Time-Resolved Image Sensor Signal Separation
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Solution Overview
Problem
Existing methods for acquiring internal information from objects using light face challenges in achieving high accuracy, high density, and high speed due to noise from surface reflections, particularly in bioinstrumentation, where separating brain signals from skin signals is difficult and requires complex arithmetic processing across multiple frames.
Innovation Solution
An image pickup apparatus that uses a time-resolved image sensor with multiple floating diffusion layers and an electronic shutter to accumulate signal charges at different timings for pulsed light beams at different positions, allowing for the separation of shallow and deep tissue components within a single frame, thereby reducing noise and enhancing signal accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple frames are used to separate brain signals from skin signals, then measurement precision is improved, but productivity deteriorates due to complex arithmetic processing across multiple frames
Solution Approach 1:
The image sensor is divided into multiple floating diffusion layers (first, second, third, and fourth accumulators) that operate independently to capture signals at different timing. This segmentation allows simultaneous acquisition of multiple signal components within a single frame, eliminating the need for complex cross-frame processing while maintaining signal separation capability.
Solution Approach 2:
The patent introduces a temporal dimension by using multiple floating diffusion layers that accumulate signals at different timing intervals. This adds a time-based differentiation layer to the spatial detection, enabling depth resolution and signal separation without requiring multiple frames, thus improving processing speed while maintaining measurement precision.
2Measurement precision
If multiple floating diffusion layers are used to accumulate signals at different timing, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Each floating diffusion layer serves multiple functions: it acts as both a signal accumulator and a timing gate. The layers collectively provide depth resolution, signal separation, and noise filtering capabilities within a single integrated sensor structure, reducing the need for additional external components or complex post-processing systems.
Solution Approach 2:
The patent combines multiple signal accumulation functions into a single image sensor device by integrating multiple floating diffusion layers. This merging of functions into one unified structure achieves high measurement precision without proportionally increasing overall device complexity, as the layers share common support infrastructure and control mechanisms.
3Productivity
If surface reflected light is included in detection, then productivity is improved by simpler detection, but measurement precision deteriorates due to noise from surface reflections
Solution Approach 1:
The patent extracts and separates surface-reflected light signals from internally scattered light signals by utilizing their different temporal characteristics. The first and second accumulators capture early-arriving surface-reflected light, while the third and fourth accumulators capture later-arriving internally scattered light, effectively extracting the desired internal signals while rejecting surface noise.
Solution Approach 2:
The patent employs periodic pulsed light illumination to create distinct temporal windows for capturing surface-reflected and internally scattered light. By synchronizing the detection timing with the light pulse periodicity, the system achieves rapid signal separation without sacrificing detection speed, maintaining high productivity while improving measurement precision.
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 high-accuracy, high-density, and high-speed imaging of biological components at both shallow and deep tissue levels, effectively removing artifacts from scalp blood flow and improving cerebral blood flow imaging by isolating internal scattered light components.
Implementation Method 1
an image sensor including pixels, each pixel including a photodetector which, in operation, converts received light into a signal charge
Data Source
AI summary
An image pickup apparatus includes: a first light source which, in operation, emits first pulsed light to project a first image of a first pattern at a first position in a predetermined region of a subject, and emits second pulsed light to project a second image of a second pattern at a second position, different from the first position, in the predetermined region of the subject; an image sensor including multiple pixels each including a photodetector that, in operation, converts received light into a signal charge, and a first accumulator and a second accumulator each of which, in operation, accumulates the signal charge; and a control circuit which, in operation, controls the first light source and the image sensor.