18521539. Robust Radar-Based Gesture-Recognition by User Equipment simplified abstract (Google LLC)

Robust Radar-Based Gesture-Recognition by User Equipment

Organization Name

Google LLC

Inventor(s)

Jung Ook Hong of Sunnyvale CA (US)

Patrick M. Amihood of Palo Alto CA (US)

John David Jacobs of San Diego CA (US)

Abel Seleshi Mengistu of Mountain View CA (US)

Leonardo Giusti of San Francisco CA (US)

Vignesh Sachidanandam of Redwood City CA (US)

Devon James O'reilley Stern of Oakland CA (US)

Ivan Poupyrev of Los Altos CA (US)

Brandon Barbello of Mountain View CA (US)

Tyler Reed Kugler of Palo Alto CA (US)

Johan Prag of Mountain View CA (US)

Artur Tsurkan of San Francisco CA (US)

Alok Chandel of Mountain View CA (US)

Lucas Dupin Moreira Costa of Mountain View CA (US)

Selim Flavio Cinek of Los Angeles CA (US)

Robust Radar-Based Gesture-Recognition by User Equipment - A simplified explanation of the abstract

This abstract first appeared for US patent application 18521539 titled 'Robust Radar-Based Gesture-Recognition by User Equipment

Simplified Explanation

The patent application describes systems and techniques for robust radar-based gesture recognition. Here is a simplified explanation of the abstract:

• Radar system detects radar-based gestures for application subscribers
• State machine transitions based on inertial sensor data
• No-gating state allows output of radar-based gestures
• Soft-gating state prevents output of radar-based gestures
• Hard-gating state prevents detection of radar-based gestures
• Techniques conserve power, improve accuracy, and reduce latency

1. 1. 1. Potential Applications

The technology can be applied in various fields such as automotive, healthcare, gaming, and smart home devices for gesture control and interaction.

1. 1. 1. Problems Solved

This technology solves the problem of inefficient power usage, inaccurate gesture recognition, and high latency in radar-based gesture recognition systems.

1. 1. 1. Benefits

The benefits of this technology include power conservation, improved accuracy in gesture recognition, reduced latency, and automatic reconfiguration based on user demand.

1. 1. 1. Potential Commercial Applications

Commercial applications of this technology can be seen in consumer electronics, automotive systems, healthcare devices, and gaming consoles for enhanced user interaction and control.

1. 1. 1. Possible Prior Art

One possible prior art could be traditional radar-based gesture recognition systems that lack the ability to dynamically adjust based on user demand and sensor data.

1. 1. 1. 1. Unanswered Questions

1. 1. 1. 1. How does this technology compare to other gesture recognition systems in terms of accuracy and latency?

This article does not provide a direct comparison with other gesture recognition systems in terms of accuracy and latency. Further research or testing may be needed to determine the performance differences.

1. 1. 1. 1. What are the specific inertial sensor data used in the state machine for transitioning between states?

The article does not detail the specific inertial sensor data used in the state machine for transitioning between states. Understanding the exact parameters and inputs could provide insights into the system's functionality and performance.

Original Abstract Submitted

Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.