
During November 2024, Inevitable M. developed a real-time EEG data collection pipeline for the UniversumX/Universum repository, focusing on immediate capture and live visualization of EEG streams. Leveraging Python and the Lab Streaming Layer (LSL), they engineered a system that logs synchronized EEG data to CSV files, enabling rapid analysis and monitoring. Their work also included enriching sensor data collection for subject 106 by integrating accelerometer and action data, expanding the CSV schema and adding debugging instrumentation. This approach provided a robust foundation for scalable data pipelines, emphasizing real-time data processing, data visualization, and enhanced dataset quality for research workflows.

November 2024 monthly summary for UniversumX/Universum. Key features delivered include a real-time EEG data collection pipeline with LSL integration and live plotting, enabling immediate capture and monitoring of EEG streams. The pipeline logs data to eeg_data1.csv with precise timing information and supports rapid analysis through live visualization. Additionally, sensor data collection enrichment for subject 106 was implemented, adding accelerometer and action data to CSV outputs and introducing debugging instrumentation to support richer datasets. Major bugs fixed: no critical defects reported in scope; stability improvements in data capture and groundwork for debugging instrumentation. Commits associated with the EEG pipeline: 40afd0eeea7b01c3a892b80b094b54599cc04ef2; 7a49b2442777453b2f9a4de43cad5d76593c1b89; c1d0f9b88e0b7339cb44e7a88aa9037fcc65847e. The subject 106 enrichment was implemented in commit 0849c468697e5abbf479d38d5c5e943b85087eed (data collection debug). Overall, these efforts deliver real-time data capture with monitoring capabilities and richer, easier-to-analyze datasets, laying a foundation for scalable data pipelines and more robust research workflows. Technologies/skills demonstrated include real-time data streaming (LSL), data logging to CSV, live plotting, and instrumentation for debugging.
November 2024 monthly summary for UniversumX/Universum. Key features delivered include a real-time EEG data collection pipeline with LSL integration and live plotting, enabling immediate capture and monitoring of EEG streams. The pipeline logs data to eeg_data1.csv with precise timing information and supports rapid analysis through live visualization. Additionally, sensor data collection enrichment for subject 106 was implemented, adding accelerometer and action data to CSV outputs and introducing debugging instrumentation to support richer datasets. Major bugs fixed: no critical defects reported in scope; stability improvements in data capture and groundwork for debugging instrumentation. Commits associated with the EEG pipeline: 40afd0eeea7b01c3a892b80b094b54599cc04ef2; 7a49b2442777453b2f9a4de43cad5d76593c1b89; c1d0f9b88e0b7339cb44e7a88aa9037fcc65847e. The subject 106 enrichment was implemented in commit 0849c468697e5abbf479d38d5c5e943b85087eed (data collection debug). Overall, these efforts deliver real-time data capture with monitoring capabilities and richer, easier-to-analyze datasets, laying a foundation for scalable data pipelines and more robust research workflows. Technologies/skills demonstrated include real-time data streaming (LSL), data logging to CSV, live plotting, and instrumentation for debugging.
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