nervous-sensors 0.2.0

Python backend for connection to ECG and EDA sensors from the Lyon Institute of Nanotechnology (INL)

Nervous Sensors

Table of Contents

• Table of Contents
• Project Overview
  • Key Features
• Prerequisites
• Installation
• Command-Line Interface (CLI)
  • Usage
    • Options
  • Example Command
• Sensor Compatibility
• Contributing
• License
• Acknowledgments
• Contact

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Project Overview

Nervous Sensors is a Python-based driver and data acquisition toolset for physiological sensors, specifically designed for Nervous ECG (Electrocardiography) and Nervous EDA (Electrodermal Activity) sensors developed in the frame of the Nervous Toolkit.

Key Features

• 📱 Bluetooth Low Energy (BLE) sensor support
• 📈 Real-time data visualization via local webserver
• 💾 Flexible data storage (CSV export)
• 📣 LSL (Lab Streaming Layer) integration for PLUME Unity plugin
• 🔗 Multi-sensor connection capabilities

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Prerequisites

• Python 3.11, 3.12 or 3.13
• Compatible Bluetooth Low Energy Nervous sensors

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Installation

pip install nervous-sensors

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Command-Line Interface (CLI)

Usage

nervous [OPTIONS]

Options

Option	Description	Example
-s, --sensors	Specify sensors to connect (by serial number)	"ECG 6543","EDA 7201"
-g, --gui	Enable real-time data graph in web browser
-f, --folder	Save CSV data files to specified folder	./data/csv/
-l, --lsl	Send sensor data to LSL outlets
-p, --parallel	Set number of parallel connection attempts

Example Command

# Connect to multiple sensors, enable GUI, save to CSV, and activate LSL
nervous -g -f ./data/csv/ -l -s "ECG 6543","EDA 7201"

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Sensor Compatibility

• Nervous ECG Sensors
• Nervous EDA Sensors

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Contributing

Contributions are what make the open-source community such a great place to learn, inspire, and create. Any contributions you make are greatly appreciated. You can open an issue to report a bug, request a feature, or submit a pull request.

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License

This project, along with the entire Nervous initiative, is licensed under the MIT License. For more details, see the License file.

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Acknowledgments

The main contributors to this project are Bertrand Massot, Tristan Habémont and Hugo Buy from INSA Lyon, CNRS, INL UMR 5270, Villeurbanne, France.

This work was supported by the French National Research Agency (ANR) under grant ANR-22-CE31-0023-03 RENFORCE.

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Contact

[e-mail]

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