Foldable Laptop Mode Detection with Multi-Sensor Hinge Sensing
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Solution Overview
Problem
Existing context recognition methods for electronic devices, such as foldable laptops, using Hall sensors and magnets are limited to context recognition only, cause complex circuit board designs, risk magnetization, and suffer from false detections and low accuracy.
Innovation Solution
Implementing multi-sensor devices, including accelerometers and gyroscopes, in the lid portions of the device to detect lid closed and tablet modes, allowing for versatile applications beyond context recognition, avoiding magnetization risks and enabling precise threshold settings for accurate detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Hall sensors and magnets are used for context recognition, then lid closed mode detection is achieved, but device complexity increases due to complex printed circuit board designs
Solution Approach 1:
The patent extracts the magnet from the system and replaces it with a Hall sensor positioned in the display assembly that detects the magnetic field generated by the keyboard assembly itself. This eliminates the need for separate magnet components and complex PCB designs while maintaining detection functionality.
Solution Approach 2:
The Hall sensor is positioned to serve multiple functions: detecting lid closed mode, determining tablet mode, and identifying upright mode. This multi-functional approach reduces the need for additional sensors and simplifies the overall device design.
2Reliability
If Hall sensors and magnets are positioned near edges of panels, then lid closed mode detection is achieved, but device complexity increases
Solution Approach 1:
The patent transitions from edge-based positioning to a dimensional approach where the Hall sensor is positioned within the display assembly volume and detects magnetic fields along the hinge axis. This allows detection without constraining components to panel edges, simplifying the overall arrangement.
3Reliability
If magnets are used for magnetic field generation, then context recognition is achieved, but harmful factors increase due to device magnetization
Solution Approach 1:
The patent converts the potential harm of magnetization by using the keyboard assembly itself as the magnetic source. The keyboard assembly is designed with magnetic properties that generate the necessary field for detection without causing harmful magnetization of the entire device, as the field is contained and controlled.
4Reliability
If Hall sensors are used for magnetic field detection, then context recognition is achieved, but measurement precision is insufficient for precise angle detection
Solution Approach 1:
The patent changes the detection parameters by using the Hall sensor to measure magnetic field strength along the hinge axis and converting this measurement into angular information. By establishing precise threshold values corresponding to specific angles (0 degrees for lid closed, 180 degrees for tablet mode), the system achieves precise angle detection through parameter transformation.
5Reliability
If Hall sensors are dedicated to magnetic field detection, then context recognition is achieved, but adaptability decreases for other applications
Solution Approach 1:
The Hall sensor is designed to perform multiple functions beyond basic context recognition. It can detect various magnetic field strengths corresponding to different device modes (lid closed, tablet, upright), and the same sensor can be used for orientation detection and other magnetic field-based applications, increasing adaptability.
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
The multi-sensor approach allows for accurate and versatile context recognition without complex circuit designs, reduces false detections, and maintains power efficiency, enabling seamless power management transitions.
Implementation Method 1
Each of the multi-sensor devices includes one or more types of motion sensors including, but not limited to, an accelerometer and a gyroscope that generate motion measurements
Implementation Method 2
Each of the multi-sensor devices includes one or more types of motion sensors including, but not limited to, an accelerometer and a gyroscope that generate motion measurements
Data Source
AI summary
The present disclosure is directed to devices and methods for performing context recognition. The context recognition detects whether the device is in a lid closed mode or a tablet mode. The context recognition is configured to handle exception cases including a first exception case in which context recognition is started while in an upright mode, and a second exception case in which context recognition is started while the device is in a lid closed mode or a tablet mode.