ABSTRACT
An ongoing pandemic SS-RNA viral infection initiated from the Chinese province has threatened people throughout the globe. Coronavirus or COVID-19 or 2019-nCoV as a contagious infection is spreading day-by-day threatening the livelihood of people. The main objective of this paper is to find out solutions for the detection of this contagious viral infection at the earliest. Computer-based artificial intelligence can be used to monitor and detect the symptoms of coronavirus. For detection of coronavirus infection, computers or smartphones can be embedded with biosensors that will perceive the information and will convert the information into digital data. In this paper, a study on the coronavirus is done and an IoT-based framework is proposed to detect the coronavirus using IoT-based sensors. The proposed approach will be able to detect the pandemic in its early stages, and better options for prevention and cure will be discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Objective: To compare action tremor assessed in-person, remotely by telemedicine, and remotely using objective motion-sensor data. Background: Access to clinical care has become more difficult for patients living with chronic diseases such as Essential Tremor (ET) and Parkinson's Disease (PD), due to COVID-19. This meta-analysis compared studies using in-person or telemedicine clinical appointments along with motion-sensor measurements to assess the therapeutic benefit of Transcutaneous Afferent Patterned Stimulation (TAPS) [Pahwa R. et al., 2019] for action tremor (i.e., tremor elicited by voluntary muscle contraction, including postural and kinetic tremors) in ET and PD patients. Design/Methods: De-identified tremor motion data were compared across three cohorts receiving TAPS therapy under clinical supervision: (1) ET action tremor assessed in-person and remotely (N=193;3-month motion-sensor remote assessment with 3 in-person visits);(2) PD action tremor assessed in-person (N=11;5 in-person visits), and (3) PD action tremor assessed remotely (telemedicine visits over 1-month;currently enrolling). The pooled analysis compared (i) sensor-measured improvements in tremor severity with TAPS therapy, and (ii) correlation between clinician-rated and sensor-measured assessments of tremor severity. Results: ET patients experienced a median 42% reduction in tremor severity in-clinic and 53% reduction in tremor severity at home (study 1) [Isaacson S. et al., 2020]. PD patients experienced a median 38% reduction in tremor severity (study 2). Sensor-measured reductions in severity were consistent across patient cohorts (p=0.3, PD vs ET in-person), but different across assessment locations (p<0.01, ET in-person vs ET remote). Clinical gold-standard ratings of tremor severity were correlated with simultaneously-measured sensor assessments (r=0.67 (study 1)1;0.89 (study 2)). Conclusions: These findings provide consistent measures of action tremor reduction from TAPS therapy in PD and ET and suggest that occasional, in-person assessments may not always capture daily at-home improvements;and demonstrate how wearable sensors can be incorporated into remote clinical studies via telemedicine for patients with movement disorders.
ABSTRACT
COVID-19 pandemic has challenged the entire health care system to a great extent and led to the development and utilization of alternative approaches. Tele-oncology holds great potential to deliver cancer care. With the use of tele-oncology, physical distancing can be maintained. This will help the cancer patients as well as the oncologist and other supporting staff from getting exposed to the virus. However, there are many challenges for starting tele-oncology especially in resource limited settings. We hereby discuss tele-oncology its applications, methods available, tools, set up and infrastructure, benefits of tele-oncology and various patient, physician and resource-related factors in detail, especially in the setting of low- A nd middle-income countries.