{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pieeg-kit-bioscience-lab-in-home-for-your","title":"PiEEG kit - bioscience Lab in home for your Brain and Body","arxiv_id":null,"date":"2025-03-19","proceeding":null,"authors":["Ildar Rakhmatulin"],"abstract":"PiEEG kit is a multifunctional, compact, and mobile device that allows measure EEG, EMG, EOG, and EKG\r\nsignals. The PiEEG Box incorporates the Raspberry Pi-based PiEEG shield, an EEG electrode cap, a display\r\nscreen, additional sensors about body parameters and the environment, and other necessary peripherals,\r\nsoftware, and an SDK course to learn signal processing into a single, portable unit. This integrated solution\r\naddresses the need for a compact, user-friendly, and accessible EEG measurement tool for researchers and\r\nhobbyists. The PiEEG Box builds upon the open-source foundation of the original PiEEG device, offering 8-\r\nchannel EEG recording capabilities. By combining all required elements into one package, the PiEEG Box\r\nsignificantly reduces setup time and complexity, potentially broadening the application of EEG technology in\r\nvarious fields including neuroscience research, brain-computer interfaces, and educational settings.","url_abs":"https://arxiv.org/abs/2503.13482","url_pdf":"https://arxiv.org/pdf/2503.13482","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pieeg-kit-bioscience-lab-in-home-for-your","repo_url":"https://github.com/pieeg-club/PiEEG_Kit","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"eeg-1","task_name":"EEG"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}