Sensessignal

Sensessignal is a term used in discussions of sensory information processing to denote signals that convey perceptual content within an information processing system. It is a coined term rather than a widely standardized label, and its precise definition can vary across disciplines. In some usages, sensessignals contrast with higher-level command signals or inferred states, focusing specifically on the raw or processed data that encode sensory information.

In practice, a sensessignal refers to data streams that carry modality-specific content such as vision, audition, or touch, along with their temporal and spatial characteristics. These signals can originate from external sensors, such as cameras, microphones, or tactile sensors, or from neural recordings that reflect sensory cortex activity. Common measurement modalities include electrophysiological techniques like EEG or intracortical recordings, as well as conventional sensor data transformed to a sensory feature space.

Processing sensessignals typically involves stages of preprocessing, feature extraction, and decoding or interpretation. Techniques may include filtering, spectral analysis, time-frequency representations, and machine learning methods to map sensory signals to perceptual states, stimuli, or actionable outputs. The goal is to preserve relevant sensory information while reducing noise and dimensionality to facilitate downstream tasks such as control, perception, or human–machine interaction.

Applications of the concept span neuromotor interfaces, sensory substitution and augmentation, robotics, and multisensory integration research. In brain–computer interfaces, sensessignals can enable users to interact with devices through perceptual or sensory-related neural activity. The term remains niche and is used selectively, with ongoing work aimed at clarifying definitions and improving cross-disciplinary communication around sensory data streams.