 We're talking with Ben Carter from Heartkey, and I'm a little confused. I see a steering wheel. I see some heart action going on here. I'm watching what looks like somebody's heart rhythm here. So tell us, what are you talking about with Heartkey? Yeah, so welcome. I'm Ben Carter from Be Secure, and we're an ECG technology company. Biometrics is known today, is all around fingerprint technology, iris technology, facial recognition. And what we do differently is we're able to take real time ECG data, identify people uniquely, but at the same time, understand if they're in a stress state or have problems of respiration or maybe even have an acute cardiac condition. So what we're seeing here, for example, is one of the number of different use cases we have. So my friend Adrian here, who's clearly a model, is actually wearing a module we've developed, which is actually taking this real live ECG feed. So wait a minute, we've got to see Adrian's ECG monitor here. So you've designed this monitor? Yeah, so what you've got here is just a standard module, sorry, connected to a standard chest strap. So what we've done here is we've taken this, and in this module, we have a microcontroller which we embed our library technology on, and then that's then sat on his chest strap. So what you're seeing here for this particular use case, for example, could be around uniform work or connected workers in the IOT space, the ability to understand who they are, where they are and how they are. So imagine, for example, someone who's in the fire service or in the military, stress, fatigue are significant challenges for these people. And so what we're doing here, through this GUI, is showing that this is Adrian, this is real-time. This is real-time. Yeah, Steve just told Adrian to hold his breath. He wants to see his heart rate go up for his stress level? You'll see his stress level, and this is real-time, exactly. So he's... Oh, his stress is going down. I'll start to read a little bit of it first. So he's uniquely identified. This is a live ECG. This is a medical grade ECG heart rate. So heart rate today is primarily understood through devices where you have an optical sensor and it derives a signal. This is a medical grade ECG heart rate. How many leads is it? It's two. So if you go to a hospital, you have a 12-lead ECG machine. We take lead one. So as long as you have polarity across the chest, you have two points of contact, then you can pick up this information. So this here now is a stress score. And stress, this is physiological stress. So we determine stress through using heart rate variability. So as you can see in each heartbeat, what we do is we look at the variations from heartbeat to heartbeat. And depending on which part of the heartbeat you look at, you can determine different forms of information. And stress is one of those. Down here, you can see a stress log as an example. So what we're trying to understand now is the impact of stress and what it means. And what happens generally in today's world is if someone's stressed, it's a reactive thing. So if someone goes off work because they're stressed, but it's too late at this point. Our technology is around giving people the ability to have early detection and prevention of this kind of thing. So imagine this type of understanding every day, all day, for weeks and months. If someone was sick or was going off stressed, you can actually determine this and they actually help them before they get sick. So again, this isn't for like tracking postal workers, probably. Well, it could be. Actually, they're probably stressful jobs, right? But it's for people who might be in more likely to be in danger of these kinds of problems. Yeah, so I think in the early days, we're looking at working with in areas like military, blue light services, security services. But we're also working with partners where this type of information can be connected to an IoT platform. So imagine a military command center where they have 20, 30, 100 soldiers and they can monitor their stress levels all the time, in real time, across an entire population. Maybe stop a bigger problem. This is an example of the additional kind of data you can derive from an ECG signal. Now he's holding up a tablet and it's on Joe blogs. We're no longer torturing Adrian. We're no longer torturing Adrian, but this is an example of the extent of more that we can do an ECG. So our verification and identification stays here. But we can do things like drowsiness within health and wellness, arrhythmia conditions and genuine health care. How do you know if he's drowsy? So again, it's just through variations within the heart rate variability. So if I go back to the signal, this is called a PQRST complex. So every beat you have is a PQRST. Whether we take elements within the T or the PQRST or the T, the T wave, we can establish different forms of ECG data or health. So it could be stress. It could be heart rate variability. It could be stress or energy expenditure, calorie burn, respiration. So our business is all around developing more and more algorithms that sit within our heart key library. And that's our business model. So we're effectively building IP software, working with hardware partners to integrate it into end devices. This is really, really fascinating. I had no idea you could get so much out of a heart rate. Very good. So if people want to learn more about heart key, where would they go? They'd go to bsecure.com. Bsecure.com? So yeah, so it's www.b-secur.com, B-secure. Okay, no E on the secure. No, that's, no, no. Missing letters, you got a dash in there. Yeah, that's it. All right, well. We'll put it down here in a lower third right below you right here. Exactly right. Thank you very much guys. And thank you for letting us make fun of you, Adrian. I'm used to it.