It's Friday, June 22nd, 2018, and you're listening to Up to Date, our weekly recap of

science news. I'm Indra Viscontas. I'm Kishra. Hari. Let's talk about mind-controlling robots,

because why not? Like, you mean like brain computer interface things or like my phone?

I was thinking brain computer interfaces more than your phone. Well, I mean, when I say

mind controlling robots, it's less, it's not really mind controlling robots, but it's as

close as we are right now by using EEG to control robotic arms.

Next week, MIT roboticist Daniela Russ is demoing a new system to use an EEG cap,

you know those multi-electrode caps strapped right to your head, to control a single robot arm to control tasks,

but without the errors that we normally see with this kind of wireless control.

You're pretty familiar with EEG technology. It's pretty error prone. I mean, well, if it's not

wired, yeah. If it's wireless, it's very noisy. And it's really hard to get a continuous signal,

for example. You know, you have to make sure that the leads are directly onto the scalp.

So anyone with big hair, that's problematic.

You know, and yeah, so it's pretty messy.

It's a messy tool.

Even when it is wired, I've heard when you use it for this specific type of control,

where it's reading particular wave patterns and then trying to translate that into specific controls on a different prosthesis like a robotic arm.

Even with the fine control from a wired system, it still has a lot of noise in order for us to be able to think like robot arm move forward three degrees, robot arm move left,

20 degrees. That kind of fine control is hard. Yeah, because there's a lot of noise in the signal. So we do a

lot of pre or post processing of EEG data to figure out where the signal is and separate it from the

noise. So this team embraced a different solution.

They embraced the fact that error is a natural part of learning.

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