Cloud-Based Framework for Pain Scale Assessment in NICU- A Primitive Study with Infant Cries

Tejaswini, S; Sriraam, N.; Pradeep, G C M

doi:10.1109/cimca.2018.8739712

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…The authors in Ref. [7] presented a design of an application that utilizes the cry of newborn babies as a pathological tool for the detection of pain. This remote pain detection application is designed on a cloud paradigm.…”

Section: Related Workmentioning

confidence: 99%

Cloud Computing to Fog Computing: A Paradigm Shift

Hassan¹,

Rashad²

2023

Edge Computing - Technology, Management and Integration

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Fog computing scatters the resources throughout the system to provide services close to the edge of the network. This chapter provides an overview of different segments associated with the fog computing paradigm for implementing efficient Internet of Things (IoT) applications. Section 1 provides an overview and motivation behind the provision of healthcare services using cloud and fog computing paradigms. Section 2 provides the literature and research work related to the deployment of healthcare applications using cloud and fog computing architectures. Section 3 provides the architectural design of a fog computing-based remote pain monitoring application. Section 4 provides the simulation parameters and architecture that are arranged for the evaluation of the proposed policy. Finally, Section 5 concludes and discusses the results of simulations obtained on different scales.

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Section: Related Workmentioning

confidence: 99%

Cloud Computing to Fog Computing: A Paradigm Shift

Hassan¹,

Rashad²

2023

Edge Computing - Technology, Management and Integration

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“…Ehealthcare industry is also moving towards providing intelligent medical services to the users near to improve quality of life. Recent work in the provision of medical services using cloud and fog computing paradigm includes remote pain monitoring using cloud paradigm for newly born babies to decrease death ratio in infants [16]. In [17], the authors designed a fall detection application for aged persons using the mobile cloud paradigm and discussed the beneficial aspects of implementation healthcare applications on the said architecture.…”

Section: Related Workmentioning

confidence: 99%

Design of Resource-Aware Load Allocation for Heterogeneous Fog Computing Environments

Hassan

Ahmad

Rehman

et al. 2022

Wireless Communications and Mobile Computing

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The architecture employed by most of the researchers for the deployment of latency-sensitive Internet of Things (IoT) applications is fog computing. Fog computing architecture offers less delay as compared to the cloud computing paradigm by providing resource constraint fog devices close to the edge of the network. Fog nodes process the incoming data by utilizing available resources which reduces the volume of data to be sent to the cloud server. Fog devices having dissimilar processing capabilities are present in a system. The connection of suitable sensor nodes to the parent fog node plays an essential role in achieving the optimum performance of the system. In this paper, we have designed an algorithm that dynamically assigns appropriate sensor devices to fog nodes to achieve a reduction in network utilization and latency. The proposed algorithm estimates the volume of information detected by an edge device from the rate of sensing frequency of the sensor attached to the edge device. The proposed policy while connecting the network nodes takes into account the heterogeneity and processing capability of the devices. Several evaluations are performed on multiple scales for the evaluation of the proposed algorithm. The outcomes of the evaluations confirm the effectiveness of the proposed algorithm in achieving a reduction in network consumption and end-to-end delay.

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“…They designed a fall detection system for elderly people using cloud computing architecture. Tejaswini et al [ 39 ] proposed remote pain monitoring based on cloud architecture for newborn infants to reduce the mortality rate. Infant crying is a pathological tool used as an indicator of pain in this research.…”

Section: Related Workmentioning

confidence: 99%

Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture

Hassan

Ahmad

et al. 2020

Sensors

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The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.

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Cloud-Based Framework for Pain Scale Assessment in NICU- A Primitive Study with Infant Cries

Cited by 8 publications

References 7 publications

Cloud Computing to Fog Computing: A Paradigm Shift

Cloud Computing to Fog Computing: A Paradigm Shift

Design of Resource-Aware Load Allocation for Heterogeneous Fog Computing Environments

Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture

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