PATENT CLAIM ANALYSIS

Application Number: 16050788
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-03
Patent Classification: ["340", "576000"]

Abstract:
Non-intrusive assessment of fatigue in drivers using eye tracking. A set of 34 features were extracted from eye tracking data collected in subjects participating in a simulated driving experiment. Vigilance was assessed by power spectral analysis of multichannel electroencephalogram (EEG) signals, recorded simultaneously, and binary labels of alert and drowsy (baseline) were generated for each epoch of the eye tracking data. A classifier and a non-linear support vector machine were employed for vigilance assessment. Evaluation results revealed a high accuracy of 88% for the RF classifier, which significantly outperformed the SVM with 81% accuracy (p<0.001).

Claim (Index 3):
Use of eye tracking data and a classifier to determine vigilance.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 95.0
- Lexical Diversity: 1.48684
- Patent Class: 340.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['12613306', '10417247', '15938799', '13419988', '10222432']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6913358706191391
- 35 USC 102 Novelty (BERT): 0.5190987697548765
- Combined Prediction Score: 0.674112160532713
- Mean Citation Score: 198.177028
- Max Citation Score: 205.90915
- Similarity Product: 111.43146217704415

Labels:
- Claim Label 101: 0
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test