Samsung Electronics Co., Ltd.

Korea University Research and Business Foundation

Amorepacific Corporation

Industry-academic Cooperation Foundation, Chosun University

Eui Seok Shin

Seung Jun Lee

Jin Young Park

Yun S Park

So Young Lee

Sang Kon Bae

Woo Chang Lee

June Young Lee

Jung Mok Bae

Dong Ho Kim

Hyo Sun Hwang

Young Hoon Kim

Byung Hoon Ko

Jae Wook Shim

Ho Jun Chang

Sung Hyun Nam

Seoung Bum Kim

Alexey Anikanov

Chang Mok Choi

Sang Jun Lee

Hyun Seok Moon

Sang Kyu Kim

Jong Wook Lee

Dae Bang Seo

Ka Ram Choi

Woochang Lee

Woo Sik Choi

Jeong Eun Hwang

Jong Keun Song

Wan Gi Kim

Si Young Cho

Tae Ryong Lee

Min Jeong Song

Hu Won Kang

Dae-Bang Seo

Jong Hee Sohn

Won Keun Oh

Phi Hung Nguyen

Thi Van Thu Le

Jin Kyu Chio

Hyun Woo Park

Ji Young Chun

Yoo Kim

A Raman sensor includes a light source assembly having a plurality of light sources configured to emit light to a plurality of skin points of skin, each of the plurality of skin points having a predetermined separation distance from a light collection region of the skin from which Raman scattered light is collected; a light collector configured to collect the Raman scattered light from the light collection region of the skin; and a detector configured to detect the collected Raman scattered light.

Compact Raman sensor and apparatus for estimating bio-component

An apparatus is provided. The apparatus includes a memory, a second type spectrum measurer, and a processor. The memory stores an individualized blood sugar estimation model. The second type spectrum measurer measures second type spectrum data for a skin of a user. The processor calculates blood sugar of the user based on the measured second type spectrum data and the individualized blood sugar model. The blood sugar model is generated based on blood sugar profile data of the user calculated based on a first type spectrum-blood sugar profile relationship model and training second type spectrum data for the skin of the user.

Apparatus and method for estimating blood sugar based on heterogeneous spectrums

A healthcare apparatus according to an embodiment includes: a plurality of light sources configured to emit light of different wavelengths onto an object; a light detector configured to measure an optical signal of each of the wavelengths by receiving light reflected or scattered from the object; and a processor configured to obtain a blood glucose level and a blood flow index by using the optical signal of each of the wavelengths, and to estimate at least one from among dietary information and dietary metabolism state information by monitoring a blood glucose level change and a blood flow index change after ingestion of a food.

Healthcare apparatus and operating method thereof

An apparatus for estimating bio-information is provided. The apparatus includes: an ultrasound image acquirer configured to acquire ultrasound images of an object; a pressurizer configured to apply pressure to the object to occlude a blood vessel; and a processor configured to estimate a change in a diameter of the blood vessel using the ultrasound images acquired by the ultrasound image acquirer before and after an occlusion of the blood vessel, and estimate bio-information based on the estimated change in the diameter of the blood vessel.

Apparatus and method for estimating bio-information, ultrasonic device, and mobile device

A disease prediction model construction apparatus is provided. The disease prediction model construction apparatus may include a spectral data acquisition unit that emits near-infrared rays toward a skin of a subject to acquire near-infrared spectral data and a prediction model construction unit that constructs a disease prediction model based on a time-blood glucose graph generated from the acquired near-infrared spectral data.

Disease prediction model construction apparatus and method, and disease prediction apparatus

A disease prediction apparatus may include: a spectrometer configured to obtain an optical spectrum of a subject; and a processor configured to predict autofluorescence of the subject based on the optical spectrum by applying the optical spectrum to an autofluorescence prediction model, and predict a risk of developing a cardiovascular disease based on the predicted autofluorescence.

Disease prediction model generation apparatus, and apparatus and method for predicting disease

An apparatus for estimating bio-information based on pulse wave signals of multiple wavelengths is disclosed. The bio-information estimating apparatus may include: a sensor part comprising a pulse wave sensor configured to measure a multi-wavelength pulse wave signal at a first point in time when a first pressure is applied from an object to the sensor part and at a second point in time when a second pressure is applied from the object to the sensor part; and a processor configured to estimate bio-information based on a difference between the multi-wavelength pulse wave signal measured at the first pressure and the multi-wavelength pulse wave signal measured at the second pressure.

Apparatus and method for estimating bio-information, and apparatus for supporting estimation of bio-information

An apparatus for measuring a body fluid includes: an optical sensor configured to emit light onto an object, receive the light returning from the object, and measure a first intensity of a first wavelength and a second intensity of a second wavelength from the received light; and a processor configured to estimate a body fluid volume of the object based on the first intensity and the second intensity.

Apparatus and method for measuring body fluid

An apparatus for estimating a skin condition includes a data acquirer configured to acquire an optical absorption spectrum of a skin; and a processor configured to determine content of a component in the skin from the optical absorption spectrum and determine a skin condition based on the determined content of the component in the skin.

Apparatus and method for estimating skin condition

Provided is an apparatus for estimating bio-information in a non-invasive manner. According to an exemplary embodiment, the bio-information estimation apparatus includes: a spectrum measurer configured to measure a spectrum of light reflected from an object; a temperature measurer configured to measure the temperature of the object while the spectrum measurer measures the spectrum of light reflected from the object; and a processor configured to calculate a spectrum correction factor, including one or more of a correction factor of a gain, a constant, and a slope, based on the measured temperature of the object, and to adjust the measured spectrum by using the calculated correction factor.

Bio-information estimation apparatus and bio-information estimation method

A spectrometer includes a chamber, a vacuum generator configured to suck in internal air of the chamber to pull skin of a subject into the chamber, a light source configured to emit light to the skin of the subject pulled into the chamber, a photodetector configured to receive light passing through the skin of the subject and acquire a spectrum of the light; and a skin contact adjuster configured to determine a contact state between the chamber and the skin by analyzing the spectrum of the light and thereby generate a determination result, and adjust the contact state between the chamber and the skin by applying a physical force to a periphery of the skin pulled into the chamber according to the determination result.

Spectrometer and operation method of spectrometer

An apparatus and a method for determining blood sugar based on heterogeneous spectrums are provided. The blood sugar model generation apparatus includes a data obtainer configured to obtain blood sugar profile data of a user based on a first type spectrum-blood sugar profile relationship model, a second type spectrum measurer configured to measure training second type spectrum data for the skin of the user, and a processor configured to generate an individualized blood sugar model based on the obtained blood sugar profile data and the measured training second type spectrum data.

Growing community of inventors

Yongin-si, South Korea

Eui Seok Shin