PATENT CLAIM ANALYSIS

Application Number: 15934015
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-08
Patent Classification: ["600", "508000"]

Abstract:
Drowsiness onset detection implementations are presented that predict when a person transitions from a state of wakefulness to a state of drowsiness based on heart rate information. Appropriate action is then taken to stimulate the person to a state of wakefulness or notify other people of their state (with respect to drowsiness/alertness). This generally involves capturing a person's heart rate information over time using one or more heart rate (HR) sensors and then computing a heart-rate variability (HRV) signal from the captured heart rate information. The HRV signal is analyzed to extract features that are indicative of an individual's transition from a wakeful state to a drowsy state. The extracted features are input into an artificial neural net (ANN) that has been trained using the same features to identify when an individual makes the aforementioned transition to drowsiness. Whenever an onset of drowsiness is detected, a warning is initiated.

Claim (Index 11):
The computing system of  claim 3 , further comprising a segmenting instruction that is executed before the execution of the instruction for extracting the plurality of different HRV-related features from the HR information, said segmenting instruction segmenting the HR information received from the one or more HR sensors into a sequence of prescribed-length segments whenever the received HR information is in the form of a HRV signal, and said segmenting instruction computing a HRV signal from the received HR information whenever the received HR information is not in the form of a HRV signal before segmenting the HRV signal into the sequence of prescribed-length segments, and wherein the instructions for extracting the plurality of different HRV-related features from the HR information, combining the extracted different HRV-related features, inputting the drowsiness detection input into the ANN classifier, determining based at least on the output of the ANN classifier if the individual is exhibiting an onset of drowsiness, and based at least on determining that the individual is exhibiting an onset of drowsiness, initiating the drowsiness onset warning, are executed on each of the HRV signal segments as they are created.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 1.86517
- Patent Class: 600.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14974584', '15627288', '12613306', '13490044', '15792085']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.449213569540888
- 35 USC 102 Novelty (BERT): 0.5990217144454653
- Combined Prediction Score: 0.4641943840313458
- Mean Citation Score: 279.333532
- Max Citation Score: 591.75287
- Similarity Product: 468.1904512883997

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