So, hello everyone. And uh thank you for attending uh uh my session. Uh So my name is Klia Duy. I'm a data scientist and a machine learning researcher. Uh I, I will be talking about uh a new emergent technology about the brain computer interface.And we will discover together in this talk, how could this technology being applied to several fields? But before starting, I would like to share this beautiful quote from Edward de Bono who said the human humor is by far the most significant activity of a human brain. And I would like to say that it is true that uh what you can see in general uh in our uh uh brain activity is our humor, um um humor, uh activity or attention uh attentional or emotional activity uh or our way actually to think or to solve problem. However, the question is um could we use this brain activity to interact with our environment to control some external devices? So in this talk, we will, we will be trying to answer this question if possible. So uh before starting, I would like to talk a bit about me. So uh I am uh I, I am a data scientist and I would like to highlight that I'm not a neuroscientist. Uh I am phd in biomedical informatics and passionate about the new technologies, data science and machine learning. Uh I would like really to um to um to create some decision support system uh to experts and discover the in, in some insights from the data. Uh and especially to help patients in um to, to live better actually.

And I like to do like operational research and innovation and create some useful tools uh with the new technologies for the industry. Uh So um in our talk in my talk, I will be uh uh um talking about uh the new immersion technologies, what is the brain computer interface technology? And then what are the main applications of this technology that could be applied in several feeds? Uh So when we talk about the new emerging technologies, uh I think it's, it is really important to talk about the previous uh and the evolution of the, the the previous technologies. And I will be starting by the operation like of, of, of uh uh the key keyboards and mouses uh to control some devices. And the PC then uh the graphical user interfaces to improve the way how to interact with this um those devices. And then the uh the apparition of mobile computing and the multi touch touch, sorry um to uh to use like our mobiles and then the operation to uh of conversa conversational interfaces like Google uh Google Home Alexia, some those assistants uh that's that give the user the possibility to interact with his environment, with his voice.

And then we all uh used for sure. Uh the technology of Xar uh uh X reality. So the augmented reality, the virtual reality or mixed reality. And um I don't know for you, but for me, I'm always asking myself like, what will be the next, what will be the next technology that could be used in inside feeds? And um according to this uh great report from reply uh about the human machine interfaces trend report, um they said that the next new tech immersion technology will be the brain computer interface. And the good news is that um we I will be given more information actually about this technology during this talk. So what is this brain computer interface? So brain computer interface actually is a field between the neuroscience and medicine and the main application or first application were were for clinical applications to help some patients uh with disabilities and the computer brain uh brain computer interface, which means we when we use our brain activity to interact with our external environment.

So the idea is how to use our heart to measure this activity and we can use use several um types of measurements. So there is a noninvasive measurements like e electroencephalographic where where the user can make uh uh um ABC I headset or eeg headset uh connecting some sensors on his uh on his uh head. And we uh we collect or we measure this activity. Uh There, there are some solution uh which we call invasive uh invasive BC I, which means we do like some surgery to put some sensors inside the brain of the patients. And it is used mainly for clinical applications. So once this brain activity is collected, we use some feature extraction method methods to extract some useful and relevant information for this brain signal. And that we that we call the biomarkers in neuroscience. So then those feature of interest will be classified using, for example, machine learning or deep learning or a signal decomposition methods to um classify and to just try to ex to understand what the user wants to do in his environment. For example, he wants to move a machine to control an external device or to move his uh processes, etcetera. And uh I want to highlight also that there are many types of non invasive BC I. So uh we we have three types mainly.

So the first one is active BC I, which means the user should like uh uh uh try to imagine like an activity. So for example, he he wants to move his arm. So he starts to uh thinking about moving his arm and then we treat like the signal and we did detect which uh and we detect that he wants to move his arm actually. And we can show to the user, for example, an avatar who show who moved the, the his arm. And the idea um uh behind that is that um we can use that for um rehabilitation uh especially for patients who are uh attended uh of uh post stroke um problems. Uh And then the reactive BC I, which means we show to the user an external uh an external stimuli which could be uh a visual or auditory. Uh And then the user um starts to focus on those stimuli. And when in the signal, we try to, to detect those um like the stimuli, that's uh that where the user where uh we was um like uh GZ in, let's say, and the basic PC I, which means that we, the user didn't use any uh movement or any uh any thoughts, let's say, and we collect basically the his um e signal and we try to, to, to, to measure his state actually, if he's stressed, if there is a fatigue, if he's workload, et cetera.

So it is more about the mental um workflow. So now let's uh see what, where we can use this actually, this BC I and I try to categorize those applications uh on uh six categories. So the first one is some clinical applications uh mainly used in the literature. Uh Then in education and training, how could we use this technology and then games and entertainment, security and authentication, new marketing. And I will be talking a bit about could we use actually this technology for the industry? I will be uh trying to ask this question too.

So the first clinical application that is really uh useful for some patients at um that has like post stroke and it is um like um a way to uh neurofeedback. So to show the user his biological activity and it is a way of rehabilitation or for example, to help him to see his activity of sleep and to to improve actually his sleep quality. So uh the first what, what, what you can see here in the first picture that the user is wearing ABC I headset. So we we collect with those sensors like his eg um brain activity and he is thinking or he is thinking about moving his arm, he is uh like uh he has like a post stroke, he can't actually move his arm. However, he can see on the screen that he can actually and there is like uh his brain is um already like active and he can move his arm and he this way we can rehabil re rehabilitate this patient. Another uh another um applications in clinical, which is the assistance. So we can use the BC I for communication, the assistance for communication, for example, for uh spellers. So we show to the user a screen and which is um a reactive BC I.

So we sh we show some uh um flickering icons with the letters and the user um can uh gaze on those um those icons um to, to, to spell or to write a word or a sentence. Um And then the second one is um is navigational assistance. So we can use actually for some patients who can't move or something like that, we can use uh an exoskeleton uh who can, who can do the uh the action or the motor uh for, for him, movements for, for him. Uh The second um the second field is the education in and the training and the idea is how to adapt the learning uh according to the personal performance. So uh according to the brain activity, we can discover that the user. Uh For example, he is um he is um maybe uh the, the training is more um like we, we, we, we should have like the less speed, let's say for, for the learning and adapt the learning process according to his brain activity. So the third um field is the gaming and entertainment. So there are lots of works um that are interested and on how to use the brain computer interface activity uh for gaming and especially for virtual reality gaming as well. The user were ABC I headset and he can play or interact with his uh virtual environment.

And other researchers are thought about uh how to create like um a, a group of um a game but uh in with the two players or more and they play only with their brain activity. So no movement, no vocal uh control, uh et cetera. So another applications um is um is the smart home. So imagine that you are in a smart home and you are using like your brain, uh your, your brain activity um to control your devices inside your home or maybe to adapt the your there, there is an adaptation, let's say of the, your environment, luminosity, et cetera according to your um um mental load or mental state if you are stressed, uh et cetera.

So, which is very uh interesting and question it actually. Uh So another field um there are some researchers who are, who are interested about the security and authentication and how to use, how to use the brain activity as a bio elected by you. Uh biometric, let's say uh to identify the person and um to identify the person and we can use it like for security um security and authentic and other fields uh you used um that's where the BC I could be used in the neuro marketing. So we can uh uh actually um maybe study like uh the pre preferences of the user according to his um uh brain signals. And uh we can do like some consumer profiling, etcetera. Uh So, uh I will give like this. Um So notes of um for, for the conclusion. So as uh you see like there is a growing interest in the those application of BC I in several uh fields. Uh So we show it in uh our talk like the deployment of BC applications um particularly in the rehabilitation ne feedback monitoring, um the mental state of user, for example, device control, new marketing training and other feeds. However, so the big question is uh if the society will, will accept actually those um this technology and um mainly so there are mainly um uh some challenges to be addressed before like some ethical uh challenges. So challenges are gonna make and technical challenges.

So because for now this technology is in uh laboratories. So the big question is how to do to bring this technology outside the laboratories, to the industry, to the operational um use. And if the user act actually accepts to use his brain signal or brain uh identity to um to several applications. Uh So what I say that um for for future work uh on my our project actually in my company. So we are working on how to use uh the brain computer interface for applications in industry 4.0. So for further question, I would be really glad, glad to, to get in touch with you. So please email me on this email or um um or connect with me on linkedin. I'm very active and I would be really happy to connect with you. Uh So some upcoming events if you are interested about the technology. So we have uh we will be having like um a conference brain info, which is a neuroscience conference uh about the application of uh B I for industry 4.0 in July. Uh And uh we submitted a new scientific articles that address uh the main applications for industry 4.0. But in depth, we talk about uh what are the main challenges and how could this cha cha challenges be addressed? So at the end, I would like to thank you very much for your uh attendance. Thank you and don't hesitate if you have some questions.

Mhm So Simon said you are showing very good visual to explain what can feel complicated in BC I I, actually, this technology is very complicated and uh as I highlighted, like it is more about the acceptability of this technology in our real world applications, let's say. So this is a very interesting and exciting. Thank you very much. A f um ethical and emotion A I with NBC I, it's an important topic. Perfect. Yeah, actually FF Neuro neuro Neuralink. Yeah, I I think they are working on uh technology. Uh Does this technology have bad effects on brain health? Uh Actually, no, no. Uh because we can um I'm not a neuroscientist, I'm not a medicine. Uh But if you are using like noninvasive BC I, you are just collecting like the data from the, the brain of the the user. And actually, it depends on the task because uh our like the neuroscientists create a task uh to see um some useful information, let's say uh in uh from the brain of the brain activity of the user. And then those uh information will be treated with uh uh with the data scientist, etcetera. So uh it depends actually on the task that you create uh for uh for this um for from the, the, the brain activity of the user.

Uh I think there are no more questions. Thank you very much for your attendance and uh let's connect on linkedin. Thank you.