Sensor Signal Alignment via Transformation Matrix
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Solution Overview
Problem
Conventional vestibular prostheses require prolonged and complex surgery for accurate alignment of motion sensors with the head-fixed coordinate system, or rely on power-intensive digital signal processing to correct sensor signals, which can lead to increased risk of complications and limited battery life.
Innovation Solution
A system that uses a signal measuring system and computer to calculate a transformation matrix from a sensitivity matrix, allowing for real-time correction of sensor signals using simple mathematical operations, enabling alignment of sensors with predefined axes to mimic correct head-fixed axes alignment without physical alignment during surgery and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical alignment of motion sensors with vestibular canals is performed during surgery, then measurement precision of head rotation is improved, but surgery duration is prolonged and risk of complications increases
Solution Approach 1:
The patent performs sensor alignment calculations using post-operative imaging (CT or MRI scans) after the surgical implantation is complete, rather than requiring precise physical alignment during surgery. The transformation matrix is computed based on the actual sensor positions relative to the head-fixed coordinate system, allowing accurate signal correction without prolonged surgical alignment procedures.
2Measurement precision
If digital signal processing techniques are used to correct sensor signals, then alignment accuracy is improved, but power consumption increases
Solution Approach 1:
The patent replaces complex digital signal processing operations with a pre-computed transformation matrix that can be applied through simpler mathematical operations. The transformation matrix, derived from imaging data and sensor positions, enables efficient coordinate system transformation with reduced computational requirements and lower power consumption compared to conventional digital filtering and alignment algorithms.
3Measurement precision
If digital signal processing is used for signal correction, then measurement precision is improved, but processing speed is limited by clock speed
Solution Approach 1:
The transformation matrix is pre-computed offline using imaging data and sensor position information, transferring the computationally intensive alignment calculations from the real-time processing path to a preliminary setup phase. During actual operation, only simple matrix multiplication operations are required, enabling high-speed real-time signal correction without being constrained by processor clock speed limitations.
Data Source
AI summary
Methods and systems, including computer readable mediums, are provided for transforming a measurement made relative to a first reference frame into a corresponding measurement relative to a second reference frame. Sensor signals that are produced by sensors in response to the sensors' motion relative to the first reference frame are transformed using a transformation matrix. The transformation generates corrected sensor signals that are relative to the axes of the second reference frame.