Continuous Patient Monitoring with a Patient Centric Agent: A Block Architecture
ABSTRACT
The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications including continuous Remote Patient Monitoring (RPM). However, the complexity of RPM architectures, the size of datasets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier based End-to-End architecture for continuous patient monitoring that has a Patient Centric Agent (PCA) as its center piece. The PCA manages a Blockchain component to preserve privacy when data streaming from body area sensors needs to be stored securely. The PCA based architecture includes a lightweight communication protocol to enforce security of data through different segments of a continuous, real time patient monitoring architecture. The architecture includes the insertion of data into a personal Blockchain to facilitate data sharing ast healthcare professionals and integration into electronic health records while ensuring privacy is maintained. The Blockchain is customized for RPM with modifications that include having the PCA select a Miner to reduce computational effort, enabling the PCA to manage multiple Blockchains for the same patient, and the modification of each block with a prefix tree to minimize energy consumption and incorporate secure transaction payments. Simulation results demonstrate that security and privacy can be enhanced in Remote Patient Monitoring with the PCA based End to End architecture.
EXISTING SYSTEM :
Internet of Things(IoT) applications in the modern healthcare system include devices, services and wireless sensors that detect physiological signs with wearable or ingestible sensors that stream data to remote, and often Cloud based servers. Secure continuous monitoring of patient’s physiological signs has the potential to augment traditional medical practice, particularly in developing countries that have a shortage of healthcare professionals. Remote Patient Monitoring(RPM) involves the integration of physiological data collected with Wearable or Implantable Medical Devices(IMDs), with other data including demographic, health record and geographic location data. The framework advanced in this article, includes Block chain technology embedded into an End to End architecture. Block chain for cryptocurrencies is a shared, authenticated, auditable and tamper-proof distributed database The anonymous properties of a transaction in digital currency address some challenges inherent in patient privacy. But existing Block chain technology in digital currency cannot be applied as is, to IoT based RPM data because of high computational costs and long transaction processing times. RPM data can stream from sensors so rapidly that it cannot be feasibly processed and added to a Block chain in real time resulting in delays might discourage patients from using Block chain. Volunteer miners might also be reluctant to join Block chain networks owing to the large storage and processing requirements.
PROPOSED SYSTEM :
We propose that RPM challenges can be reduced with the inclusion of a Patient Centric Agent(PCA). The Patient Centric Agent(PCA) has oversight over the End to End flow of data. The PCA determines the storage, security and access level required at any point in time. The PCA coordinates different segments of RPM such as patient sensors and devices, Blockchain nodes, and healthcare service provider devices. The PCA determines whether a stream of data should be stored in a Blockchain and manages the process, if so. The PCA executes on a machine with mass memory capacity and high processing power. No studies to date have advanced the notion of embedding Patient Centric Agent with customized Blockchain for RPM. The PCA based End-to-End RPM architecture securely connects a patient’s BSN to healthcare providers through different intermediate devices. It has the following design elements, explained in more detail throughout the article;
1) Two tiers-One tier deals with the stream and storage of data. The second tier, called the Healthcare Control Unit, deals with auditing and key management.
2) A secure communication protocol from BSN to patient’s smart phone and smart phone to the Patient Centric Agent(PCA). This involves a lightweight authentication algorithm that includes dynamically generated sessional symmetric keys to confirm an End to End security as well as consumption of less power. 3) A Block chain customized for RPM. Modifications include: The task of selecting a Miner is left to the PCA so that computational effort is reduced and multiple Block chains can be accommodated. The modification of a block with prefix tree to minimize energy consumption and incorporate secure transaction payments. The architecture advanced here envisages the PCA playing a central role enforcing security, mediating access to relevant electronic health records, storing particularly sensitive RPM data in a distributed manner, and enabling secure payments.
The architecture consists of BSN, Smartphone(Sensor Data Provider), Patient Centric Agent, Blockchain, and Healthcare Provider Interface. There are multiple communication channels from End to End of this architecture such as BSN to Smartphone, Smartphone to PCA, PCA to Blockchain. Every channel requires security against different network attacks such eavesdropping, Sybil, and man in middle. Further, BSN is a power constraint network in eHealthcare architecture. High computational encryption and authentication are not appropriate for BSN network. So, our research focuses on the proposal of lightweight encryption and authentication for BSN to Smartphone channel as well as Smartphone to PCA. Secondly, BSN produces a huge stream of data and needs to perform some pre-processing on data before sending data to Blockchain. Further, the processing rate of a block produced from real-time data might be slower than that of data arrival in Blockchain. Therefore, we focus on the development of an intelligent Patient Centric Agent that coordinates a the BSN and Smartphone. The PCA categorizes patient’s data as eventful and uneventful, defines security level, controls access for patient data and generates alarms during the emergency, nominates miners in Blockchain to optimize the overall energy of the customized Blockchain. Blockchain network confirms the privacy of patient documents, tamper-proof, availability, and guards against a single point of failure. Energy and security analysis of the proposed architecture was done to demonstrate its applicability in continuous health monitoring system.
CONCLUSION:
In this paper, we present a Patient-Centric Agent based healthcare architecture. The architecture consists of BSN, Smartphone(Sensor Data Provider), Patient Centric Agent, Blockchain, and Healthcare Provider Interface. There are multiple communication channels from End to End of this architecture such as BSN to Smartphone, Smartphone to PCA, PCA to Blockchain. Every channel requires security against different network attacks such eavesdropping, Sybil, and man in middle. Further, BSN is a power constraint network in eHealthcare architecture. High computational encryption and authentication are not appropriate for BSN network. So, our research focuses on the proposal of lightweight encryption and authentication for BSN to Smartphone channel as well as Smartphone to PCA. Secondly, BSN produces a huge stream of data and needs to perform some pre-processing on data before sending data to Blockchain. Further, the processing rate of a block produced from real-time data might be slower than that of data arrival in Blockchain. Therefore, we focus on the development of an intelligent Patient Centric Agent that coordinates a the BSN and Smartphone. The PCA categorizes patient’s data as eventful and uneventful, defines security level, controls access for patient data and generates alarms during the emergency, nominates miners in Blockchain to optimize the overall energy of the customized Blockchain. Blockchain network confirms the privacy of patient documents, tamper-proof, availability, and guards against a single point of failure. Energy and security analysis of the proposed architecture was done to demonstrate its applicability in continuous health monitoring system.