ACQ to TXT Converter

ACQ to TXT Conversion Explained

Converting .ACQ to .TXT extracts physiological time-series data from the proprietary Biopac binary format into plain text. People convert .ACQ files to analyze raw signal data—such as ECG, EEG, or EMG recordings—outside of the official AcqKnowledge software.

When you convert .ACQ to .TXT, you gain universal compatibility. Any programming language or text editor can read the resulting file. However, you lose file efficiency. Because binary data is translated into ASCII characters, the resulting .TXT file is significantly larger. You also lose proprietary metadata, such as hardware configurations, subject details, and specific event marker formatting. If you only need to store the data long-term without analyzing it in third-party tools, this conversion is a bad idea due to the massive increase in file size.

Typical Tasks and Users

This conversion is primarily used by researchers, data scientists, and biomedical engineers. Common workflows include:

• Custom Signal Processing: Importing raw voltage values into Python (using Pandas or NumPy) or MATLAB to apply custom filters or machine learning models.
• Data Sharing: Sending physiological recordings to collaborators who do not own a paid Biopac AcqKnowledge license.
• Open Science Archiving: Publishing raw dataset values in a universally readable format for peer review or public repositories.

Software & Tool Support

Several tools can open, edit, or convert these formats:

• Biopac AcqKnowledge: The official, paid software that creates .ACQ files. It includes built-in options to export data to text.
• Bioread: An open-source Python library that can parse .ACQ files and extract data arrays via the command line.
• EEGLAB: A popular MATLAB toolbox that supports importing Biopac data for EEG analysis.
• Text Editors: Tools like Notepad++ or VS Code are required to open the resulting .TXT files, as standard Notepad will crash when opening large datasets.

Pros and Cons of the Conversion

Pros:

• Universal Compatibility: .TXT files can be opened on any operating system without proprietary software.
• Scriptability: Plain text is easily parsed by R, Python, Julia, and MATLAB.
• No Vendor Lock-in: Ensures your raw data remains accessible even if Biopac software is unavailable.

Cons:

• File Size Explosion: High-frequency physiological data converted from binary to ASCII text often becomes 5 to 10 times larger.
• Metadata Loss: Hardware settings, channel labels, and sample rate information are often stripped or reduced to basic text headers.
• Performance: Reading and writing gigabytes of plain text is much slower than processing binary data.

Conversion Difficulties & Why Convert.Guru

The real technical problem in this conversion is the .ACQ format itself. Biopac has released multiple versions of the format over the years (Windows vs. Mac versions, old vs. new AcqKnowledge releases). Extracting the correct sampling rate, handling multiplexed channels, and aligning event markers with the correct time-series data requires precise binary decoding. If the conversion tool misinterprets the byte order (endianness) or the channel scaling factors, the resulting text data will be corrupted.

Convert.Guru handles this conversion accurately by managing the binary decoding pipeline for you. It reads the proprietary headers, applies the correct scaling factors to the raw voltage data, and outputs clean, tab-delimited or comma-separated .TXT columns. This allows you to convert .ACQ to .TXT reliably without writing custom Python scripts or purchasing expensive software licenses.

ACQ vs. TXT: What is the better choice?

Which format should you choose?

Choose .ACQ for data collection, active recording, and storage. If you are working entirely within the Biopac ecosystem, keep the file in its native format to save disk space and preserve all experiment settings.

Choose .TXT when you need to process the signals in custom scripts, share data with non-Biopac users, or archive raw values in an open format.

Note: If you are converting for statistical analysis, consider converting to .CSV instead of plain .TXT for better spreadsheet compatibility, or .EDF (European Data Format) if you need an open format that still supports physiological metadata.

Conclusion

Converting .ACQ to .TXT makes sense when you need to free your physiological data from proprietary software for custom analysis in Python, R, or MATLAB. The biggest limitation to watch for is the massive increase in file size, which can make standard text editors freeze. Convert.Guru provides a reliable, script-free solution for this exact conversion, ensuring your multi-channel data and scaling factors are accurately translated into plain text.