PATENT CLAIM ANALYSIS

Application Number: 15992108
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["600", "301000"]

Abstract:
A system and methods for a machine learning exercise belt comprising a belt, gyroscope, accelerometer, pressure sensor, electromyography (EMG) sensor and wireless adaptor, which may use machine learning algorithms and network communication to determine a weight lifter's form and intensity during exercise and provide feedback if they are performing an exercise with poor form, to help avoid injury and other consequences from poor form during weight lifting exercises.

Claim (Index 3):
The system of  claim 1 , wherein a pressure sensor is used to measure breathing patterns of a user during exercise.

Metadata:
- Claim Count in Document: 38.0
- Percentile: 93.0
- Lexical Diversity: 1.44444
- Patent Class: 600.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14447562', '15268619', '14515540', '15853746', '12975306']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4626013917525387
- 35 USC 102 Novelty (BERT): 0.4981104752492201
- Combined Prediction Score: 0.4661523001022069
- Mean Citation Score: 148.64671400000003
- Max Citation Score: 151.27776
- Similarity Product: 79.43764584869385

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