PATENT CLAIM ANALYSIS

Application Number: 15960461
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["702", "181000"]

Abstract:
A variety of techniques are used automate the collection and classification of workout data gathered by a wearable physiological monitor. The classification process is staged in order to correctly and efficiently characterize a workout type. Initially, a generalized workout event is detected using motion and heart rate data. Then a location of the monitor on a user is determined. An artificial intelligence engine can then be conditionally applied (if a workout is occurring and a suitable device location is detected) to identify the type of workout. In addition to improved speed and accuracy, a workout detection process implemented in this manner can be realized with a sufficiently small computational footprint for deployment on a wearable physiological monitor.

Claim (Index 13):
The method of  claim 3  wherein determining the position of the wearable physiological monitor includes training a machine learning algorithm to identify the position and updating the machine learning algorithm on a central server based on new data from a plurality of users.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 91.0
- Lexical Diversity: 1.62821
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15207924', '14750389', '15265761', '14995874', '15035090']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2235486914167701
- 35 USC 102 Novelty (BERT): 0.5011025577209136
- Combined Prediction Score: 0.2513040780471845
- Mean Citation Score: 200.28484
- Max Citation Score: 211.56848
- Similarity Product: 131.02659337063793

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

Dataset: test