• The (virtual) doctor will see you now
  • Control a computer… with only your mind
  • Would you volunteer to have this device implanted in your brain?

Dear Reader,

The good news seems to arrive daily now with regard to COVID-19. In fact, there is too much to cover in just one day.

But today, I’d like to follow up on the topic of how widely COVID-19 has spread versus the number of confirmed cases. These are two very different numbers, as I’ll outline below.

A team lead by members of the Stanford University School of Medicine just published the most comprehensive research to date in the U.S. concerning COVID-19 antibody seroprevalence. More simply, the research tested healthy individuals in Santa Clara County, California, (in the Stanford area) for the existence of COVID-19 antibodies.

If someone tests positive for COVID-19 antibodies, they already had COVID-19 and recovered. Therefore, they have become immune for at least a year and possibly as long as three years.

The team tested county residents… 3,330 people that are representative of the population in that area. Here are the results.

The population-weighted prevalence of the COVID-19 antibodies was 2.81%, with a range of 2.24%–3.37%. This represents a range between 48,000 and 81,000 people in Santa Clara Country infected with COVID-19 by April. As of this writing, there are only 1,870 confirmed cases of COVID-19 in Santa Clara County and just 73 deaths.

In other words, the study suggests that actual cases of COVID-19 in that area are as much as 43 times higher than the number of confirmed cases.

As I have been writing, serological tests are critical to understanding the virus. Confirmed cases are irrelevant in estimating a case fatality rate for a virus like COVID-19. We must understand how many people have contracted the virus. Then we will have a far more accurate understanding of how “deadly” a virus really is.

The press and others would have us believe that the death rate is 3.9% (73 deaths / 1,870 confirmed cases).

The research from Stanford shows us something completely different.

At 48,000 infected with COVID-19, the case fatality rate is 0.17% [73 deaths / (41,000+1,870)]. This is on par with seasonal flu.

At 81,000 infected with COVID-19, the case fatality rate is 0.08% [73 deaths / (81,000+1,870)]. This is dramatically lower than seasonal flu.

We can think of 0.17% as our upper bound… the worst-case scenario. But the reality is that it is likely much lower. The San Francisco Bay Area wasn’t impacted too badly from the outbreak. In areas where the prevalence is higher, the case fatality rate will be lower.

This is why serological testing is so critical. It helps us understand the facts, which allows us to make good decisions.

Now on to our insights…

The future of medicine is here…

For health care workers treating COVID-19 patients, contracting the virus is now a common occurrence. The CDC estimates that as many as 9,200 health care workers have been infected with COVID-19. But an early stage company is aiming to do something about that…

Ava Robotics has developed an autonomous telepresence robot to help hospital staff with COVID-19 patients. Ava Robotics’ background is a bit interesting.

It was originally the health care robotics division of iRobot, the successful company that built its name with autonomous robots that clean the floor. But health care is a very different market than home cleaning robots, so it made a lot of sense to spin this division out into its own company.

The telepresence robot consists of a high-quality camera mounted on a video screen that navigates hospitals and clinics on wheels. It allows remote doctors to see and treat patients or collaborate with other doctors as though they were physically present. Here’s a visual:

A Telepresence Robot

Source: Ava Robotics

This is what the future of medicine looks like. Robotic telepresence will empower doctors to be far more efficient, which will enable them to see more patients in a day… especially in a pandemic scenario like we are dealing with now.

Right now, doctors must disinfect themselves and put on protective gear before they see any COVID-19 patients. If they take a break, go to the bathroom, or see another patient who may not be infected, they must disinfect their gear again. That’s a tedious process that takes up a lot of time.

Using robotic telepresence, doctors cut out that process. They can roll from one patient to the next without needing to worry about spreading infection. They can cover more ground and see more patients every day.

I expect we’ll see more and more hospitals take advantage of this technology, even after COVID-19 has passed. It just makes too much sense. Plus, it will allow hospitals to consult with the top specialists around the world in a hands-on way. Location will no longer be an impediment.

So this is an exciting development. No matter what happens with Ava Robotics – an acquisition or an IPO – I suspect that iRobot will do quite well, as it has a large ownership stake in the company.

We’ll keep a close eye on the company, since telehealth and remote health care technology are going to be major beneficiaries of this pandemic.

A breakthrough in brain-computer interface research…

We have talked about brain-computer interfaces before. These are devices that can read brain signals, allowing users to control a computer or other connected device with just their minds.

However, up to this point, brain-computer interfaces could only link brain activity to specific words with about 70% accuracy. That’s just not good enough for a mass-market product. And that’s where today’s breakthrough comes in…

Researchers at the University of California, San Francisco, found a way to boost this accuracy using a form of artificial intelligence (AI) called neural networks.

The AI analyzed how machine language translation works – think Google Translate – and applied it to brain signals. In doing so, it found out that the key was to focus on complete sentences rather than single words. This provided more context to learn from.

So the researchers took four volunteers who already had electrodes implanted in their brains (to monitor them for seizures) and asked them to read out 30–50 sentences aloud. That created a robust dataset for the AI to learn from.

And by the end of the training, the AI could decipher up to 250 unique words with 97% accuracy. That’s a dramatic improvement over our existing technology. And it’s nearly good enough for a mass-market commercial product.

This brain-computer interface tech will have a profound impact on people who aren’t able to speak due to an accident or health condition. Patients with speech problems will now be able to communicate their thoughts more clearly to doctors and loved ones.

I can’t wait to see how the tech progresses from here.

Solving the last problem with brain-computer interfaces…

Staying on topic… One of the biggest problems with brain-computer interfaces right now is that electrodes can’t stay in the brain for long periods of time. The brain is not a forgiving environment for foreign objects. And believe it or not, electronic implants erode in the brain very quickly.

So to apply the research discussed above, we would need a new approach to keep electrodes in the brain for years. And fortunately, new research out of Duke University is showing incredible progress toward solving the problem…

Duke researchers developed a neural interface that can survive in the brain for six years. Here’s what it looks like:

1,008 Electrode Neural Interface Virtual Tour

Source: Charles Wang and Mackenna Hill, Duke University

As we can see, the electrodes are embedded in a thin and flexible glass case less than a micrometer thick. There are over 1,000 electrodes in there. They are what read the brain signals.

As for the glass casing, it degrades in the brain at just 0.46 nanometers per day. And this form of glass is biocompatible, so the body can process and discard the material as it dissolves.

The team at Duke has already tested this device in a monkey’s brain successfully. The monkey suffered no harm, and the device could read its brain signals.

That means the next step is to test this device in human volunteers. I suspect patients who have suffered a serious accident that impedes their speech would be the top choice.

And from there, we’ll face a challenging ethical discussion…

Brain-computer interfaces will enable people to access the cloud in real time. Imagine a direct pipe between our brain and the internet. That means we could tap into all the information available on the internet with just our thoughts.

For readers who have seen The Matrix, this isn’t too different from “downloading” programs directly into our brain like they did in the movie.

But the big question is – should we?

That discussion is coming faster than we may expect…


Jeff Brown
Editor, The Bleeding Edge

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