Rapid Profile Viscometer Devices And Methods

A method, comprising:

• receiving, at a trained algorithm, first data including a first WBV of a subject collected at a first time and at a shear rate of from about 1/s to about 1000/s;
• and
• (1) determining, by the trained algorithm, a correlation between the first data and a first physiological state, the correlation being indicative of a physiological state of the subject, or
• (2) receiving, at the trained algorithm, second data including a first WBV of a subject collected at a second time and at a shear rate of from about 1/s to about 1000/s, and determining, by the trained algorithm, a correlation between the first data and the second data, the correlation being indicative of a current or future physiological state of the subject.

A system, comprising

• a viscometer stage,
• the viscometer stage configured to receive a whole blood sample from a subject and determine a WBV of the sample at one or more shear rates of from 1/s to 1000/s;
• a processing stage,
• (1) the processing stage configured to implement a trained algorithm that receives at least a first data from the subject, the first data including a WBV collected at a first time and at a shear rate of from about 1/s to about 1000/s, the trained algorithm configured to determine a correlation between the first data and a first physiological state, the correlation being indicative of a current or future physiological state of the subject, or
• (2) the processing stage configured to implement a trained algorithm that receives (i) a first data from a subject, the first data including a WBV collected at a first time and at a shear rate of from about 1/s to about 1000/s and (ii) a second data from the subject, the second data including a WBV collected at a second time and at a shear rate of from about 1/s to about 1000/s, the trained algorithm configured to determine a correlation between the first data and the second data, wherein the correlation is indicative of a current or future physiological state of the subject.

A method of training an algorithm for detecting a current or future physiological state of a subject, the method comprising:

• inputting a plurality of datasets for each of a plurality of subjects into a model function, wherein the plurality of datasets include:
• (i) a first dataset including a first WBV of a subject collected at a first time and at a shear rate of from about 1/s to about 1000/s;
• (ii) a second dataset including a second WBV of a subject collected at a second time and at a shear rate of from about 1/s to about 1000/s;
• and
• (iii) a third dataset including at least one or more physiological states of the subject;
• and
• calculating weighted values for each data type of the first dataset and the second dataset via the model function;
• and
• generating a trained model by assigning the weighted values to the data type of the first dataset and the second dataset.