PIEEG Low-cost Brain-computer interface (EEG, EMG, and ECG)
PIEEG Low-cost Brain-computer interface (EEG, EMG, and ECG)
For several years now we have been working on open source software projects. Our devices measure biosignals, such as those used in electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG).
Our goal is to make PiEEG universal, easy to use, and compatible with various types of electrodes. We develop them so that everyone can use them. To start measuring biosignals, all you need to do is connect the electrodes and run the Python script. Applications may include games, entertainment, sports, health, meditation, and more.
At the forefront of PiEEG’s development stands a team of multidisciplinary researchers, whose expertise spans the crucial intersections of hardware engineering, machine learning, and neuroscience. The contributions to the scientific community are exemplified by the authorship of multiple groundbreaking papers on BCIs, which have significantly advanced our understanding of hardware for neural interfaces and their applications. The commitment to open science is evident in the creation of open-source versions of many neuroscience inventions, fostering collaboration and accelerating progress in the field.
As a collective of hardware and software engineers, the PiEEG team brings a unique blend of skills to the project. Furthermore, proficiency in developing machine learning algorithms for EEG classification enables PiEEG to offer advanced signal analysis capabilities, pushing the boundaries of what’s possible in portable, accessible BCI technology.
PIEEG had success on the CrowdSupply platform, finally, we raised 6 times more than initially planned.
Ildar Rakhmatulin. PhD. Scientist, Engineer, and Entrepreneur in bioscience | Instructor Udemy
With a strong academic background in the UK (Imperial College, Heriot-Watt University, Edinburgh University), Ildar has published numerous papers on topics including deep neural networks for EEG feature extraction, low-cost brain-computer interfaces, and applications of artificial intelligence in various fields. His work has been widely cited, demonstrating his significant impact in the field of neurotechnology and BCI research. Rakhmatulin’s career spans multiple countries, including Japan, where he worked as a Research Development Electronic Engineer for five years. He is multilingual, speaking Russian, Spanish, Japanese, and English, which has likely contributed to his global perspective and collaborations in the field of neurotechnology.
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