Hovering Keyboard Hand Detection for User Identification
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Solution Overview
Problem
Conventional Information Handling Systems (IHSs) lack effective user identification methods, particularly in scenarios where physical contact with a keyboard is not feasible, such as in hovering keystroke detection, which complicates user authentication and preference management.
Innovation Solution
The implementation of a hovering keyboard with proximity sensors that detect hand presence and fit proximity data to a geometric model to identify users, allowing for user authentication and dynamic keyboard layout adjustments based on user identification, including lighting keys corresponding to hand position and distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If proximity sensors are used to detect hovering keystrokes without physical contact, then ease of operation is improved, but user identification capability deteriorates
Solution Approach 1:
The hand is segmented into multiple detection zones corresponding to different keys, with each zone monitored by proximity sensors. This segmentation allows the system to identify which specific keys are being hovered over and to distinguish between different users based on hand position patterns, thereby maintaining user identification capability while enabling contactless operation.
Solution Approach 2:
A geometric model of the hand is introduced as an intermediary between the raw proximity sensor data and user identification. The model fits detected hand positions to expected hand geometries, enabling accurate user identification even without physical contact by comparing the fitted model parameters against stored user profiles.
2Measurement precision
If proximity sensors detect hand position to enable hovering keystrokes, then device complexity increases, but user identification capability improves
Solution Approach 1:
The proximity sensors serve multiple functions: detecting hovering keystrokes, determining hand position, and enabling user identification. This multi-functionality reduces the need for separate components for each function, thereby managing device complexity while achieving precise hand position detection and user identification capabilities.
Solution Approach 2:
The system uses the hand's own geometric characteristics and natural positioning over the keyboard to perform identification, rather than requiring separate biometric sensors. The hand itself provides the identification data through its position and shape when hovering over keys, eliminating the need for additional complex authentication hardware.
3Measurement precision
If geometric modeling is applied to fit proximity data to hand models, then user identification accuracy improves, but processing time increases
Solution Approach 1:
Geometric models of hands are pre-computed and stored for multiple users before actual authentication. During identification, the system only needs to fit the sensor data to these pre-prepared models rather than creating models from scratch, significantly reducing processing time while maintaining high identification accuracy.
Solution Approach 2:
The system fits only the essential geometric parameters of the hand model (such as finger positions and lengths) rather than attempting to model every detail of the hand. This partial modeling approach achieves sufficient accuracy for user identification while minimizing the computational complexity and processing time required.
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 secure user identification and dynamic keyboard configuration, distinguishing between users such as children and adults, and enforcing parental controls or security measures based on detected hand characteristics without requiring physical contact.
Implementation Method 1
proximity sensors disposed on a hovering keyboard coupled to the IHS
Data Source
AI summary
Systems and methods for identifying users via hand detection using a hovering keyboard are described. In some embodiments, an Information Handling System (IHS) may include a processor, and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to: detect a hand using proximity sensors disposed on a hovering keyboard coupled to the IHS; and identify a user based on the detection.