Head-Mounted Device Calibration Using Repetitive Head Movements
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Solution Overview
Problem
Existing head-mounted devices, such as smart glasses, require frequent recalibration due to variations in facial anatomy and shifting of the device on the wearer's face, leading to sensor misalignment and inaccurate position and motion measurements.
Innovation Solution
A method for calibrating head-mounted devices that involves detecting a known repetitive movement pattern, acquiring three-dimensional motion data, selecting relevant data, and numerically treating it to establish a reference base for sensor recalibration, which can be triggered by user request, periodic events, or detected shifts, using sensors like IMUs, gyroscopes, and cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the device is worn continuously during daytime activities, then the device remains convenient for use, but the sensor position shifts relative to the face causing measurement bias
Solution Approach 1:
The system continuously monitors sensor data to detect changes in head position and movement patterns. When a shift is detected, the system automatically triggers a recalibration procedure using known movement patterns (such as walking cycles) to realign the sensor reference frame with the wearer's actual head position, thereby maintaining measurement precision without interrupting continuous use.
Solution Approach 2:
The calibration system performs automatic self-calibration without requiring professional intervention. The wearer simply needs to engage in normal activities (like walking) which generate the known movement patterns needed for recalibration. The system autonomously detects movement patterns, processes the data, and updates the sensor reference frame, eliminating the need for manual calibration procedures.
2Measurement precision
If manual recalibration is performed by a professional in a shop or laboratory, then initial calibration accuracy is improved, but the process becomes inconvenient and requires specialized equipment
Solution Approach 1:
The system enables users to perform calibration themselves without professional intervention. The wearer wears the device during normal activities, and the system automatically detects known movement patterns (such as walking cycles) to perform recalibration. This eliminates the need to visit a shop or laboratory while maintaining calibration accuracy.
Solution Approach 2:
The patent replaces complex mechanical calibration equipment with software-based detection algorithms. Instead of using physical measurement tools and manual procedures, the system uses sensors to detect movement patterns and processes this data through numerical treatment to establish reference frames, substituting mechanical calibration procedures with electronic and computational methods.
3Measurement precision
If the sensor reference frame is updated frequently to account for position shifts, then measurement accuracy is maintained, but the calibration process becomes more complex and time-consuming
Solution Approach 1:
The system performs recalibration periodically based on detected changes in movement patterns rather than continuously. By monitoring for specific indicators of position shift (such as changes in head movement characteristics during walking), the system updates the reference frame at appropriate intervals, maintaining accuracy while avoiding unnecessary frequent recalibrations that would increase complexity.
Solution Approach 2:
The system changes the calibration approach based on detected parameters. When movement pattern analysis indicates a position shift, the system switches to a recalibration mode that uses updated movement data to establish a new reference frame. This parameter-based decision-making allows the system to maintain accuracy only when needed, reducing overall complexity.
4Extent of automation
If automatic recalibration is implemented based on detected shifts, then measurement accuracy is maintained without user intervention, but the system complexity increases
Solution Approach 1:
The system uses feedback from sensor data to automatically detect position shifts and trigger recalibration. By continuously monitoring movement patterns and comparing them against established criteria, the system autonomously determines when recalibration is needed and executes the recalibration process without user intervention, achieving high automation while managing complexity through intelligent decision-making.
Solution Approach 2:
The system performs self-calibration automatically without requiring user involvement. The wearer simply wears the device during normal activities, and the system autonomously detects movement patterns, processes the data, and updates the sensor reference frame. This self-service capability achieves high automation while keeping the user experience simple.
Data Source
AI summary
The invention relates to method for calibrating a head-mounted device (1), the head-mounted device (1) comprising a frame (2) and at least one sensor (4) mounted on the frame (2), for measuring position and/or motion, the method being implemented while the head-mounted device (1) is worn on a wearer's head, the method comprising steps of: —detection (DET) of a known repetitive movement pattern of the wearer's head by the sensor (4), —acquisition (ACQ) of three-dimensional motion data by the sensor (4), —selection (SEL) of data relative to the movement pattern from the motion data, —numerical treatment (NUM) of the selected data to obtain a reference base relative to the wearer's head, and —calibrating (CAL) the sensor (4) based on the obtained reference base.