ABSTRACT
The Internet of things (IoT) is a system of interconnected devices and linked electronic devices which can collect, transmit, and manage data without human or computer intervention. The IoT is also potential technology that transforms everyday objects into dependable and effective intelligent things. It has impacted every element of life;however, its influence on healthcare has become particularly profound because of its slicing facet shift. It is now feasible to link innovative items over the internet and provide more digitally connected world ways for special applications. In published research on IoT in health care and the COVID-19 epidemic, the potential of this platform is examined. This literature-based research might also help specialists imagine related problems and combat the COVID-19 outbreak. This study report examines the human healthcare IoT (H2IoT) state, including existing services, architecture, topology, tools, services, and healthcare applications. In modern hospitals, "IoT” technology and internet-connected digital gadgets are commonplace. Clinicians have now abandoned paper and have become entirely or partly reliant on devices linked to wireless connections and tablets. © 2023 selection and editorial matter, Durgesh Srivastava, Neha Sharma, Deepak Sinwar, Jabar H. Yousif, and Hari Prabhat Gupta;individual chapters, the contributors.
ABSTRACT
The coronavirus epidemic began in Wuhan and has already spread to practically every country on the planet. Conravirus has a big population in India, and people are becoming infected at an alarming rate. Machine learning algorithms have been utilized to find trends in the number of active cases owing to COIVD in India and the state of Odisha in this study. The data was gathered from the WHO and studied to see if there was a link between the number of current cases, those who died, and those who recovered. The model was entirely based on multiple regression, support vector machine, and random forest which fits as an effective tool for prediction and error reduction. Based on the dataset taken from March 16, 2020, to August 20, 2020, from the ICMR website, the mean absolute error (MAE) of SVM is less for Odisha and multiple linear regression is less for India. The multiple learner regression model is able to predict number of active cases properly as its R2 score value are 1 and 0.999 for Odisha and India, respectively. Machine leaning model helps us to find trends of effected cases accurately. The model is able to predict what extent the COVID cases will grow or fall in the next 30 days which enables us to be prepared in advance and take some preventive measures to fight against this deadly COVID virus. It is observed that features are positively correlated with each other. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Background • Coronavirus disease 2019 (COVID-19) outbreak and lockdown has caused negative impact on mental health status of health care workers including the physiotherapists as physiotherapists are also involved in the care of patients with COVID-19 infection. • Taking care of COVID-19 infected patients can be exhaustive both physically and mentally due to involved risk of contracting the disease which may prove fatal for some. • Due to ongoing lockdown many physiotherapists are not able to work either fully or partially as per their potential. So, physiotherapists like other health care workers are not immune to mental health impacts of COVID-19 lockdown. Aim • To assess relationship between psychological impact of COVID-19 in the form of anxiety and depression, and the resilience among physiotherapists. Methods • Data were collected from total 378 physiotherapists. • Beck's depression inventory (BDI), generalized anxiety disorder 7 item (GAD-7) scale, and brief resilience scale (BRS) were used to assess depression, anxiety, and resilience respectively among the study participants. • Data were analyzed by using SPSS 15 and, Chi-sqaure, Fisher exact, and Person's correlation tests. Results • Prevalence of anxiety and depression were 37.8% and 31% respectively. • As regards the resilience, 2.9% had high, 74.3% had normal, and 22.8% had low resilience levels. • Physiotherapists who had high level of resilience had lower rates of anxiety on GAD-7 and lower rates of depression on BDI. Conclusion • Strengthening the resilience of physiotherapists can promote their mental health in longer run in face of stressful event like COVID-19 lockdown. • So, resilience strengthening programs must be the priority.
ABSTRACT
Introduction: Novel coronavirus disease 2019 (COVID-19) has caused a rapidly evolving confused state. Like other front line health care workers (HCWs), physiotherapists are also providing their valuable services to COVID-19 patients. Caring COVID-19 patients is exhaustive both physically and mentally due to associated risks. So physiotherapists are prone to development of psychological problems like depression and anxiety during COVID-19 pandemic and lockdown. Main objective of study was to assess relationship between psychological impact of COVID-19 lockdown in the form of depression and anxiety, and the resilience among physiotherapists across India. Methods: Present cross-sectional online survey was conducted in the rural tertiary health-care center from Maharashtra, India, with sample size was 378. Data were recorded with consecutive sampling method from study participants on socio-demographic details, Beck's Depression Inventory (BDI), Generalized Anxiety Disorder 7 item (GAD - 7) scale and Brief Resilience Scale (BRS). After the collection, data were analyzed using version 15.0 of SPSS software, Chi-square test, Fisher's exact test and Pearson's correlation test. Results: Prevalence of depression and anxiety among study participants were 31% and 37.8% respectively. As regards depression, 56 (14.8%) had mild, 23 (6.1%) had borderline, 29 (7.7%) had moderate, 8 (2.1%) had severe and 1 (0.3%) had extreme depression. As regards anxiety, 96 (25.4%) had mild, 32 (8.5%) had moderate and 15 (3.9%) had severe anxiety. As regards resilience level, 86 (22.8%) had low, 281 (74.3%) had normal and 11 (2.9%) had high resilience. Those respondents who had high resilience had lower rates of depression on BDI and lower rates of anxiety on GAD-7. Conclusion: Programs to strengthen resilience should be priority. In longer run, increasing resilience of physiotherapists can have mental health promoting value during the stressful event of COVID-19 lockdown.
ABSTRACT
It is a well-established fact that patients of Covid 19 have musculoskeletal dysfunctions in addition to cardiorespiratory and psychosocial problems. Muscu-loskeletal system is amongst the most common systems found to be affected in patients admitted in ICU for prolonged periods and some patients of Covid 19 do have to spend a reasonably long period in ICU’s. Prolonged hospital stay may be needed in Covid 19 patients having ARDS or pneumonia and symptoms of fever, cold and cough to monitor their recovery. This may result in musculoskeletal dysfunctions as demonstrated in some studies. Thus, treat-ing the musculoskeletal system becomes a vital part of the regimen to be followed during the patients stay in the ICU which needs to be followed up even after the patient is shifted from the ICU by keeping a track of Physical Functional performance of the subjects after discharge. This experimental study was done on 150 Covid-19 positive subjects to see the long term effectiveness of a structured exercise protocol on the Physical Functional performance of Covid 19 patients. The results of the study were analysed statistically and both the outcome measures FIMS and POMA showed significant changes with p value <0.05 and <0.05 respectively. The study thus shows that the structured exercise protocol helped in maintaining the Physical Functional performance of the subjects through-out the hospital stay and also after discharge during follow up.