Modern Healthcare Applications Research Articles

Retracted: A Mathematical Queuing Model Analysis Using Secure Data Authentication Framework for Modern Healthcare Applications

Retracted: A Mathematical Queuing Model Analysis Using Secure Data Authentication Framework for Modern Healthcare Applications

The promise of digital healthcare technologies.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

Blockchain-Enabled IoT for Rural Healthcare: Hybrid-Channel Communication with Digital Twinning

Internet of Things (IoT) and blockchains are enabling technologies for modern healthcare applications, offering the improved monitoring of patient health and higher data integrity guarantees. However, in rural settings, communication reliability can pose a challenge that constrains real-time data usage. Additionally, the limited computation and communication resources of IoT sensors also means that they may not participate directly in blockchain transactions, reducing trust. This paper proposes a solution to these challenges, enabling the use of blockchain-based IoT healthcare devices in low-bandwidth rural areas. This integrated system, named hybrid channel healthcare chain (HC2), uses two communication channels: short-range communication for device authorisation and bulk data transfer, and long-range the radio for light-weight monitoring and event notifications. Both channels leverage the same cryptographic identity information, and through the use of a cloud-based digital twin, the IoT device is able to sign its own transactions, without disclosing the key to said twin. Patient data are encrypted end to end between the IoT device and data store, with the blockchain providing a reliable record of the data lifecycle. We contribute a model, analytic evaluation and proof of concept for the HC2 system that demonstrates its suitability for the stated scenarios by reducing the number of long-range radio packets needed by 87× compared to a conventional approach.

Aligning Semantic Interoperability Frameworks with the FOXS Stack for FAIR Health Data.

FAIR Guiding Principles present a synergy with the use cases for digital health records, in that clinical data need to be found, accessible within a range of environments, and data must interoperate between systems and subsequently reused. The use of HL7 FHIR, openEHR, IHE XDS, and SNOMED CT (FOXS) together represents a specification to create an open digital health platform for modern health care applications. To describe where logical FOXS components align to the European Open Science Cloud Interoperability Framework (EOSC-IF) reference architecture for semantic interoperability. This should provide a means of defining if FOXS aligns to FAIR principles and to establish the data models and structures that support longitudinal care records as being fit to underpin scientific research. The EOSC-IF Semantic View is a representation of semantic interoperability where meaning is preserved between systems and users. This was analyzed and cross-referenced with FOXS architectural components, mapping concepts, and objects that describe content such as catalogues and semantic artifacts. Majority of conceptual Semantic View components were featured within the FOXS architecture. Semantic Business Objects are composed of a range of elements such as openEHR archetypes and templates, FHIR resources and profiles, SNOMED CT concepts, and XDS document identifiers. Semantic Functional Content comprises catalogues of metadata that were also supported by openEHR and FHIR tools. Despite some elements of EOSC-IF being vague (e.g., FAIR Digital Object), there was a broad conformance to the framework concepts and the components of a FOXS platform. This work supports a health-domain-specific view of semantic interoperability and how this may be achieved to support FAIR data for health research via a standardized framework.

E2EGI: End-to-End Gradient Inversion in Federated Learning.

A plethora of healthcare data is produced every day due to the proliferation of prominent technologies such as Internet of Medical Things (IoMT). Digital-driven smart devices like wearable watches, wristbands and bracelets are utilized extensively in modern healthcare applications. Mining valuable information from the data distributed at the owners' level is useful, but it is challenging to preserve data privacy. Federated learning (FL) has swiftly surged in popularity due to its efficacy in dealing privacy vulnerabilities. Recent studies have demonstrated that Gradient Inversion Attack (GIA) can reconstruct the input data by leaked gradients, previous work demonstrated the achievement of GIA in very limited scenarios, such as the label repetition rate of the target sample being low and batch sizes being smaller than 48. In this paper, a novel method of End-to-End Gradient Inversion (E2EGI) is proposed. Compared to the state-of-the-art method, E2EGI's Minimum Loss Combinatorial Optimization (MLCO) has the ability to realize reconstructed samples with higher similarity, and the Distributed Gradient Inversion algorithm can implement GIA with batch sizes of 8 to 256 on deep network models (such as ResNet-50) and ImageNet datasets. A new Label Reconstruction algorithm is developed that relies only on the gradient information of the target model, which can achieve a label reconstruction accuracy of 81% in one batch sample with a label repetition rate of 96%, a 27% improvement over the state-of-the-art method. This proposed work can underpin data security assessments for healthcare federated learning.

Rubus Capped Zinc Oxide Nanoparticles Induce Apoptosis in MCF-7 Breast Cancer Cells.

Rubus fairholmianus (RF) has widely been used to treat various ailments, including pain, diabetes, and cancer. Zinc oxide nanoparticles (ZnO NPs) have drawn attention in modern healthcare applications. Hence, we designed this study to synthesize zinc oxide (ZnO) nanoparticles using R. fairholmianus root extract to investigate its synergistic cytotoxic effect on MCF-7 cells and explore the possible cell death mechanism. ZnO NPs were synthesized via green synthesis using R. fairholmianus root extract, and the effect on MCF-7 cells was determined by looking at cellular morphology, proliferation, cytotoxicity, apoptosis, and reactive oxygen species (ROS). The results showed that cellular proliferation was reduced following treatment with R. fairholmianus capped zinc oxide nanoparticles (RFZnO NPs), while cytotoxicity and ROS were increased. There was also an increase in apoptosis as indicated by the significant increase in cytoplasmic cytochrome c and caspase 3/7 (markers of apoptosis), as well as increased levels of pro-apoptotic proteins (p53, Bax) and decreased levels of anti-apoptotic protein (Bcl-2). In conclusion, these results showed that RFZnO NPs induce apoptosis in breast cancer cells via a mitochondria-mediated caspase-dependent apoptotic pathway and suggest the use of acetone root extract of R. fairholmianus for the treatment of cancer-related ailments.

Energy­efficient technologies in the Internet of Things (IoT)

The internet of things (IoT) has a significant economic and environmental impact owing to the billions or trillions of interconnected devices that use various types of sensors to communicate through the internet. It is well recognized that each sensor requires a small amount of energy to function; but, with billions of sensors, energy consumption can be significant. Therefore, it is crucial to focus on developing energy-efficient IoT technology and sustainable solutions. The contribution of this article is to support the implementation of eco-friendly IoT solutions by presenting a thorough examination of energy-efficient practices and strategies for IoT to assist in the advancement of sustainable and energy-efficient IoT technologies in the future. Four framework principles for achieving this are discussed, including (i) energy-efficient machine-to-machine (M2M) communications, (ii) energy-efficient and eco-sustainable wireless sensor networks (WSN), energy-efficient radio-frequency identification (RFID), and energy-efficient microcontroller units and integrated circuits (IC). This review aims to contribute to the next-generation implementation of eco-sustainable and energy-efficient IoT technologies. The internet of things (IoT) is a revolutionary technology driving telecommunications advancements and improving people’s quality of life worldwide. The IoT also has the potential to boost the global economy significantly. It is anticipated that the global economic impact of the IoT will be between USD 2.7 trillion and 6.2 trillion by 2025 due to IoT devices that are a critical component of emerging applications and play a central role in the widespread adoption of machine type communications. According to experts, the IoT has the potential to revolutionize different smart zones including modern healthcare applications, smart homes and smart cities

A CSI-Based Human Activity Recognition Using Deep Learning.

The Internet of Things (IoT) has become quite popular due to advancements in Information and Communications technologies and has revolutionized the entire research area in Human Activity Recognition (HAR). For the HAR task, vision-based and sensor-based methods can present better data but at the cost of users’ inconvenience and social constraints such as privacy issues. Due to the ubiquity of WiFi devices, the use of WiFi in intelligent daily activity monitoring for elderly persons has gained popularity in modern healthcare applications. Channel State Information (CSI) as one of the characteristics of WiFi signals, can be utilized to recognize different human activities. We have employed a Raspberry Pi 4 to collect CSI data for seven different human daily activities, and converted CSI data to images and then used these images as inputs of a 2D Convolutional Neural Network (CNN) classifier. Our experiments have shown that the proposed CSI-based HAR outperforms other competitor methods including 1D-CNN, Long Short-Term Memory (LSTM), and Bi-directional LSTM, and achieves an accuracy of around 95% for seven activities.

Evaluation of Induced Apoptosis by Biosynthesized Zinc Oxide Nanoparticles in MCF-7 Breast Cancer Cells Using Bak1 and Bclx Expression.

Zinc oxide nanoparticles (ZnO NPs) have peaked interests in many researches in these recent years due to their advantageous application in modern health care applications. Therefore, we successfully synthesized ZnO NPs by Acacia luciana flower extract as stabilizing, reducing and capping agent, to investigate the antiproliferative potential and apoptosis induction in breast cancer cell lines. The involvements of Acacia luciana bioactive compounds in the stabilization of the ZnO NPs were confirmed by FTIR analysis. FESEM and EDS instruments confirmed that biosynthesized nanoparticles have an irregular morphology and mostly composed of Zn, C, and O respectively. The TEM and zeta potential instruments confirmed that biosynthesized nanoparticles have slight negative charges with particle size of 40 nm. The survivorship of MCF-7 cells were examined by MTT assay and revealed that ZnO NPs inhibited cell viability in a dose- and time-dependent effect with IC50 value of 3.1 µg/mL after 72 h exposure. Also, as a novel work onto ZnO NPs obtained by Acacia extracts, the Bak1/Bclx expression ratio was elucidated utilizing RT-PCR technique. The results demonstrated that ZnO NPs could enhance the expression ratio; therefore they have the potential to induce apoptosis in breast cancer cells via mitochondria-mediated apoptotic pathway.

Synthesis and Apoptotic Efficacy of Biosynthesized Silver Nanoparticles Using Acacia luciana Flower Extract in MCF-7 Breast Cancer Cells: Activation of Bak1 and Bclx for Cancer Therapy

Due to unique properties of green silver nanoparticles, especially chemical and biological properties, they are one of the most used metallic nanoparticles in modern healthcare applications. Accordingly, we synthesized Ag-NPs using Acacia luciana as a reducing and stabilizing agent, to elucidate its apoptosis inducing ability in MCF-7 cancer cells. The Ag-NPs were characterized using FTIR and FESEM. These instruments confirmed that biosynthesized nanoparticles are rod-shaped with average size of 50 nm and negative surface charge of 2.59 mV. The in vitro anticancer effects using MTT assay revealed that the Ag-NPs showed inhibition of cell survival in a time and dose-dependent manner with IC50 value of 4.37 mg/mL. Also, the expression of pro- and antiapoptotic genes was measured using real-time PCR. The results hinted that Ag-NPs can significantly increase the Bak1/Bclx ratios through the change in mitochondrial membrane permeability and be used as a therapeutic agent breast cancer cells.

An Improved Authentication Protocol for Wireless Body Sensor Networks Applied in Healthcare Applications

Wireless body sensor networks are now very popular for modern healthcare applications like health monitoring, remote healthcare, emergency healthcare etc. This healthcare application mainly used for constant monitoring of health specific data while doing regular activities. The wireless body area network is consisted of small wearing sensors which are implanted in human body for capturing medical data and send to a medical server through a network connector to base station. A major issue is secure transmission of patient’s medical healthcare information to the medical server through wireless communication. Also the data collected in this network is very sensitive because on the basis of this clinical data, further treatment will be occurred. Therefore, security requirements such as confidentiality, integrity, authenticity should be guaranteed during communication. This paper proposes a strong mutual authentication protocol based on public key cryptography for satisfying all security requirements. The proposed authentication approach resists the major vulnerable attacks in wireless body sensor networks with low computational and communicational load.

Technological improvement in modern health care applications using Internet of Things (IoT) and proposal of novel health care approach

Purpose With the development of emerging engineering technology and industrialization, there are greater changes in the life style of people in smart urban cities; therefore, there is also more chance of various health problems in urban areas. The life style of persons in metro urban areas with the expansive volume of population is similarly influenced by different application and administration frameworks. These are affecting the human health system up to an extended extent and there are more health-related issues and health hazard concerns that can be identified in urban areas. The purpose of this paper is to present an analytical study on various aspects of the smart health care system in a smart perspective by analyzing them with respect to emerging engineering technologies such as mobile network, cloud computing, Internet of Things (IoT), big data analytics and ubiquitous computing. This paper also carries out a detailed survey of health issues and improved solutions in automated systems using these technologies. Second, the paper also presents a novel health care system using smart and safe ambulances and their appropriate control at traffic points with safety and security features in a smart city, so that the valuable life of patients can be saved in time by immediate treatment in nearest hospital or health care units. Design/methodology/approach In this paper, an analytical survey was conducted for improvement in the health care sector using computer technology and IoT-based various modern health care applications. An idea of Smart Health Care Hospital using sensors, mobile agent smart vehicle configuration and safety traffic control for ambulance was proposed. Findings A simulation was carried out to see the performance of a safety mechanism in the proposed approach. Comparative analysis was carried out with other approaches to know the execution time, response time and probable delay due to the implementation of this approach. Originality/value It is an original research work with motivation inspired from current emergent technology to apply in the health care system.

Co-placement optimization in sensor-reusable cyber-physical digital microfluidic biochips

Digital microfluidic biochips (DMFBs) facilitate modern healthcare applications. One of the most important applications is point-of-care (POC) clinical diagnosis which is directly related to human health. However, biochemical experiments are usually error-prone, which makes monitoring intermediate results during bioassay execution be required to ensure the correctness of POC clinical diagnosis. To tackle this problem, cyber-physical digital microfluidic biochips with integrated sensors have been proposed and have attracted attention recently. In order to fully utilize the sensors for detection, the reusability of sensors should be taken into consideration during the module placement stage of cyber-physical DMFBs synthesis flow. Moreover, excessive actuation of electrodes may cause reliability degradation and this issuse should also be taken care of during module placement stage. In order to deal with the aforementioned problems, this paper presents the first co-optimization method for both module and sensor placement. Experimental results show that the proposed method can effectively minimize bioassay completion time while meeting all constraints from sensors and electrodes.

Preparation and efficacy assessment of malva nut polysaccharide for skin hydrating products

Scaphium scaphigerum or malva nut has long been served in Chinese medicine. However, the use of this herb in modern health care applications has, to date, been rarely reported. Maceration of the herb in water afforded malva nut polysaccharide which was standardized. Safety and skin hydrating efficacy of the polysaccharide and products were evaluated in human volunteers. Malva nut polysaccharide (41.71±0.64%) having 36.58±0.51% total sugar content was isolated, with further analysis quantifying ash, carbohydrate, reducing sugar and moisture contents to be 6.05±0.00, 40.06±1.00, 12.20±0.05 and 12.64±0.31%, respectively. The polysaccharide exhibited swelling and hydrating capacities of 0.46±0.01% and 54.46±0.02g/g, with L*, a* and b* of 52.56±0.04, 9.02±0.06 and 18.42±0.03, respectively, and a viscosity of 1263.00±2.00 cps. Accelerated testing indicated the biopolysaccharide to be stable, resulting in no skin irritation in 15 human volunteers. The skin hydrating efficacy as assessed via a randomized single-blind, placebo-controlled study in 24 volunteers highlighted the superior performance of malva nut over the vehicle (moisture retainment for 70min as examined by Corneometer® CM 825). A stable skin moisturizing gel containing malva nut was developed and was shown to exhibit improved performance over benchmark tamarind and algae polysaccharide gels (after 180min observation). Malva nut polysaccharide has potential as a key ingredient in skin hydrating products, which should encourage its further development.