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Community BrainFlow Implementation for the NeuroPawn KnightBoard Abdallah AlwanFeburary 10 2025 The NeuroPawn Knightboard finally got implementation into BrainFlow. BrainFlow is one of the largest open-source biosignal library. It supports a multitude of different programming languages, with the most notable being Python.  We thought, “why make a new library when? We can just implement our board into something many people already know and trust.” So that’s exactly what we did. BrainFlow is board agnostic so changing boards is as simple as just changing the name of the input device in your code. Check out some code examples on our GitHub and the tutorials page. Community

Community Intro to NeuroPawn Hardware Workshop Abdallah AlwanFeburary 10 2025 In October 2024, Abdallah Alwan the founder of NeuroPawn, gave a workshop lecture on NeuroPawn hardware, introduction to neurotech, and a live demonstration. This workshop focused on basic neuroscience concepts such as the neuron structure, the action potential, and summation. We then focused on how EEGs pick up signals from the surface of the scalp, where those signals come from, and what are some possible ways that signals can get distorted. After talking about some signal processing techniques such as FFT, High and Low-pass filters, and ways to improve the incoming data, we talked about different brain-computer interfacing paradigms. These included: Motor Imagery Steady State Visually Evoked Potentials Coded Visually Evoked Potentials P300 Event Related Potentials N400 Event Related Potentials We finished off the workshop by exploring NeuroPawn hardware hands-on and measuring our ECG signals. Community

Community NeuroPawn Sponsors ARmed Student Group Abdallah AlwanFeburary 10 2025 ARmed is a student group focused on implementing augmented reality in medicine. They approached NeuroPawn wanting to implement our Knight Board into the project to capture biosignals and make their glasses capture more than just hand-gestures. Furthermore, their equipment is expensive and they want students to gain some experience working with medical devices before jumping in on AR project. We thought this was a perfect chance to use NeuroPawn’s Biopotential Kit as a stepping stone to the bigger projects. Using our kit as a learning tool, student’s can build their skills and confidence to work on the complex projects such as their AR glasses. Community

Community natHACKS Hackathon Group Uses 2 NeuroPawn Headsets to Achieve Neural Synchrony Abdallah AlwanFeburary 10 2025 Last weekend the Goldilocks team (Hildelith Leyser, Sean Piatt, Ian Goodall-Halliwell, Zijing Wu, Sikanderdeep Singh Kingra, Megh Mistry) created WaveLinks: a neural synchrony detection platform. The purpose of this project was to enhance the patient-therapist connection during psychiatric treatment by evaluating the synchrony of their brainwaves. “This could potentially help therapists adjust in real time, building stronger emotional bonds, reducing stress, and improving outcomes for issues like depression, anxiety, and PTSD. WaveLink makes the invisible connection between patient and therapist visible, creating a new way to improve mental health treatment.” – WaveLink Github https://lnkd.in/e_NMSgQE The used two NeuroPawn Biopotential Kits to obtain EEG-data from the right temporopareital junction of two individuals. They then put the EEG data streams through their SURFER model (Self-sUpervised coRrelation Feature analyzER). This model preprocesses each data stream, puts them through a convolutional neural network, then through a multi-layer perceptron to extract features. Finally, they perform a cross correlational analysis to determine the sync score. What an innovative project by a group of extremely talented and passionate individuals. The combination of ML and Neurotech in this regard, will surely advance our ability to treat mental health issues. We are honored to have been part of this project. Community

Community natHACKS Hackathon Group Creates SSVEP Demo to Play Chess Abdallah AlwanFeburary 10 2025 Students at the University of Alberta utilized NeuroPawn hardware to create a game controller for Chess using the Steady State Visually Evoked Potentials (SSVEP) brain-computer interfacing paradigm. SSVEP works by locking a user’s visual cortex to the frequency of a flashing stimulus. For example, if you were looking at a 10 hz stimulus, the neurons at the back of your head would turn on and off at 10 hz.  This group exploited this phenomenon by extracting EEG signals from the back of the head. They were able to process that signal using a fast-fourier transform to extract the component frequencies. They then used filter bank canonical correlation analysis to determine the synchrony of different channels. Using these techniques they were able to control a chess game just by looking at specific stimuli.  Community

Community University of Calgary Capstone Group Tackles Inclusivity in Neurotech Abdallah AlwanFeburary 9 2025 Neurotech’s biggest hurdle is hair. In order to derive a signal that is adequate for inference, electrodes must touch your skin. This is a huge issue in neurotech, as hair makes it extremely difficult to touch the scalp and capture accurate biosignals. This, along with motion artifacts from hair strands makes it hard for newbies to get involved in neurotech, without strenuously studying signal processing pipelines, or exploring machine learning. Previous attempts have tried to solve this problem by creating conductive spike electrodes that are meant to glide past the hair. Although this partially fixes the problem, it creates more down the line. One of these problems is that comfort is decreased because the electrode rests on the scalp with a couple of spikes. Secondly, a helper is usually required for set up to make sure that the spikes don’t grab the hair and actually go through it. This decreases the overall usability of the product since it cannot be worn for too long, and requires assistance in setting up. However, the problem that trumps these two is that these spike electrodes still do not work on individuals with thick hair. This is where the innovative solution from the students at the University of Calgary steps in. They are designing a soft-tipped active spike electrode which works on a multitude of hair types. Their material of choice is a conductive silicone polymer which has flexible properties. This is paired with a narrow-spike design which allows for the spike to wedge itself in between hair fibers. Once contact is made with the scalp, the spikes flair out which increases the contact area, reducing the contact resistance and pressure. This not only increases comfort, but improves the signal quality.  This new electrode material and design will be paired with active amplification circuitry, which further reduces the electromagnetic interference, and improves signal quality. Follow along as these students enter the final stage development where they will use this new active electrode to make a brain-computer interface. Community