Optimized Embedded Healthcare Industry Model with Lightweight Computing Using Wireless Body Area Network

Abstract

Wireless technology is offering numerous growth to develop communication systems. The Internet of Things (IoT) is combined with the sensing ecosystem to transfer and process the physical environment. Recently, IoT devices have collaborated with wireless devices to improve embedded medical applications. Many solutions are proposed to decrease the power consumption of the sensing ecosystem and support the health industry. However, optimizing the transformation of collected data with lightweight power consumption is still a burning research issue. Moreover, uncontrolled network devices and healthcare professionals are remotely accessed by such embedded systems. Thus, securing sensitive information is also a significant factor for mobile communications. Therefore, this research presents an optimized embedded healthcare industry model with lightweight computing using a wireless body area network (WBAN), aiming to lessen the control overheads and improve the power consumption in mobile e-health services. To begin, it employs an optimal learning algorithm to lower the management costs of embedded systems in order to transform and administer the electronic health record (EHR) more efficiently. Second, with the help of trustworthy gateways, it delivers a safe EHR algorithm as well as lightweight computing resources for embedded systems. The proposed model is tested with a variety of experiments and demonstrates its significant improvement over state-of-the-art techniques.

A Deep learning approach for trust-untrust nodes classification problem in WBAN

“…A battery for uninterrupted data transmission and reception fuels each sensor component. Each sensor node battery has an initial energy capacity of one thousand joules [15][16][17][18][19][20].…”

Reviewing the Impact of Embedded Systems in Medical Devices in the Usa

“…These systems integrate computing elements within medical equipment to perform specific functions such as monitoring, control, and data processing. The implementation of embedded systems in medical devices has the potential to optimize the healthcare industry by decreasing management costs and supporting real-time analysis of patients' conditions (Saba et al, 2022). However, the security of intelligent embedded devices is of strategic importance due to the increasing growth of attacks originated by security threats and vulnerability exploitation (Chang et al, 2018).…”

“…Notable lessons learned from embedded systems in medical devices include the importance of trust and security in intelligent embedded systems, particularly in ensuring privacy preservation and user trust (Yadav & Alharbi, 2021;Ezeigweneme et al, 2024). Additionally, the integration of e-health data transmission to medical experts for real-time treatments, supported by a digital mobile network, has demonstrated the significance of optimized embedded healthcare industry models with lightweight computing (Saba et al, 2022;Ogundairo et al, 2023). Furthermore, the potential negative consequences of non-consented switch of inhaled medications and devices in asthma patients underscore the criticality of considering factors such as design characteristics, medication, and ease of use in embedded medical devices (Björnsdóttir et al, 2013).…”

“…The potential impact on the future of healthcare is substantial, with embedded systems revolutionizing medical treatment and patient care. Smart processing, which links various physical objects with embedded technology for communication and perception, has the potential to transform healthcare delivery and patient outcomes (Saba et al, 2022). Moreover, the application of Industry 4.0 technologies to the pharma, medical, and healthcare sectors is expected to address medical data integrity concerns and contribute to overcoming healthcare challenges, including those posed by the Covid-19 pandemic (Jezon, 2022).…”

“…Embedded systems in medical devices refer to the integration of computing elements within medical equipment to perform specific functions, such as monitoring, control, and data processing (Zavitsanou et al, 2016). These systems are crucial in healthcare as they enable realtime monitoring of patient conditions, automated drug delivery, and precise control of medical devices, leading to improved patient outcomes and safety (Saba et al, 2022). The review aims to assess the impact of embedded systems in medical devices in the USA, focusing on their role in enhancing healthcare delivery, patient safety, and treatment efficacy.…”