PATENT CLAIM ANALYSIS

Application Number: 16045319
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-11
Patent Classification: ["705", "003000"]

Abstract:
An example method includes: classifying lung function risk based on patient attributes and a clinical protocol; generating alarms and incentives for compliance with the clinical protocol based on patient attributes, clinical protocol, and patient lung function risk; determining an orientation and position of a clinical device based on tagged feature(s) of the clinical device compared to identified patient feature(s); monitoring patient interaction with the clinical device; identifying a deviation from the clinical protocol based on the monitored patient interaction, a patient biometric indicator, and a desired setpoint state in the protocol; when a deviation is identified, providing feedback proportional to the deviation, the feedback including an adjustment with respect to the clinical protocol and/or the clinical device; and triggering at least one alarm and/or incentive based on deviation and feedback, wherein the alarm/incentives differs based on whether and to what extent deviation is identified and feedback.

Claim (Index 9):
The method of  claim 1 , wherein identifying a deviation further includes detecting, using the configured processor as a reasoning engine, an anomaly in the monitored pattern of patient interaction.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 95.0
- Lexical Diversity: 2.25676
- Patent Class: 705.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14737132', '13231639', '15692182', '15887708', '14141706']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1031880152229011
- 35 USC 102 Novelty (BERT): 0.5671360051459021
- Combined Prediction Score: 0.1495828142152012
- Mean Citation Score: 260.745568
- Max Citation Score: 434.1638
- Similarity Product: 393.0991150501966

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