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IBM Demonstrates a Finger Nail Sensor That Could Help Diagnose Parkinson's Disease

April 02, 2019 00:00 AM UTC
- Updated February 18, 2020 14:19 PM UTC

The technology is developed to capture signals of motions, gestures, and grip strength.

Transcript
I won't take us back to think about how we extend measurements from the planet. He'll be on the clinic. So just recall the experience you had in your recent visit to the clinic. You know, you win. There were some signs and symptoms. The physician sat you down and they examined and they concluded from that. Okay, this is radio are and this is what you're experiencing, and they made deficiency with it. But that was actually an episodic event with for 10 minutes, you were in that clinic, but the remainder of the day and the remainder of your life. You're actually living outside the clinic. So what we want to think off is how do we extend the ability to observe from the clinic Toby on the clinic to your home and the 99% of the time that you're not in the clinic? How can we do that? So we want to talk about activities that you do, and in particular, I'm gonna show you a new sensor that our team came up with. We call it the fingernail sensor. It's a prototype that I'm showing you here. It was published recently with results that are described in the paper, but I'm going to demonstrate to you what this device does. It is a fingernail center. And as you can see, it is a very proper tighty thing right now. The eventual form in which this device will be used is not what it looks like here. Rather think of it as the same form factor as your nail itself. That thickness that size that is just pasted on your nails. And that's the device. Okay, but I will demonstrate to you what this prototype device does already. So what is it designed to do? It is actually designed. D'oh. Capture a few signals. So if you get to the signal on the screen, what do you say here? I'm showing you, actually, three traces that are being continuously produced, the top one is actually coming straight from the sternum. And in this case, this actually is just a device that I happen to have a phone that I'm using to give you a signal from, uh, the phone on on on my sternum on the fingernail sensor, I actually had the ability to pick up two additional signals. One is the strain and another is actually the acceleration that this device is producing. So what can they do? I will show you, for example, that if I was to hold an object, the act of gripping that object produces a new signal off strain. So as I do, that way we'll see a signal. What I have produced for you in the video where this device actually then create a whole variety off new signals. So if you were to actually cut to the to the video and I will walk you through some of these signals so on that, what do you say is holding objects with my hand? And what is this producing? This is actually producing the act off gripping an object, holding it, turning it. Each of those is actually creating new strain information from the tip off your digits. And it is producing signals off not only the act of holding and gripping, but to the application off appropriate. Aye. Aye. Classifications techniques. We can actually then loan from that instant off. That signal. What if the activity that you was the individual is catching up? Not only what activity, but how Well you're performing that activity. Quantify. Actually, the amount off strain and force that you're applying as you do each of these activities and these are not synthetic activities that you do over in the clinic, but rather these activities that you do in your normal daily life. And of course, if you happen to have specific changes, how you carry on those activities either because you off known movement disorders or because some modulation that is according to your activity that you aren't even aware off. For example, cardiovascular diseases known to modulate your grip strip. If those changes are occurring well, before you actually know that those changes are occurring just by monitoring the activity itself, as shown in this video, you begin to pick up those changes. Also illustrated here is a specific example off a subject actually sitting and standing, you may sit in stand without the assistance of your hands, or you must sit and stand by holding the armrest. And because you're gripping the amorous, the fingernail sensor is actually able to tell us how much force you're exerting as you hold the amorous sit in skin and then off course. If as an individual you have difficulty in getting up out of a chair in Have the demonstration short over there. That act itself can also be seen as a different signal. Okay, so what have I shown? You hear that by putting sensors on the digits on the extremities of your hand and then going about doing activities as you would normally in itself actually produces a wealth of new information on how well you're carrying all those activities and whether there is any change, even a gradual change that can be tracked over time. So that's sort of the ability of this one sensor to give us that signal. Of course, the sensor alone is not what is all that is relevant. This, together with additional information like the movement I was showing you with just a phone placed on the body is allowing me to see whether I'm actually sitting or standing on, then yielding the fingernail sense that I can put that together and say, Did I hold the arm rest to get a part of a chair and activities off that kind like activities in a kitchen, holding your toothbrush, grabbing a door handles. All of those are just normal activities that in itself to produce a signal so that what I'm showing you here is a way to extend the ability to observe from that episodic event in the clinic to actually continuous observations that can occur in your normal daily life. Okay. And this then has ability to provide quantitative information with regard to changes in your signs and symptoms as your disease progresses, or as subtle changes begin to occur that you are not even still recognizing as a disease. Okay, Thank you for your attention.