Reliable physiological recordings depend on consistent data quality. Identifying recording problems during acquisition allows researchers to address them while the participant is still in the lab. This training demonstrates how Power Analysis in AcqKnowledge software provides quantitative feedback for real-time signal quality monitoring and post-acquisition review.

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Spectral measures can reveal interference and artifacts that are difficult to identify through waveform inspection alone. Using examples from electrodermal activity (EDA), electrocardiography (ECG), and other physiological recordings, we’ll explore how Power at line frequency, Power outside of band, and Total and Band power over time help flag mains interference, out-of-band noise, motion artifacts, and potential electrode problems.

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Because absolute signal power depends on signal amplitude and acquisition gain, individual power values can be difficult to interpret. You’ll learn how to combine Power Analysis outputs in the Expression calculation channel to calculate normalized signal-quality ratios and build a real-time quality index with configurable thresholds. We’ll also cover analysis settings and reusable configurations that support consistent quality checks across participants and recording sessions.

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In this training, you’ll learn to:

• Identify spectral measures that help detect line-frequency interference, out-of-band noise, and transient artifacts.
• Configure Power Analysis calculation channels for real-time monitoring and apply Power Analysis to recorded data.
• Select window width, update interval, preprocessing, and analysis basis to support timely detection of recording problems.
• Use the Expression calculation channel to calculate signal-quality ratios from multiple Power Analysis channels.
• Combine ratios into a quality index with defined thresholds and save the configuration as a preset or Workflow.

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Join us to strengthen your physiological data acquisition and review workflows with quantitative signal quality checks.