Dataset Title: “ECLectic. WP3 Task 3.1. Versatile Electrochemiluminescence Imaging Platform for Multiplexed Biosensing and Point-of-Care Application”. 
Dataset Author: Stephania Rodríguez Muiña (BCMaterials and University of the Basque Country-UPV/EHU), ORCID (0009-0006-3196-8964); Gabriele Giagu (University of Bologna), ORCID (0009-0003-9755-2986); Giovanni Valenti (University of Bologna), ORCID (0000-0002-6223-2072); Javier del Campo García (BCMaterials and University of the Basque Country-UPV/EHU), ORCID (0000-0002-3637-5782). 
Dataset Contributors: Giovanni Valenti (University of Bologna), ORCID (0000-0002-6223-2072).              
Dataset Contact Person: Javier del Campo García (BCMaterials and University of the Basque Country-UPV/EHU), ORCID (0000-0002-3637-5782), javier.delcampo@bcmaterials.net; Giovanni Valenti (University of Bologna), ORCID (0000-0002-6223-2072), g.valenti@unibo.it.
Dataset License: this dataset is distributed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, https://creativecommons.org/licenses/by/4.0/.
Publication Year: 2026
Project Info: ECLectic, funded by European Union, MSCA Doctoral Network Horizon Europe programme. Grant Agreement num. 101119951
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Folder "Scripts" contents

The folder consists of:

• 7 codes
"1_Main_mono_camera.py"
"1-1_Electrode_initial_capture.py"
"1-2_a_Methodscript_CA_1_3-0V_1_1s_3steps.txt"
"1-2_b_Methodscript_CV_0-2_0V_100mVs.txt"
"1-2_c_Methodscript_OCP_2s_CA_2V_5s.txt"
"1-2_Potentiostat.py"
"1-3_Frame_analysis.py"
• 1 Readme file
"Scripts_README.txt"

Abstract
This dataset provides the Python control software and electrochemical MethodSCRIPT files used to operate and validate a synchronized electrochemiluminescence (ECL) imaging platform. The platform integrates a Raspberry Pi 4B, a monochrome OV9281 global-shutter camera, and an EmStat4s potentiostat to enable temporally synchronized acquisition of optical ECL signals and electrochemical data. The codes support camera configuration, live preview, electrode image acquisition, potentiostat control via MethodSCRIPT, synchronized data recording, region-of-interest (ROI)–based image analysis, background subtraction, and quantitative data export. Together, these tools demonstrate reliable camera–potentiostat synchronization and provide a complete open-source workflow for ECL data acquisition and analysis.

Content of the files 
• file "1_Main_mono_camera.py" is the main control script that orchestrates the entire acquisition workflow. It initializes the OV9281 monochrome camera, manages live preview and user interaction, coordinates synchronization with the potentiostat, triggers electrochemical measurements, and controls the simultaneous recording and saving of optical frames, videos, and metadata.
• file "1-1_Electrode_initial_capture.py" contains a code to acquire the initial electrode image prior to the electrochemical experiment. This image serves as the reference for manual focusing, sample positioning, and subsequent region-of-interest (ROI) selection during image analysis.
• file "1-2_a_Methodscript_CA_1_3-0V_1_1s_3steps.txt" contains a methodSCRIPT file defining a multi-step chronoamperometry (CA) protocol, specifying potential steps, durations, and acquisition parameters to be executed by the EmStat4s potentiostat.
• file "1-2_b_Methodscript_CV_0-2_0V_100mVs.txt" contains a methodSCRIPT file defining a cyclic voltammetry (CV) protocol, including potential window and scan rate, used for electrochemical characterization and synchronization testing.
• file "1-2_c_Methodscript_OCP_2s_CA_2V_5s.txt" contains a methodSCRIPT file defining the open-circuit potential (OCP) followed by chronoamperometry (CA) protocol used in ECL experiments (OCP for 2 s, then a 2 V step for 5 s).
• file "1-2_Potentiostat.py" contains a Python module responsible for communication with the EmStat4s potentiostat. It handles loading and execution of MethodSCRIPT files, data acquisition, timestamping, and saving electrochemical outputs in CSV format for synchronization with optical data.
• file "1-3_Frame_analysis.py" contains a post-acquisition analysis script that enables interactive ROI selection, background subtraction using dark reference frames, pixel intensity integration, temporal alignment of optical and electrochemical data, and generation of plots and synchronized CSV datasets. It also produces processed PNG and TIFF images for qualitative visualization.

File Specifics
All .py files in this dataset correspond to control and analysis software developed and tested on a Raspberry Pi 4B running Debian GNU/Linux 12 (Bookworm). The software is written in Python 3.11.2 and is intended to control and synchronize image acquisition and electrochemical measurements.

Format:
	- Source code: .py files (UTF-8 encoded) 
	- Electrochemical methodscripts: .txt files (MethodSCRIPT format)

Requirements
The following Python packages are required to run the control and analysis scripts:
# Core Camera and Image Processing
	picamera2 >= 0.3.31
	opencv-python >= 4.5.0
	Pillow >= 9.4.0
	tifffile >= 2023.2.3
# Data Analysis and Scientific Computing
	numpy >= 1.24.2
	pandas >= 1.5.0
	matplotlib >= 3.6.3
#File and System Operations
	python-dotenv >= 0.21.0
#Serial Communication (Potentiostat Interface)
	pyserial >= 3.5
#File Sorting and Organization
natsort >= 8.0.0
#Spreadsheet Support
openpyxl >= 3.0.0
#Standard Library Modules (No Installation Required)
os
sys
glob
csv
time
subprocess
threading
concurrent.futures
datetime
re
logging