Biological photometric device and biological photometry method using same
First Claim
1. A biological photometric device, comprising:
- one or more light sources, each irradiating light on a subject;
a plurality of light detectors, each detecting the light, which is irradiated on an irradiation point on the subject from one of the light sources and propagated in the subject, at a detection point on the subject; and
a calculator that analyzes signals obtained by the light detectors,wherein each of the light sources and each of the light detectors are configured to be disposed on the subject such that SD distance defined on the subject as a distance between the irradiation point and the detection point, is spaced as at least two types of spacing, andthe calculator extracts a plurality of separated components including a deep portion component reflecting signal from brain of the subject and a shallow portion component reflecting signal from scalp of the subject using a signal separation method from a plurality of measurement data respectively measured by combinations of the light source and the light detector having different values of the SD distances from one another, analyzes a first dependency of weight of the deep portion component within the measurement data with respect to the SD distance or a partial optical path length in gray matter and a second dependency of weight of the shallow portion component within measurement data with respect to the SD distance or the partial optical path length in gray matter by performing regression analysis and reconstructs the deep portion component and the shallow portion component of the measurement data according to the first dependency of weight of the deep portion component and the second dependency of weight of the shallow portion component.
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Abstract
The present invention is capable of separating/removing the influence of skin blood flow contained in near infrared spectroscopy (NIRS) signals and extracting a brain- or brain cortex-origin signal. Moreover, the present invention enables versatile separation of brain-origin and skin-origin signals in view of differences among individuals. A biological photometric device, wherein light transmitters and light receivers are located in such a manner that measurement can be conducted at a plurality of source-detector (SD) distances and light received by the individual light-receivers can pass through the gray matter to thereby separate a brain-origin signal and a skin-origin signal. Individual component analysis (ICA) is conducted on data obtained at the individual measurement points. Then, it is determined whether each individual component originates in the brain or in the skin with the use of the SD distance-dependency of the weighted value of each of the separated components.
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Citations
17 Claims
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1. A biological photometric device, comprising:
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one or more light sources, each irradiating light on a subject; a plurality of light detectors, each detecting the light, which is irradiated on an irradiation point on the subject from one of the light sources and propagated in the subject, at a detection point on the subject; and a calculator that analyzes signals obtained by the light detectors, wherein each of the light sources and each of the light detectors are configured to be disposed on the subject such that SD distance defined on the subject as a distance between the irradiation point and the detection point, is spaced as at least two types of spacing, and the calculator extracts a plurality of separated components including a deep portion component reflecting signal from brain of the subject and a shallow portion component reflecting signal from scalp of the subject using a signal separation method from a plurality of measurement data respectively measured by combinations of the light source and the light detector having different values of the SD distances from one another, analyzes a first dependency of weight of the deep portion component within the measurement data with respect to the SD distance or a partial optical path length in gray matter and a second dependency of weight of the shallow portion component within measurement data with respect to the SD distance or the partial optical path length in gray matter by performing regression analysis and reconstructs the deep portion component and the shallow portion component of the measurement data according to the first dependency of weight of the deep portion component and the second dependency of weight of the shallow portion component. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A biological photometric method that uses a biological photometric device including:
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one or more light sources that irradiates light on a subject; a plurality of light detectors that detects the light, which is irradiated on an irradiation point on the subject from the one or more light sources and propagated in the subject, at a detection point on the subject; and
a calculator that analyzes a signal obtained by the one or plurality of light detectors, the method comprising;disposing each of the light sources and each of the light detectors on the subject such that SD distance defined on the subject as a distance between the irradiation point and the detection point, is spaced as at least two types of spacing; extracting a plurality of separated components including a deep portion component reflecting signal from brain of the subject and a shallow portion component reflecting signal from scalp of the subject using a signal separation method from a plurality of measurement data respectively measured by combinations of the light source and the light detector having different values of the SD distance from on another; analyzing a first dependency of weight of the deep portion component within the measurement data with respect to the SD distance or a partial optical path length in gray matter and a second dependency of weight of the shallow portion component within measurement data with respect to the SD distance or the partial optical path length in gray matter by performing regression analysis; and reconstructing the deep portion component and the shallow portion component of the measurement data according to the first dependency of weight of the deep portion component and the second dependency of weight of the shallow portion component.
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Specification