Abstract: A signal interpretation engine apparatus and method are disclosed as including a computer programmed to run a feature expansion module, a weight table module, a consolidation module, and a map generation module. The feature expansion module contains feature operators for operating on a signal to expand the signal to form a feature map of feature segments. Each feature segment corresponds to a unique representation of the signal created by a feature operator from the signal across an epoch. An epoch corresponds to an event within a time segment. A consolidation module applies aggregators to consolidate the inner products or superposition segments into a distribution function representing an attribute over a domain reflecting a selected weight table, aggregator, and event type, corresponding to each value of the attribute.

Abstract: A method for assessing a condition of an organism having body waves corresponding to states of the organism. The method includes the step of recording signals corresponding to a body wave, output by a portion of the organism in a first state, to provide a first record. In a similar manner, signals are recorded during a time period in which the organism is in a second state, to provide a second record. The first and second records, are processed by applying feature expansion procedures thereto. The results of the feature expansion procedures are evaluated to identify first selected feature expansion procedures effective to distinguish values of the first signals corresponding to the first state from values of the first signals corresponding to the second state.

Abstract: A signal interpretation engine apparatus and method are disclosed as including a computer programmed to run a feature expansion module, a weight table module, a consolidation module, and a map generation module. The feature expansion module contains feature operators for operating on a signal to expand the signal to form a feature map of feature segments. Each feature segment corresponds to a unique representation of the signal created by a feature operator from the signal across an epoch. An epoch corresponds to an event within a time segment. A consolidation module applies aggregators to consolidate the inner products or superposition segments into a distribution function representing an attribute over a domain reflecting a selected weight table, aggregator, and event type, corresponding to each value of the attribute.

Abstract: A signal interpretation engine apparatus and method are disclosed in certain presently preferred embodiment as including a computer programmed to run a plurality of modules comprising a feature expansion module, a weight table module, a consolidation module, and a map generation module. The feature expansion module contains feature operators for operating on a signal to expand the signal to form a feature map of feature segments Each feature segment corresponds to a unique representation of the signal created by a feature operator operating on the signal across an epoch. An epoch corresponds to an event occurring within a time segment. The weight table module provides a weight table having weight elements Each weight element has a weight corresponding to a feature segment of the feature map. The consolidation module provides a superposition segment by combining the feature segments of the feature map corresponding to the epoch by forming an inner product of the feature map and the weight table.