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How a Vibrating Smartwatch Could Be Used to Stop Nightmares | WIRED

The FDA has given NightWare clearance to market a “digital therapeutic” device that uses an Apple Watch to interrupt PTSD-related nightmares.
— Read on www.wired.com/story/how-a-vibrating-smartwatch-could-be-used-to-stop-nightmares/

The younger Skluzacek (inventor) got his idea from the work of service dogs, who lick or nudge veterans with PTSD who are thrashing or moaning in their sleep, to disrupt their nightmares and allow them to sleep more peacefully.

The “digital therapeutic system” uses the sensors on a specially programmed Apple Watch to create a baseline sleep profile of the wearer. The sensors then can detect the rising heart rate and body movement associated with troubled sleep. The watch delivers vibrations in cycles of 10 seconds, increasing in intensity to arouse but not awaken the wearer, until the metrics ease back to normal levels.

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Northwestern University Has Developed An AI System That Helps Detect Covid-19 On Chest X-Rays

This could potentially act as a rapid screening and triage tool.
— Read on www.forbes.com/sites/saibala/2020/11/29/northwestern-university-has-developed-an-ai-system-that-helps-detect-covid-19-on-chest-x-rays/

Earlier last week, Northwestern University researchers announced that they successfully created a new Artificial Intelligence (AI) radiology tool that can detect Covid-19 in chest x-rays.

The study has since been published in the journal Radiology, and indicates that the system “classified 2,214 test images with an accuracy of 83%.”

Dr. Aggelos Katsaggelos, a senior author of the study, states in the press report that “We are not aiming to replace actual testing […] X-rays are routine, safe and inexpensive. It would take seconds for our system to screen a patient and determine if that patient needs to be isolated.” Dr. Ramsey Wehbe, another main author of the study, explained that “It could take hours or days to receive results from a COVID-19 test […] A.I. doesn’t confirm whether or not someone has the virus. But if we can flag a patient with this algorithm, we could speed up triage before the test results come back.”

As Katsaggelos so aptly describes, the ability to conduct an initial screening to see if patients need to be isolated could itself be a potentially massive value addition to emergency department physicians. During the height of the pandemic, and still in many places, personal protective equipment (PPE) was one of the first supplies to run low, meaning that healthcare professionals were routinely seeing coronavirus positive patients without protection for themselves, potentially exacerbating the spread of the virus. In fact, this caused many healthcare workers to often reuse and stretch out limited supplies of PPE for patient care. Per the Centers for Disease Control and Prevention (CDC), so far, nearly 238,000 healthcare professionals have contracted Covid-19, with over 841 having passed away due to the virus.

The discussion in the journal article also provides an important consideration of this technology: “Prior clinical studies showed COVID-19 pneumonia produces characteristic features on chest imaging, but up to 56% of symptomatic patients can demonstrate normal chest imaging, especially early in their disease course. Imaging is therefore inappropriate to “rule out” disease. Also, many of the findings seen in COVID-19 imaging are non-specific with overlap, particularly with other viral pneumonias. Chest imaging therefore should not be used as a diagnostic tool for COVID-19, but could play an important role in earlier identification of patients likely to have the disease to aid in triage and infection control.”

The press report does also warn that “Of course, not all COVID-19 patients show any sign of illness, including on their chest X-rays. Especially early in the virus’ progression, patients likely will not yet have manifestations on their lungs.” In these cases, this AI radiology tool will likely not be very helpful.

Nonetheless, as the authors of the study so aptly conclude: “We feel that this algorithm has the potential to benefit healthcare systems in mitigating unnecessary exposure to the virus by serving as an automated tool to rapidly flag patients with suspicious chest imaging for isolation and further testing.” Indeed, if this screening tool continues to be further tested, and can be proven to be efficacious, safe, viable, and somewhat scalable, it may potentially be able to help alleviate some of the burden that healthcare workers face.

The content of this article is not implied to be and should not be relied on or substituted for professional medical advice, diagnosis, or treatment by any means, and is not written or intended as such. This content is for information and news purposes only. Consult with a trained medical professional for medical advice.

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Scientists Figured Out How Much Exercise You Need to ‘Offset’ a Day of Sitting

We know that spending hour after hour sitting down isn’t good for us, but just how much exercise is needed to counteract the negative health impact of a day at a desk? A new study suggests about 30-40 minutes per day of building up a sweat should d
— Read on www.sciencealert.com/getting-a-sweat-on-for-30-40-minutes-could-offset-a-day-of-sitting-down

Scientists Figured Out How Much Exercise You Need to ‘Offset’ a Day of Sitting

We know that spending hour after hour sitting down isn’t good for us, but just how much exercise is needed to counteract the negative health impact of a day at a desk? A new study suggests about 30-40 minutes per day of building up a sweat should do it.

Up to 40 minutes of “moderate to vigorous intensity physical activity” every day is about the right amount to balance out 10 hours of sitting still, the research says – although any amount of exercise or even just standing up helps to some extent.

That’s based on a meta-analysis across nine previous studies, involving a total of 44,370 people in four different countries who were wearing some form of fitness tracker.

The analysis found the risk of death among those with a more sedentary lifestyle went up as time spent engaging in moderate-to-vigorous intensity physical activity went down.

“In active individuals doing about 30-40 minutes of moderate to vigorous intensity physical activity, the association between high sedentary time and risk of death is not significantly different from those with low amounts of sedentary time,” write the researchers in their published paper.

In other words, putting in some reasonably intensive activities – cycling, brisk walking, gardening – can lower your risk of an earlier death right back down to what it would be if you weren’t doing all that sitting around, to the extent that this link can be seen in the amassed data of many thousands of people.

While meta-analyses like this one always require some elaborate dot-joining across separate studies with different volunteers, timescales, and conditions, the benefit of this particular piece of research is that it relied on relatively objective data from wearables – not data self-reported by the participants.

The study arrives alongside the publication of the World Health Organization 2020 Global Guidelines on Physical Activity and Sedentary Behaviour, put together by 40 scientists across six continents. The British Journal of Sports Medicine (BHSM) has put out a special edition to carry both the new study and the new guidelines.

“These guidelines are very timely, given that we are in the middle of a global pandemic, which has confined people indoors for long periods and encouraged an increase in sedentary behaviour,” says physical activity and population health researcher Emmanuel Stamatakis from the University of Sydney in Australia.

“People can still protect their health and offset the harmful effects of physical inactivity,” says Stamatakis, who wasn’t involved in the meta-analysis but is the co-editor of the BJSM. “As these guidelines emphasise, all physical activity counts and any amount of it is better than none.”

The research based on fitness trackers is broadly in line with the new WHO guidelines, which recommend 150-300 mins of moderate intensity or 75-150 mins of vigorous intensity physical activity every week to counter sedentary behaviour.

Walking up the stairs instead of taking the lift, playing with children and pets, taking part in yoga or dancing, doing household chores, walking, and cycling are all put forward as ways in which people can be more active – and if you can’t manage the 30-40 minutes right away, the researchers say, start off small.

Making recommendations across all ages and body types is tricky, though the 40 minute time frame for activity fits in with previous research. As more data gets published, we should learn more about how to stay healthy even if we have to spend extended periods of time at a desk.

“Although the new guidelines reflect the best available science, there are still some gaps in our knowledge,” says Stamatakis. “We are still not clear, for example, where exactly the bar for ‘too much sitting’ is. But this is a fast-paced field of research, and we will hopefully have answers in a few years’ time.”

The research has been published here, and the new guidelines here, in the British Journal of Sports Medicine.

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Mobility network models of COVID-19 explain inequities and inform reopening

Based on cellular mobility data,

Researchers from Stanford University, among other institutions, studied anonymized data on 98 million people and their movement patterns hour-by-hour in the 10 largest metro areas in the U.S. An early version of the peer-reviewed findings was published on Tuesday in the journal Nature.

“We found large variation in predicted reopening risks: on average across metro areas, full-service restaurants, gyms, hotels, cafes, religious organizations, and limited-service restaurants produced the largest predicted increases in infections when reopened,” study authors wrote.

The COVID-19 pandemic dramatically changed human mobility patterns, necessitating epidemiological models which capture the effects of changes in mobility on virus spread1. We introduce a metapopulation SEIR model that integrates fine-grained, dynamic mobility networks to simulate the spread of SARS-CoV-2 in 10 of the largest US metropolitan statistical areas. Derived from cell phone data, our mobility networks map the hourly movements of 98 million people from neighborhoods (census block groups, or CBGs) to points of interest (POIs) such as restaurants and religious establishments, connecting 57k CBGs to 553k POIs with 5.4 billion hourly edges. We show that by integrating these networks, a relatively simple SEIR model can accurately fit the real case trajectory, despite substantial changes in population behavior over time. Our model predicts that a small minority of “superspreader” POIs account for a large majority of infections and that restricting maximum occupancy at each POI is more effective than uniformly reducing mobility. Our model also correctly predicts higher infection rates among disadvantaged racial and socioeconomic groups2–8 solely from differences in mobility: we find that disadvantaged groups have not been able to reduce mobility as sharply, and that the POIs they visit are more crowded and therefore higher-risk. By capturing who is infected at which locations, our model supports detailed analyses that can inform more effective and equitable policy responses to COVID-19.
— Read on www.nature.com/articles/s41586-020-2923-3

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Data analysis identifies the ‘mother’ of all SARS-CoV-2 genomes

Data analysis identifies the ‘mother’ of all SARS-CoV-2 genomes.

Despite major efforts, no one to date has identified the first case of human transmission, or “patient zero” in the COVID-19 pandemic. Finding such a case is necessary to better understand how the virus may have jumped from its animal host first to infect humans as well as the history of how the SARS-CoV-2  has mutated over time and spread globally.

— Read on medicalxpress.com/news/2020-11-analysis-mother-sars-cov-genomes.html