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Bio-Silicon Bidirectional Synergetic Learning GUI | ||
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GUI Elements and Data Presentation: | ||
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Live Data Visualization: | ||
Neural Activity Maps: 3D/2D brain maps showing real-time activity. | ||
Signal Waveforms: Live EEG/neural waveforms with zoom capabilities. | ||
Data Metrics: Key metrics like signal strength, frequency bands, and synchronization. | ||
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Quick-Render Neural Visualizations: | ||
Simplified Heatmaps: Fast-rendering heatmaps for activity levels. | ||
Real-Time Graphs: Streamlined signal graphs for live data. | ||
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Cyberpunk-Style Data Displays: | ||
Neon Accents: Highlighting key data points. | ||
Abstract Data Art: Cyberpunk-inspired art forms for complex data representation. | ||
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Biopunk Elements: | ||
Organic Textures and Dynamic Forms: Bio-inspired backgrounds and animations. | ||
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Historic Data Access: | ||
Timeline Control and Session Summaries: Easy navigation and session overviews. | ||
Comparative Analysis Tools: Side-by-side data comparisons. | ||
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System Status and Control: | ||
Connectivity Indicators: Status of MEA, ADCs, DACs, and FPGA connections. | ||
Stimulation Controls: Interface for brain stimulation adjustments. | ||
Signal Processing Settings: Customization of signal processing parameters. | ||
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Notifications and Alerts: | ||
Dynamic alerts for critical statuses and pattern recognitions. | ||
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AI Elements Integration: | ||
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Neural Signal to Action Mapping: | ||
Interactive Neural Maps and Action Prediction Panel: Correlating neural signals with actions and predicting potential responses. | ||
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Environment to Neural Signal Mapping: | ||
Environmental Influence Visualization and Feedback Loop: Showing the impact of environmental changes on neural activity. | ||
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Language Optimization and Learning: | ||
Symbolic Language Panel and Learning Progress Tracker: Visualizing AI-driven language optimization and efficacy over time. | ||
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UI Design Aesthetics: | ||
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Color Scheme: Dark backgrounds with blues, purples, greens, and red accents. | ||
Typography: Modern, readable fonts with cyberpunk-styled elements. | ||
Graphical Elements: Biopunk motifs, sleek icons, and minimalistic controls. | ||
Animations and Transitions: Smooth updates with selective neon glow effects. | ||
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User Experience (UX): | ||
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Intuitive Navigation: Clear layout with collapsible menus for a clean interface. | ||
Responsive Design: Adaptability to various screens and touch-friendly controls. | ||
Customization Options: Layout personalization and notification settings. | ||
Help and Documentation: Integrated guides with tooltips for user support. | ||
Feedback Mechanisms: Channels for reporting issues or suggesting improvements. | ||
Interactive AI Insights: Exploration of AI-generated hypotheses and effects. | ||
Customizable Visualization Settings: User choice in data display and themes. | ||
Tooltip Explanations: Informative hover-over details for AI elements. | ||
Real-Time Rendering Performance Indicators: Alerts for any rendering delays or issues. | ||
Include indicators showing the performance of real-time renderings, ensuring users are aware of any delays or processing issues. | ||
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...llligence-BCI-V0.9/BCI-V.09/V0.9.1/.ipynb_checkpoints/BCI_V0.9-checkpoint.1_documentation
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This document outlines the design specifications for a Brain-Computer Interface (BCI) system intended for the transmission and reception of neural signals between a biological brain/organoid and a computer system. The design is focused on the electronic components, signal processing units, and interfacing protocols, specifically employing Cyclone IV FPGAs for digital signal processing. | ||
System Components | ||
Analog Front-End (AFE) | ||
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Instrumentation Amplifiers (IA): Each of the 64 channels is equipped with a separate PCB hosting an AD620 module to amplify neural signals. This configuration ensures clean signal acquisition with minimal interference. | ||
Analog-to-Digital Converters (ADC): For every two channels, a separate PCB with a PCM1802 module is used, taking advantage of its stereo input capability to convert the analog signals into digital data with high fidelity. | ||
Digital-to-Analog Converters (DAC): Similarly, every two channels share a PCB with a CS4344 module for converting digital signals back into analog form, maintaining the stereo output feature of the DACs. | ||
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Digital Processing Unit | ||
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Field-Programmable Gate Arrays (FPGA): Cyclone IV FPGAs are responsible for the real-time processing and routing of neural signals, as well as the gain of the amps, and the system clocks. | ||
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Communication Protocols | ||
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I2S | ||
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Power Supply Design | ||
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Linear Regulators: To ensure clean power delivery, 3.3V and 5V linear regulators are used across the system. These regulators provide stable voltage levels and reduce noise, which is critical for maintaining signal integrity. | ||
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Printed Circuit Board (PCB) Design | ||
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Capacitors: A combination of 1 µF, 100 nF, and 10 nF capacitors are strategically placed across the PCBs to filter out noise and stabilize the power supply lines, further enhancing signal quality. | ||
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Additional documentation of the breakout boards and FPGA: | ||
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AD620 documentation: | ||
https://www.electroschematics.com/module/ | ||
https://protosupplies.com/product/ad620-instrumentation-amplifier-module/ | ||
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AD620 purchase link: | ||
https://pt.aliexpress.com/item/1005003617853134.html?spm=a2g0o.cart.0.0.39037f06n6T8mc&mp=1&gatewayAdapt=glo2bra | ||
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CS4344 documentation: | ||
https://store.siqma.com/cs4344-dac-module.html | ||
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CS4344 purchase link: | ||
https://pt.aliexpress.com/item/1005004996846258.html?spm=a2g0o.cart.0.0.39037f06n6T8mc&mp=1&gatewayAdapt=glo2bra | ||
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PCM1802 documentation: | ||
https://raspberrypi.stackexchange.com/questions/107778/how-to-use-rpi-python-to-control-pcm1802-24-bit-hifi-stereo-adc-and-max4466-micr | ||
https://www.pjrc.com/pcm1802-breakout-board-needs-hack/ | ||
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PCM1802 purchase link: | ||
https://pt.aliexpress.com/item/32867094207.html?spm=a2g0o.cart.0.0.39037f06n6T8mc&mp=1&gatewayAdapt=glo2bra | ||
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Cyclone IV documentation: | ||
https://www.intel.com/content/www/us/en/docs/programmable/767845/current/cyclone-iv-featured-documentation-quick.html | ||
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Cyclone IV purchase link: | ||
https://pt.aliexpress.com/item/4000837637863.html?spm=a2g0o.cart.0.0.39037f06n6T8mc&mp=1&gatewayAdapt=glo2bra |
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lab_equipment_designs/steps_for_biosafety_cabinet_design_and_airflow_simulation
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Modeling the Physical Structure: Use FreeCAD to model the physical structure of the biosafety cabinet including the main chamber, passbox, latches, and fans. | ||
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Designing Moveable Parts: Utilize the assembly workbenches in FreeCAD to design parts that can move or be interacted with, like door latches. | ||
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Airflow Simulation Preparation: Use the model you created as the basis for setting up an airflow simulation. This might involve defining the inlet and outlet regions for air, setting up the fans' positions, and assigning material properties. | ||
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Performing Airflow Simulation: Export the model to a CFD software like OpenFOAM or use a FreeCAD workbench that integrates CFD capabilities to perform the airflow simulation. | ||
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Analysis and Iteration: Analyze the simulation results to optimize the design for airflow, pressure control, and ergonomics. Make iterative changes to the design as necessary. |