Biological signal processing turns measured biological activity into data that can be analyzed, compared, visualized, and potentially sonified. Examples include neural, physiological, electrophysiological, and other biosignals.
What are biological signals?
Biological signals are measurable changes associated with living systems. Depending on the measurement method, they may be represented as electrical waveforms, time series, frequency-domain features, chemical measurements, or other structured data.
Core biological signal-processing steps
- Define the biological measurement and acquisition method
- Check signal quality and artifacts
- Filter or transform data when scientifically justified
- Extract reproducible features
- Compare measurements using appropriate controls
- Visualize and document the results
Neural and physiological signals
Neural and physiological measurements can be complex, noisy, and dependent on acquisition conditions. Reliable analysis therefore requires careful experimental design, transparent preprocessing, and clear separation between observed signals and interpretation.
From biological signals to sonification
After measurement and processing, selected signal features can be mapped to sound using a documented sonification method. The resulting audio is a representation of data; it is not automatically evidence of a biological or quantum mechanism. See Quantum Signal Sonification for the broader data-to-sound research pathway.
Related research: 4realsy Research Priority and Quantum Biology Explained.