Capacitive Gesture Detection with Bayesian Classification

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Solution Overview

Problem

Current capacitive sensing technologies face challenges in accurately detecting environmental conditions and user interactions around mobile devices, such as determining material types and gestures, due to limited information retrieval and interference from conductive objects.

Innovation Solution

A capacitive gesture system utilizing a suite of algorithms with a chip for capacitive sensing, enabling gesture recognition from various angles and environments, employing a Naïve Bayesian classifier for accurate classification, and a three-electrode sensing array with differential feed line cancellation for precise capacitance measurement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If capacitive sensing is used to detect environmental conditions and gestures, then the ability to detect user interactions is improved, but interference from conductive objects and limited information retrieval occur

Engineering Contradiction:

Improvegesture detection accuracyVSAvoidinterference from conductive objects

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system divides the sensing area into multiple zones with different electrode configurations. Each zone is optimized for specific detection purposes, allowing the system to segment the detection space to reduce interference from conductive objects while maintaining gesture detection accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediate processing layers including machine learning classifiers and signal processing algorithms that act as mediators between the raw capacitive signals and the final gesture recognition. These intermediaries filter out interference from conductive objects and extract meaningful gesture information.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If environmental detection capabilities are enhanced, then the ability to adjust mobile device settings is improved, but power consumption increases

Engineering Contradiction:

Improveenvironmental adaptation capabilityVSAvoidpower consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system implements periodic environmental scanning rather than continuous monitoring. The capacitive sensors and machine learning algorithms operate in periodic cycles, adjusting device settings based on detected environmental changes while consuming power only during active detection and adjustment periods.

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The system uses the mobile device's existing capacitive touch screen infrastructure and processor for environmental detection, rather than adding dedicated power-hungry sensors. The device leverages its own components to perform dual functions of user interface and environmental sensing.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If gesture recognition from various angles is implemented, then the versatility of user interaction is improved, but processing time increases

Engineering Contradiction:

Improvegesture recognition capabilityVSAvoidprocessing time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system pre-trains machine learning classifiers with gesture data from multiple angles and orientations before actual use. During operation, the pre-trained models can quickly classify gestures without requiring extensive real-time processing, reducing latency while maintaining multi-angle recognition capability.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces traditional rule-based gesture recognition algorithms with machine learning-based classification systems. The machine learning approach processes multi-angle gesture data more efficiently by learning patterns directly from data rather than requiring complex geometric calculations and rule evaluations.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables reliable detection of environmental characteristics and user inputs, allowing for real-time adjustments to mobile device settings, such as radio frequency communication and user interface outputs, while reducing power consumption and processing time.

Implementation Method 1

Capacitive sensing is a technology based on capacitive coupling which takes human body capacitance as input

Methodology Applied

Scientific EffectCapacitive coupling: Capacitance

Implementation Method 2

a three-electrode sensing array with differential feed line cancellation for precise capacitance measurement

Methodology Applied

Scientific EffectDifferential measurement:

Data Source

PatentUS11785133B2Capacitive gesture detection system and methods thereof

Publication Date: 2023.10.10 ANALOG DEVICES INC

AI summary

Apparatus and methods are disclosed related to managing characteristics of a mobile device based upon capacitive detection of materials proximate the mobile device, a capacitive gesture system that can allow the same gestures be used in arbitrary locations within range of a mobile device. One such method includes receiving a first capacitive sensor measurement with a first capacitive sensor of the mobile device. The method further includes determining a value indicative of a material adjacent to the mobile device based on a correspondence between the first capacitive sensor measurement and stored values corresponding to different materials. The method further includes sending instructions to adjust a characteristic of the mobile device based on the determined value indicative of the material adjacent to the mobile device. In certain examples, gesture sensing can be performed using capacitive measurements from the capacitive sensors.