Electrophysiological signal processing method, corresponding system, vehicle and computer program product

A system comprising:

• processing circuitry configured to perform operations of:
• receiving at least one electrophysiological signal;
• segmenting the at least one electrophysiological signal to produce a set of sampled waveforms;
• producing a set of randomly generated noise samples;
• applying artificial neural network processing to the set of sampled waveforms and to the set of randomly generated noise samples to produce at least one altered data pattern, wherein the altered data pattern comprises the set of sampled waveforms altered as a function of the randomly generated noise samples;
• providing calibration data comprising expected waveforms for the sampled waveforms in the set of sampled waveforms;
• applying classifier processing to the produced at least one altered data pattern to detect a degree of resemblance between the produced at least one altered data pattern and the calibration data, wherein the classifier processing produces classification signals having values above or below at least one threshold value as a function of the detected degree of resemblance;
• and
• triggering a user circuit as a function of the classification signal.

A computer program product loadable into a memory of at least one processing circuit, and comprising software code portions for executing, when the product is run on the at least one processing circuit, steps of:

• segmenting at least one electrophysiological signal to produce a set of sampled waveforms;
• producing a set of randomly generated noise samples;
• applying artificial neural network processing to the set of sampled waveforms and to the set of randomly generated noise samples to produce at least one altered data pattern, the altered data pattern comprising the set of sampled waveforms altered as a function of the randomly generated noise samples;
• providing calibration data comprising expected waveforms for the sampled waveforms in the set of sampled waveforms;
• applying classifier processing to the produced at least one altered data pattern to detect a degree of resemblance between the produced at least one altered data pattern and the calibration data, wherein the classifier processing produces classification signals having values above or below at least one threshold value as a function of the detected degree of resemblance;
• and
• triggering a user circuit as a function of the classification signals.