US 11,442,579 B2 · Method and electronic device for accidental touch prediction using ml classification

Abstract

A method for accidental touch prediction using machine learning (ML) classification is provided. The method includes determining, by an electronic device, a mutual data index of a sensor data using a first ML model. Further, the method includes recognizing whether the sensor data corresponds to an object touch or a non-object touch based on the mutual data index. Further, the method includes performing, by the electronic device, one of detecting that the electronic device is in a pocket mode and providing an object touch notification on a touch screen of the electronic device in response to determining that the sensor data corresponds to the object touch, and recognizing whether the sensor data corresponds to an accidental touch or a non-accidental touch using at least one second ML model based on touch data in response to determining that the sensor data corresponds to the non-object touch.

Claims22

Dependent claims

A method for accidental touch prediction using machine learning (ML) classification by an electronic device, the method comprising:

capturing, by the electronic device, sensor data corresponding to a touch on a touch screen of the electronic device;
determining, by the electronic device, a mutual data index of the sensor data using a first ML model;
recognizing, by the electronic device, whether the sensor data corresponds to an object touch or a non-object touch based on the mutual data index;
and
performing, by the electronic device, one of:
in response to determining that the sensor data corresponds to the object touch, detecting that the electronic device is in a pocket mode and providing an object touch notification, or
in response to determining that the sensor data corresponds to the non-object touch, recognizing whether the sensor data corresponds to an accidental touch or a non-accidental touch using at least one second ML model.

4 more elements

An electronic device for accidental touch prediction using machine learning (ML) classification, the electronic device comprising:

a memory;
a touch screen;
and
at least one processor coupled with the memory and the touch screen, the at least one processor being configured to:
capture sensor data corresponding to a touch on the touch screen,
determine a mutual data index of the sensor data using a first ML model,
recognize whether the sensor data corresponds to an object touch or a non-object touch based on the mutual data index, and
perform one of:
in response to determining that the sensor data corresponds to the object touch, detect that the electronic device is in a pocket mode and provide an object touch notification;
or
in response to determining that the sensor data corresponds to the non-object touch, recognize whether the sensor data corresponds to an accidental touch or a non-accidental touch using at least one second ML model.

8 more elements

Dependencies are inferred from the claim text.

Method and electronic device for accidental touch prediction using ml classification

Life of this patent

Method and electronic device for accidental touch prediction using ml classification

Life of this patent

Abstract

Claims22