docs: use custom logo.jpg and update README badges

Author: Jshulgach

ANNOUNCEMENT_DRAFT.md

@@ -0,0 +1,33 @@
+# Drafting your LinkedIn Announcement
+
+This post is designed to be visually engaging and highlight the value to both the neurotech community and researchers.
+
+## Option 1: Feature-Focused (Best with a GIF/Video of the Real-Time Viewer)
+
+**Headline:** ✨ Announcing `python-oephys` v0.1.0: Streamlining Real-Time Electrophysiology! ✨
+
+I’m thrilled to release `python-oephys`, a comprehensive open-source Python toolkit for the [Open Ephys](https://open-ephys.org/) ecosystem. 🦾🧠
+
+Working with high-density neural data shouldn't mean spending weeks on boilerplate I/O. We’ve built this to bridge the gap between acquisition and real-time inference.
+
+**What's inside?**
+- 🔴 **Seamless ZMQ Streaming**: Live acquisition directly from the Open Ephys GUI.
+- 🎛️ **High-Performance Processing**: Optimized filters and automated signal quality (QC) checks.
+- 🤖 **End-to-End ML**: Hybrid CNN-LSTM models for real-time gesture recognition.
+- 📊 **Interactive Tooling**: Real-time plots and desktop applications for trial segmentation.
+
+Whether you're building closed-loop systems or performing deep offline analysis, `python-oephys` provides the unified high-performance foundation you need.
+
+🚀 **Get started:** `pip install python-oephys`
+💻 **Code & Examples:** [https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys]
+
+A big thank you to the Neuromechatronics Lab at Carnegie Mellon University for the support in bringing this release to life!
+
+#Neurotech #OpenEphys #EMG #MachineLearning #Python #OpenSource #SignalProcessing #CMU #BrainComputerInterface
+
+---
+
+## Tips for your post:
+1. **The Visual is Key**: Record a 15-second screen capture of the `RealTimeEMGViewer` running. It makes the project feel "real" and interactive.
+2. **Tag the Lab**: Tag the Neuromechatronics Lab page and any core collaborators like Max Murphy or Adrian Foy.
+3. **The First Comment**: LinkedIn loves engagement. Post the link to the GitHub repo in the *first comment* instead of the post body to maximize algorithm reach.

README.md

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+![Logo](https://raw.githubusercontent.com/Neuro-Mechatronics-Interfaces/python-open-ephys/main/docs/figs/logo.jpg)
+
 # Python OEphys
 
-[![Python](https://img.shields.io/badge/python-3.10%2B-blue)](https://www.python.org/)
+[![Docs](https://img.shields.io/badge/docs-online-blue.svg)](https://neuro-mechatronics-interfaces.github.io/python-open-ephys/)
+[![Python](https://img.shields.io/badge/python-3.10+-blue)](https://www.python.org/)
 [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
 [![PyPI version](https://badge.fury.io/py/python-oephys.svg)](https://badge.fury.io/py/python-oephys)
+[![Downloads](https://pepy.tech/badge/python-oephys)](https://pepy.tech/project/python-oephys)
 
 **python-oephys** is a comprehensive Python toolkit for working with Open Ephys devices and electrophysiology data. From file loading to real-time ZMQ streaming, signal processing to machine learning, and visualization tools—everything you need for high-density neural data analysis in one package.
 

docs/figs/logo.jpg

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+---
+title: 'python-oephys: A Unified Python Toolkit for Real-Time Open Ephys Data Processing and Machine Learning'
+tags:
+  - Python
+  - electrophysiology
+  - Open Ephys
+  - EMG
+  - real-time
+  - machine learning
+authors:
+  - name: Jonathan Shulgach
+    orcid: 0000-0000-0000-0000
+    affiliation: 1
+affiliations:
+  - name: Neuromechatronics Lab, Carnegie Mellon University, Pittsburgh, PA, USA
+    index: 1
+date: 26 January 2026
+bibliography: paper.bib
+---
+
+# Summary
+
+`python-oephys` is an open-source Python library designed to facilitate the acquisition, processing, and analysis of high-density electrophysiology data, specifically targeting the Open Ephys ecosystem. It provides a unified interface for both offline analysis of binary recordings and real-time streaming via ZeroMQ (ZMQ). Key capabilities include modular signal processing pipelines, automated channel quality assessment, and integrated machine learning models (CNN-LSTM) optimized for low-latency gesture classification.
+
+# Statement of need
+
+The Open Ephys GUI is a widely used platform for neural data acquisition, but researchers often face significant friction when transitioning from raw data acquisition to real-time closed-loop control or advanced offline analysis. Existing tools often handle either file I/O or real-time streaming, but rarely both in a unified, high-performance package. 
+
+`python-oephys` satisfies this need by providing:
+1. **Unified I/O**: A consistent API for both `.oebin` and `.npz` formats.
+2. **Real-time Integration**: Low-latency ZMQ clients that allow Python scripts and GUI applications to react to live neural streams.
+3. **ML-Ready Pipelines**: Pre-integrated deep learning architectures tailored for spatio-temporal neural signals, reducing the time required to build predictive models for BCIs or myoelectric control.
+
+# State of the field
+
+Similar tools like `LibEMG` focus on general myoelectric control, while the official `open-ephys-python-tools` provide basic file reading. `python-oephys` bridges these domains by specializing in the high-density spatial configurations typical of Open Ephys hardware while providing the real-time application layer (viewers and decoders) missing from low-level I/O libraries.
+
+# Key Features
+
+- **Real-time ZMQ Client**: Handles multi-channel streaming with minimal overhead.
+- **Channel QC**: Implements automated noise floor and saturation detection.
+- **EMGClassifierCNNLSTM**: A hybrid neural network for spatio-temporal feature extraction.
+- **Applications**: Includes desktop GUIs for data visualization and manual trial segmentation.
+
+# Acknowledgements
+
+This work was supported by the Neuromechatronics Lab at Carnegie Mellon University.
+
+# References

paper.md

@@ -30,6 +30,12 @@ dependencies = [
     "open-ephys-python-tools",
     "pylsl",
 ]
+[project.urls]
+Homepage = "https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys"
+Documentation = "https://neuro-mechatronics-interfaces.github.io/python-open-ephys/"
+Repository = "https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys.git"
+Issues = "https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys/issues"
+
 # dynamic = ["version"]
 
 [build-system]

pyproject.toml

@@ -14,7 +14,7 @@
 __author__ = "Jonathan Shulgach"
 __email__ = "jshulgac@andrew.cmu.edu"
 __license__ = "MIT"
-__url__ = "https://github.com/jshulgach/intan-python"
+__url__ = "https://github.com/Neuro-Mechatronics-Interfaces/python-open-ephys"
 __description__ = "Python interface for streaming, parsing, and analyzing Open Ephys files"
 
 submodules = [