PATENT CLAIM ANALYSIS

Application Number: 15923225
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["382", "128000"]

Abstract:
A system and method for contactless blood pressure determination. The method includes: receiving a captured image sequence; determining, using a trained hemoglobin concentration (HC) changes machine learning model, bit values from a set of bitplanes in the captured image sequence that represent the HC changes of the subject; determining a blood flow data signal; extracting one or more domain knowledge signals associated with the determination of blood pressure; building a trained blood pressure machine learning model with a blood pressure training set, the blood pressure training set including the blood flow data signal of the one or more predetermined ROIs and the one or more domain knowledge signals; determining, using the blood pressure machine learning model trained with a blood pressure training set, an estimation of blood pressure; and outputting the determination of blood pressure.

Claim (Index 12):
The method of  claim 1 , wherein extracting the one or more domain knowledge signals comprises determining one or more biosignals, the biosignals comprising at least one of heart rate measured from the human subject, Mayer waves measured from the human subject, and breathing rates measured from the human subject.

Metadata:
- Claim Count in Document: 13.0
- Percentile: 90.0
- Lexical Diversity: 2.39683
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15923242', '15761891', '16076522', '16076492', '14969300']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.349129996403176
- 35 USC 102 Novelty (BERT): 0.5376694924987006
- Combined Prediction Score: 0.3679839460127285
- Mean Citation Score: 277.991468
- Max Citation Score: 394.2462
- Similarity Product: 257.4606266396284

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test