Post-Covid Remote Patient Monitoring Using Medical Internet Of Things And Machine Learning Analytics

The Covid-19 pandemic disturbed the smooth functioning of healthcare services throughout the world. New practices such as masking, social distancing and so on were followed to prevent the spread. Further, the severity of the problem increases for the elderly people and people having co-morbidities as proper medical care was not possible and as a result many deaths were recorded. Even for those patients who recovered from Covid could not get proper health monitoring in the Post-Covid phase as a result many deaths and severity in health conditions were reported after the Covid recovery i.e., the Post-Covid era. Technical interventions like the Internet of Things (IoT) based remote patient monitoring using Medical Internet of Things (M-IoT) wearables is one of the solutions that could help in the Post-Covid scenarios. The paper discusses a proposed framework where in a variety of IoT sensing devices along with ML algorithms are used for patient monitoring by utilizing aggregated data acquired from the registered Post-Covid patients. Thus, by using M-IoT along with Machine Learning (ML) approaches could help us in monitoring Post-Covid patients with co-morbidities for and immediate medical help. © 2023 SCPE.

Medical Internet of Things and Data Analytics for Post-COVID Care: An Analysis

The healthcare services across the world have been badly affected by the pandemic since December 2019. People have suffered in terms of medical supplies and treatments because existing medical infrastructure has failed to accommodate huge number of COVID infected patients. Further, patients with existing morbidities have been the worst hit so far and need attention. Therefore, there is a need of post-COVID care for such patients which can be achieved by using technologies such as Internet of Things (IoT) and data analytics. This paper presents medical IoT-based data analysis for post-COVID care. This paper, further, presents post-COVID data analysis to get an insight into the various symptoms across the different perspectives. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Publisher Correction: Additive manufacturing for biomedical applications: a review on classification, energy consumption, and its appreciable role since COVID-19 pandemic (Progress in Additive Manufacturing, (2022), 10.1007/s40964-022-00373-9)

The publication of this article unfortunately contained mistakes. The funding note was not correct. The corrected funding note is given below. Funding The current study was funded by;The National Key Research and Development Program of China [Grant No. 2019QY(Y)0502];The Key Research and Development Program of Shaanxi Province [Grant No. 2020ZDLSF04- 07];The National Natural Science Foundation of China [Grant No. 51905438];The Fundamental Research Funds for the Central Universities [Grant No. 31020190502009];The Innovation Platform of Bio fabrication [Grant No. 17SF0002];and China postdoctoral Science Foundation [Grant No. 2020M673471]. The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

Additive manufacturing for biomedical applications: a review on classification, energy consumption, and its appreciable role since COVID-19 pandemic

The exponential rise of healthcare problems like human aging and road traffic accidents have developed an intrinsic challenge to biomedical sectors concerning the arrangement of patient-specific biomedical products. The additively manufactured implants and scaffolds have captured global attention over the last two decades concerning their printing quality and ease of manufacturing. However, the inherent challenges associated with additive manufacturing (AM) technologies, namely process selection, level of complexity, printing speed, resolution, biomaterial choice, and consumed energy, still pose several limitations on their use. Recently, the whole world has faced severe supply chain disruptions of personal protective equipment and basic medical facilities due to a respiratory disease known as the coronavirus (COVID-19). In this regard, local and global AM manufacturers have printed biomedical products to level the supply-demand equation. The potential of AM technologies for biomedical applications before, during, and post-COVID-19 pandemic alongwith its relation to the industry 4.0 (I4.0) concept is discussed herein. Moreover, additive manufacturing technologies are studied in this work concerning their working principle, classification, materials, processing variables, output responses, merits, challenges, and biomedical applications. Different factors affecting the sustainable performance in AM for biomedical applications are discussed with more focus on the comparative examination of consumed energy to determine which process is more sustainable. The recent advancements in the field like 4D printing and 5D printing are useful for the successful implementation of I4.0 to combat any future pandemic scenario. The potential of hybrid printing, multi-materials printing, and printing with smart materials, has been identified as hot research areas to produce scaffolds and implants in regenerative medicine, tissue engineering, and orthopedic implants.

Public perceptions of the perils of misinformation in pandemic

Objective: To investigate the public perception regarding to the perils of misinformation in pandemic. Methodology: This quantitative cross-sectional design study with convenient sampling techniques was conducted in the IAHS, UAJ&K in March to April 2020 after ethical approval. Sample with both genders, using any types of social media between 15 to 65 years of ages was selected. Those who used social media for 2 years were included in the study, while new social media users were excluded. The date were collected from online survey with structural questionnaire and was analyzed on SPSS version 21. Results: Out of 229 participants, 107(46%) said that pandemic was due to punishment from God. Some thought it resulted from some sort of human negligence (N=40, 17%), and a few of them said it's a man-made biological weapon (N=15, 6%). The participants had physical (N=17, 7%), social (N=66, 28%), economical (N=67, 29%), and mental (N=35, 15%) issues due to pandemic. To avoid the misinformation majority respondent decided to Stop posting/sharing (N=99, 53%) provide or share authentic information (N=97, 42%), motivate other (N= 94, 41%) and delete/report misinformation (N=65, 25%). Conclusion: Misinformation leads to panic attack, sleep disturbance and develop mistrust. So it is important to arrange awareness campaigns for public on the issue of detrimental effects of misinformation.