PATENT CLAIM ANALYSIS

Application Number: 15984245
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["710", "073000"]

Abstract:
Logic of a handheld controller can implement sensor fusion algorithms based on force data provided by a force sensing resistor (FSR) in combination with touch data or proximity data provided by a touch sensor or an array of proximity sensors, respectively. An example sensor fusion algorithm can be used to re-calibrate the FSR when an object contacts an associated control, as detected by the touch sensor. Another example sensor fusion algorithm can be used to ignore spurious inputs detected by the FSR when an object is in contact with an adjacent control. Another example sensor fusion algorithm can be used to detect a hand size of a hand grasping a handle of the controller, as detected by the array of proximity sensors, and to adjust the threshold force to register a FSR input event at the FSR according to the hand size.

Claim (Index 14):
The handheld controller of  claim 12 , wherein:\n the plurality of predefined sizes include a first size and a second size that is larger than the first size; a default threshold value is associated with the first size or the second size; and adjusting the threshold value comprises at least one of:\n increasing the default threshold value to the adjusted threshold value associated with the second size, the adjusted threshold value being greater than the default threshold value; or \n decreasing the default threshold value to the adjusted threshold value associated with the first size, the adjusted threshold value being less than the default threshold value.

Metadata:
- Claim Count in Document: 7.0
- Percentile: 93.0
- Lexical Diversity: 2.23529
- Patent Class: 710.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15834372', '15834425', '14038307', '11986873', '15150769']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6776245236381215
- 35 USC 102 Novelty (BERT): 0.4803106470011246
- Combined Prediction Score: 0.6578931359744218
- Mean Citation Score: 144.635294
- Max Citation Score: 159.26344
- Similarity Product: 106.12341920672894

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