PATENT CLAIM ANALYSIS

Application Number: 16104312
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2018-12
Patent Classification: ["482", "008000"]

Abstract:
An intelligent fitness set and anti-cheating method thereof is disclosed. The intelligent fitness set includes a support, a base, a plurality of handheld fitness equipments and two handles, wherein a processor, a movement posture sensor and a touch sensor are provided in each handle, and the movement posture sensor and the touch sensor are connected respectively with the processor. One end of each handle is closed, while a bayonet is provided in the other end of the handle and the switchable hot-pluggable bayonet is configured to connect respectively to the plurality of handheld fitness equipments. In the present disclosure, one set of action training of a plurality of handheld fitness equipments is performed through the same set of handles, so that a user can complete movement of one time only by strictly complying with active standards during movement.

Claim (Index 6):
An anti-cheating method based on the intelligent fitness set of  claim 1 , wherein comprising:\n determining whether the user is cheating or not by the built-in processor in the handle based on data from the built-in sensor in the handle and data fed back from the sensor built in each of the plurality of handheld fitness equipments, when the two handles are connected to any one of the plurality of handheld fitness equipments.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 96.0
- Lexical Diversity: 2.11268
- Patent Class: 482.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['16104345', '14008000', '13687035', '14067657', '14684626']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.671310858349758
- 35 USC 102 Novelty (BERT): 0.5578651167845606
- Combined Prediction Score: 0.6599662841932383
- Mean Citation Score: 253.47194
- Max Citation Score: 514.6647
- Similarity Product: 352.9550654903054

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

Dataset: test