours and peak hours respectively. This delay is only 5.84% in off-peak hours and 7.72% in peak hours of permissible delay of 250 ms for medical application.
In India, the first confirmed case of novel corona virus (COVID-19) was discovered on 30 January,... more In India, the first confirmed case of novel corona virus (COVID-19) was discovered on 30 January, 2020. The number of confirmed cases is increasing day by day and it crossed 21,53,010 on 09 August, 2020. In this paper a hybrid forecasting model has been proposed to determine the number of confirmed cases for upcoming 10 days based on the earlier confirmed cases found in India. The proposed modelis based on adaptive neuro-fuzzy inference system (ANFIS) and mutation based Bees Algorithm (mBA). ThemetaheuristicBees Algorithm (BA) has been modified applying 4 types of mutation and Mutation based Bees Algorithm (mBA) is applied to enhance the performance of ANFIS by optimizing its parameters. Proposed mBA-ANFIS model has been assessed using COVID-19 outbreak dataset for India and USAand the number of confirmed cases in next 10 days in Indiahas been forecasted. Proposed mBA-ANFIS model has been compared to standard ANFIS model as well as other hybrid models such as GA-ANFIS, DE-ANFIS, HS-...
Wearable or implantable sensor based remote health monitoring and support systems are gaining hug... more Wearable or implantable sensor based remote health monitoring and support systems are gaining huge popularity because of its accuracy, affordability, mobility support and remote nature. For seamless monitoring, energy efficiency of Medical Body Sensor Network (MBSN) must be high to stretch out network lifetime. For single hop MBSN with STAR topology, sensor nodes send signal directly to the sink node whereas in multi-hop MBSN sensor nodes may act as a forwarder besides data acquisition. This drain out energy of sensor nodes in concern rapidly in case of repeated data forwarding which causes death of node, break of a route or path between sources and sink leading to unsuccessful data transmission. If it is a critical data then it may have life threatening impact on patient. Exclusive forwarder nodes, termed as relay node may be deployed in convenient positions inside the network for intelligent routing which will reduce burden of sensor nodes in terms of energy consumption. Here the nodes considered in the network are divided into different clusters. Relay nodes are placed at the position of cluster heads applying k- means algorithm which analyzes effectiveness of this framework in terms of energy efficiency. Comparison of energy consumptions in three different routing scenarios are considered: through relay node only, direct source to sink without relay node and using shortest path between source to sink irrespective of relay node position. The simulation results show that for varying network configurations in terms of number and position of nodes on human body, scenario of routing with relay nodes only proves to be energy efficient in comparison.
IoT based applications such as smart healthcare, transportation, surveillance etc. lead to more c... more IoT based applications such as smart healthcare, transportation, surveillance etc. lead to more convenient and healthy lifestyle to human being nowadays. Biosensors sense health vitals and send acquired data to cloud server for processing. These huge sensory health data need to be processed and analyzed efficiently and intelligently for knowledge extraction with high accuracy and low resource requirements. Here comes the inevitable role of artificial intelligence, machine learning and deep learning. Here a comprehensive study and analysis on application of IoT and AI in smart healthcare has been done to present recent developments in this emerging research domain supported with few case studies. Issues and challenges in dealing with big health data applying data science and data analytics have also been highlighted. Case studies help to get insight in recent developments on drug discovery, chronic disease prediction such as heart disease, kidney related ailments etc. applying ML, DL.
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