Wireless Body Area Network (WBAN) is among the most promising technologies for enhancing life quality. WBANs enable constant monitoring of physiological processes by implanting or wearing small, low-power, intelligent sensor nodes in or on the human body. These sensor nodes may be placed either invasively or non-invasively. Patient data must be disseminated reliably and promptly for WBAN's healthcare apps to function. For this reason, medical teams may use real-time apps for sharing vital information like blood pressure, an ECG, and an EEG. Critical data packets are delay-sensitive and must arrive at sink nodes within the time constraints that satisfy QoS for WBAN. However, networks' unpredictable and dynamic nature (node mobility, link partitioning) makes reliable data transfer a challenging task. Additionally, postural mobility and ultra-short wireless range cause rapid topology changes, resulting in network partitioning. The network partitioning causes failure of data delivery to the sink or coordinator and causes a delay as well. In the case of normal data, it is not a big issue, but it is not tolerable for emergency data because it may be life-threatening. Consequently, compromising the link reliability and stability results in higher delays, increased packet re-transmissions, and decreased throughput performance. Therefore, we propose an Enhanced Probabilistic Route Stability (EPRS) scheme to address these issues. The proposed EPRS scheme introduces a cost function called Link Assessment Cost (LAC) that makes coherent decisions regarding route reliability in determining whether an active route is a good candidate for routing and satisfying QoS requirements. The LAC is based on two critical factors about link status, i.e., Route Stability Factor (RSF) and Expected Probability of link E(p). Based on these factors, a score is assigned to a link that determines the status (likelihood) of a link, either connected or disconnected. In this way, the multi-facet EPRS selects the most stable and reliable routes despite the disconnection in the networks, thereby improving the route stability and throughput, minimizing the end-to-end delay, route discovery calls, and retransmissions as depicted by simulation results.

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Smart Sensing has shown notable contributions in the healthcare industry and revamps immense advancement. With this, the present smart sensing applications such as the Internet of Medical Things (IoMT) applications are elongated in the COVID-19 outbreak to facilitate the victims and alleviate the extensive contamination frequency of this pathogenic virus. Although, the existing IoMT applications are utilized productively in this pandemic, but somehow, the Quality of Service (QoS) metrics are overlooked, which is the basic need of these applications followed by patients, physicians, nursing staff, etc. In this review article, we will give a comprehensive assessment of the QoS of IoMT applications used in this pandemic from 2019 to 2021 to identify their requirements and current challenges by taking into account various network components and communication metrics. To claim the contribution of this work, we explored layer-wise QoS challenges in the existing literature to identify particular requirements, and set the footprint for future research. Finally, we compared each section with the existing review articles to acknowledge the uniqueness of this work followed by the answer of a question why this survey paper is needed in the presence of current state-of-the-art review papers. Index Terms-Smart sensing, QoS of IoMT, IoMT applications in COVID-19, QoS requirements, QoS challenges, routing protocols. I. INTRODUCTIONC OVID-19 is an infectious and transmittable virus that can provoke penetrating respiratory syndrome in humans [1]. This virus has been spread all over the globe and infected 437,792,328 individuals, followed by 5,978,217 fatalities and 369,500,307 recovered cases by March 1, 2022 [2]. The research community believes that COVID-19 infection rates Manuscript