System and method to detect the presence and progression of diseases characterized by systemic changes in the state of the vasculature

A system for detecting an internal condition in a living body comprising:

• a plurality of sensors configured to generate respective data streams corresponding to physiological characteristics at a plurality of anatomically distinct locations of the body;
• a controller configured to synchronize the respective data streams to generate a multi-anatomic data stream;
• and
• a processor configured to:
• receive the multi-anatomic data stream;
• extract features comprising at least one of temporal features, spatial features, and cross-anatomic correlation features;
• distinguish signals corresponding to different tissue regions based on characteristics of the multi-anatomic data stream;
• and
• generate an output indicative of a probability of the internal condition based on the extracted features and the distinguished signals.

A method for detecting an internal condition in a living body comprising:

• obtaining, from a plurality of sensors positioned at a plurality of anatomically distinct locations, respective data streams corresponding to physiological characteristics;
• synchronizing the respective data streams to generate a multi-anatomic data stream;
• processing the multi-anatomic data stream to:
• extract features comprising at least one of temporal features, spatial features, and cross-anatomic correlation features;
• distinguish signals corresponding to different tissue regions;
• and
• generating an output indicative of a probability of the internal condition based on the extracted features and the distinguished signals.

A wearable system for detecting an internal condition in a living body comprising:

• a wearable support structure configured to be positioned on a body of a subject;
• a plurality of sensors coupled to the wearable support structure and configured to generate respective data streams corresponding to physiological characteristics at a plurality of anatomically distinct locations;
• a controller configured to synchronize the respective data streams;
• and
• a processor configured to:
• receive the synchronized data streams;
• generate a multi-anatomic data representation;
• extract features including at least one of temporal features, spatial features, and cross-anatomic correlation features;
• and
• generate an output indicative of a probability of the internal condition based on the multi-anatomic data representation.