Vibrome® Biosignatures for Working Dogs

Vibrome® biosignatures are measurable patterns in the mechanical, acoustic, vibrational, flow-related and movement signals produced by a dog’s body. These patterns may provide information about physiological condition when collected and interpreted appropriately.

Electro-mechano-acoustical refers to electrical, mechanical and sound-related activity associated with living systems. Quantum K9™ describes analyzing combinations of these signals rather than relying on a single measurement.

The website describes detecting inaudible, imperceptible and invisible physiological signals. The actual signal range and sensitivity depend on the sensors, placement, environment and system configuration.

Multimodal sensors collect more than one type of signal or measurement. Combining signal types may provide a broader view of working-dog physiology, subject to data quality and validation for the intended use.

Quantum K9™ describes non-invasive sensing designed to avoid needles and minimize discomfort. The exact scanning method, contact requirements and operating procedure depend on the selected hardware.

The website describes lightweight sensors that may integrate with working-dog harnesses and vehicle pads. Fit, durability, safety, signal quality and freedom of movement should be evaluated before operational use.

AI-assisted analysis is intended to translate complex physiological signal patterns into simpler information or alerts. Results depend on the training data, algorithm, validation, operating conditions and intended use.

Neurosymbolic AI combines pattern-learning methods with rule- or knowledge-based reasoning. Quantum K9™ describes using this approach to help convert biosignature data into information relevant to handlers and care teams.

Actionable information should connect a measured pattern to a defined response, such as repeating a scan, reducing exertion or requesting veterinary review. Organizations should establish response procedures before field deployment.

Movement, sensor placement, environmental noise, harness fit, temperature, hardware condition and operator technique can affect signal quality. Quality checks are important before relying on a result.