Being at the center of the concepts, such as artificial intelligence and machine learning that we frequently come across in our daily lives, smart devices have also been used for human health for a long time. Studies have revealed that particularly smart watches can also be used for the Coronavirus pandemic engulfing the world as we have experienced recently.<\/p>\n
In order to create the learning algorithm of the machines, data were collected from a medical wristband for analyzing the sleep patterns of 25 participants infected with the flu virus. An impaired sleep pattern was spotted, which occurred 24 hours before the spreading of the virus, in 7 out of 8 participants with usable data.<\/p>\n
As per the researchers, more data were collected from people wearing smart watches due to the Covid-19 pandemic, which will lead to some changes in new models. It is believed that these models can be used to determine an early warning signal and even determine any asymptomatic spreading. Although this approach will never be capable of detecting COVID-19 by any means, it might be useful in letting people know when to take measures.<\/p>\n
In the current Coronavirus pandemic, those having cold or flu symptoms are asked to isolate themselves as they have not experienced the most common symptoms, such as fever, dry cough and shortness of breath, unless they test positive for Covid-19. If the algorithm is calculated accurately, a smart watch or a fitness application can provide an early warning for those who are about to fall sick or for those who need to isolate themselves.<\/p>\n
REFERENCES:<\/strong> Studies have revealed that particularly smart watches can also be used for the Coronavirus pandemic engulfing the world as we have experienced recently.<\/p>\n","protected":false},"author":5,"featured_media":1941,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[499],"tags":[],"class_list":["post-2195","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"yoast_head":"\n
\n\u201cAn unsupervised transfer learning algorithm for sleep monitoring\u201d. Xichen She, Yaya Zhai, Ricardo Henao, Christopher W. Woods, Geoffrey S. Ginsburg, Peter X.K. Song, Alfred O. Hero. (2020)<\/p>\n","protected":false},"excerpt":{"rendered":"