Apple inc. (20240103632). PROBABILISTIC GESTURE CONTROL WITH FEEDBACK FOR ELECTRONIC DEVICES simplified abstract

PROBABILISTIC GESTURE CONTROL WITH FEEDBACK FOR ELECTRONIC DEVICES

Organization Name

apple inc.

Inventor(s)

Matthias R. Hohmann of Mountain View CA (US)

Anna Sedlackova of San Francisco CA (US)

Bradley W. Griffin of Aptos CA (US)

Christopher M. Sandino of Menlo Park CA (US)

Darius A. Satongar of Staffordshire (GB)

Erdrin Azemi of San Mateo CA (US)

Kaan E. Dogrusoz of San Francisco CA (US)

Paul G. Puskarich of Palo Alto CA (US)

Gergo Palkovics of Seattle WA (US)

PROBABILISTIC GESTURE CONTROL WITH FEEDBACK FOR ELECTRONIC DEVICES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240103632 titled 'PROBABILISTIC GESTURE CONTROL WITH FEEDBACK FOR ELECTRONIC DEVICES

Simplified Explanation

The patent application discusses technology related to providing gesture-based control of electronic devices. This includes using a machine learning system to predict gestures and their probabilities, generating a likelihood of the user's intent to perform the gesture, updating the likelihood over time, and providing feedback indicators to guide the user.

• Determining gestures and their probabilities with a machine learning system
• Generating a likelihood of the user's intent to perform a gesture
• Providing visual, auditory, and/or haptic feedback indicators based on the likelihood
• Dynamically updating the likelihood over time

Potential Applications

This technology could be applied in various electronic devices such as smartphones, tablets, smart TVs, and gaming consoles to enhance user interaction and control.

Problems Solved

This technology solves the problem of improving user experience by providing a more intuitive and efficient way to control electronic devices through gestures.

Benefits

The benefits of this technology include enhanced user experience, increased convenience, and improved accessibility for individuals with physical limitations.

Potential Commercial Applications

Potential commercial applications of this technology include consumer electronics, smart home devices, virtual reality systems, and automotive interfaces.

Possible Prior Art

One possible prior art for this technology could be the use of gesture recognition systems in gaming consoles and virtual reality devices.

How does the machine learning system adapt to different users' gestures and preferences?

The article does not provide details on how the machine learning system can personalize its predictions based on individual users' gestures and preferences.

What are the potential privacy concerns related to using gesture-based control in electronic devices?

The article does not address any potential privacy concerns that may arise from collecting and analyzing user gestures for control purposes.

Original Abstract Submitted

aspects of the subject technology relate to providing gesture-based control of electronic devices. providing gesture-based control may include determining, with a machine learning system that includes multiple machine learning models, a prediction of one or more gestures and their corresponding probabilities of being performed. a likelihood of the user's intent to actually perform that gesture may then be generated, based on the prediction and a gesture detection factor. the likelihood may be dynamically updated over time, and a visual, auditory, and/or haptic indicator of the likelihood may be provided as user feedback. the visual, auditory, and/or haptic indicator may be helpful to guide the user to the correct gesture if the gesture is intended, or to stop performing an action similar to the gesture if the gesture is not intended.