Joint Axis Calibration for Wearable Sensors
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Solution Overview
Problem
Existing wearable and body-mounted sensors face challenges in accurately measuring joint movement due to misalignment between sensed rotation axes and actual joint axes, leading to inaccuracies in measurement.
Innovation Solution
A method and device for calibrating estimated joint axis directions using orientation data from sensors located on either side of a joint, calculating sensor frame estimated gravity vectors, and determining joint axis directions that minimize a loss function based on projections of these vectors, thereby correcting for misalignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are attached to the body about a joint, then movement of the joint can be tracked, but the sensed rotation axes of the sensor device cannot align with the movement axis of the joint due to body shape constraints
Solution Approach 1:
The system performs preliminary calibration by collecting orientation data from multiple known poses before actual measurement. This preliminary action establishes the transformation relationship between sensor axes and joint axes, enabling accurate measurement without requiring precise physical alignment during operation.
Solution Approach 2:
The system changes the parameter representation from direct spatial alignment to mathematical transformation. By using orientation data and transformation matrices, the system compensates for misalignment through parameter adjustment rather than physical repositioning, resolving the contradiction between measurement accuracy and positioning feasibility.
2Measurement precision
If sensors are carefully positioned to align with joint axes, then measurement accuracy improves, but this is impossible due to body shape constraints
Solution Approach 1:
The system introduces an intermediary mathematical model (transformation matrix) that mediates between the sensor coordinate system and the joint coordinate system. This intermediary allows accurate joint axis representation without requiring direct physical alignment, making the system reliable regardless of body shape variations.
Solution Approach 2:
The calibration process using multiple known poses is performed as a preliminary action to establish the transformation relationship. This one-time preliminary setup ensures reliable and accurate measurements for all subsequent operations without requiring repeated adjustments.
3Ease of operation
If the sensed rotation axes are misaligned with the joint movement axis, then sensor attachment is easier, but inaccuracies in joint movement measurement occur
Solution Approach 1:
The system replaces the mechanical alignment requirement with a computational solution. Instead of relying on precise physical positioning, the system uses orientation data collection and mathematical transformation to achieve accurate measurement, substituting mechanical precision with computational correction.
Solution Approach 2:
The system transforms the problem from spatial alignment (mechanical parameter) to coordinate transformation (mathematical parameter). By changing how alignment is achieved from physical to mathematical, the system maintains measurement accuracy while simplifying the attachment process.
Data Source
AI summary
A method for calibrating respective estimated joint axis directions for each of a pair of body mounted sensors, one of the pair of sensors being located to each side of the joint comprising a joint axis, the sensors each calculating a pitch angle about respective first sensor axes and a roll angle about respective second sensor axes, the first and second sensor axes together with a third sensor axis orthogonal to the first and second sensor axes forming a sensor frame, the method comprising: receiving orientation data for each of the two sensors, the orientation data being associated with at least two different poses of the joint for each of the two sensors and the orientation data comprising the pitch angle and the roll angle of the sensor for each pose; calculating a sensor frame estimated gravity vector for each pose associated with each sensor based on the pitch and roll angles for each pose associated with each sensor and a gravity vector running along a vertical direction; and determining the estimated joint axis directions for the joint axis, relative to the first and second sensor axes, for each sensor that minimise a loss function concerning projections of each sensor frame estimated gravity vector for each pose associated with each sensor on to the estimated joint axis direction for the respective sensor.