Samsung Electronics Co., Ltd.

Postech Academy-industry Foundation

University System of Maryland

Industry-academic Cooperation Foundation, Dankook University

Korea Advanced Institute of Science and Technology

Ui Kun Kwon

Sang Joon Kim

Chang Soon Park

Seung Keun Yoon

Young Soo Kim

Dae Geun Jang

Seungkeun Yoon

Changmok Choi

Jaechun Lee

Eung Sun Kim

Tae Rim Park

Youn Ho Kim

Chang Mok Choi

Gi Hong Im

Seung Woo Noh

Patil Sandhya

Yunseo Ku

Young-Doo Kim

Jongwook Lee

Sang-joon Kim

Chi Sung Bae

Anirudh Bhatt

Ha-Neul Lee

Chunhui (Allan) Zhu

Joon Seong Kang

Jong Wook Lee

Sang Kon Bae

Shi Hong Park

Dong Sik Kim

Peyman Yousefian

Young Jun Hong

Jin Woo Choi

Chang Yong Shin

Jae Min Kang

Tae Soo Kwon

Jong Bu Lim

Jin-Oh Hahn

Hye Rim Lim

Dae-Young Seol

Yeong Seok Ko

Sungtae Shin

Vahid Tarokh

Hyo Sun Hwang

Chisung Bae

Shubhranshu Singh

Seok Ju Yun

Seong Joong Kim

Won-Jae Shin

Tae Seok Kim

Osama Aboul Magd

Jin Woo Shin

Chan Ho Choi

Gi Hong Lim

Kwi Hyuk Jin

Jin-Oh Hann

Young Seok Ko

A blood pressure monitor may include a photoplethysmogram (PPG) sensor to obtain a PPG sensor and at least one processor configured to extract characteristic points from the PPG signal, determine internally dividing points of the characteristic points based on time values of the characteristic points, extract feature values from the PPG signal based on the internally dividing points, and determine a blood pressure based on the extracted feature values of the PPG signal. The blood pressure monitor may further include a display configured to provide a graphical user interface that displays a vertical line that is movable in a timeline over a graph that shows a change in the blood pressure over time, a blood pressure value corresponding to a position of the vertical line, and component pulses constituting the PPG signal, together with the graph and the vertical line.

Apparatus and method for estimating bio-information

An apparatus for non-invasively estimating bio-information and a method of determining whether a bio-signal is normal by the apparatus for estimating bio-information are provided. The apparatus for estimating bio-information according to an embodiment of the disclosure includes: a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object; and a processor configured to extract a plurality of pairs of local maximum points and local minimum points from a second derivative signal of the PPG signal, to select at least one reference pair from among the extracted plurality of pairs, and to determine whether the PPG signal is normal based on the selected at least one reference pair.

Apparatus for estimating bio-information and method of detecting abnormal bio-signal

An apparatus for estimating blood pressure may include: a photoplethysmogram (PPG) sensor configured to measure a PPG signal from a user; and a processor configured to: extract a cardiovascular feature from the PPG signal; calculate a first variation in the extracted cardiovascular feature compared to a reference cardiovascular feature measured at a reference time; determine a measurement posture of the PPG signal based on a time interval between two waveform components of the PPG signal; in response to the measurement posture corresponding to the reference posture, estimate the blood pressure based on the first variation; and in response to the measurement posture not corresponding to the reference posture, obtain a second variation by correcting the first variation; and estimate blood pressure based on the second variation.

Apparatus and method for estimating blood pressure

An apparatus for non-invasively estimating blood pressure is provided. The apparatus for estimating blood pressure may include a bio-signal measurer configured to measure a bio-signal from a user and a processor configured to estimate blood pressure using the measured bio-signal. The processor may extract a first feature and a second feature from the bio-signal at an extraction time, estimate changes in the first feature and the second feature which have occurred during a time period from a calibration time at which the first feature and the second feature are calibrated to the extraction time at which the first feature and the second feature are extracted, and estimate a blood pressure based on the changes in the first feature and the second feature.

An apparatus for estimating blood pressure may include: a memory storing one or more instructions; and a processor configured to execute the one or more instructions to: extract a cardiac output (CO) feature, a first candidate total peripheral resistance (TPR) feature, and a second candidate TPR feature from a bio-signal; determine one of the first candidate TPR feature and the second candidate TPR feature as a TPR feature based on a direction of change in the CO feature and a direction of change in the first candidate TPR feature between a blood pressure measurement time and a calibration time; and estimate the blood pressure based on the TPR feature and the CO feature.

A method of determining regularity of a bio-signal is provided. The method of determining regularity of a bio-signal according may include acquiring a plurality of pulse waveforms of the bio-signal, acquiring a plurality of slope waveforms corresponding to the plurality of pulse waveforms, binarizing the plurality of slope waveforms, acquiring synchronization information of the plurality of pulse waveforms based on binarizing the plurality of pulse waveforms; acquiring a synchronization rate of a reference interval based on the synchronization information, and determining whether the bio-signal is regular or irregular based on the synchronization rate of the reference interval.

Method of determining regularity of bio-signal, apparatus and method for estimating bio-information

An adaptive bio-signal feature combining apparatus includes: a feature extractor configured to extract first feature values and second feature values from a bio-signal of an object; a stable interval determiner configured to determine at least one stable interval in the bio-signal; a statistical variable calculator configured to calculate a statistical variable value of a first feature and a statistical variable value of a second feature for each of the at least one stable interval based on the first and second feature values extracted from the at least one stable interval; and a feature combiner configured to calculate an integrated combining coefficient that is used to combine the first feature and the second feature, based on the statistical variable value of the first feature and the statistical variable value of the second feature.

Adaptive bio-signal feature combining apparatus and method

An apparatus for estimating bio-information is provided. The apparatus for estimating bio-information by using an ultrasonic signal according to an embodiment of the present disclosure includes: an ultrasonic sensor configured to acquire an ultrasonic signal from an object; and a processor configured to detect peaks from the acquired ultrasonic signal, and to determine false detection of a peak, among the detected peaks, by using at least one of amplitudes of the detected peaks or a left waveform shape and a right waveform shape of the peak.

Apparatus for estimating bio-information, and method of determining false detection of bio-signal peaks

A method of obtaining a feature for blood pressure estimation is provided. The method includes extracting a reference feature from a bio-signal; obtaining a feature for blood pressure estimation by: obtaining, as the feature for blood pressure estimation, a first candidate feature based on the reference feature being less than a first threshold; obtaining, as the feature for blood pressure estimation, a second candidate feature based on the reference feature being greater than or equal to a second threshold that is greater than the first threshold; or obtaining, as the feature for blood pressure estimation, a combination of the first candidate feature and the second candidate feature based on the reference feature being less than the second threshold; and estimating a blood pressure by using the obtained feature.

Method of obtaining feature for blood pressure estimation, apparatus and method for estimating blood pressure

An apparatus for non-invasively estimating bio-information may include a bio-signal acquirer configured to acquire a bio-signal; and a processor configured to extract a plurality of characteristic points from the bio-signal, determine internally dividing points of the plurality of characteristic points, and extract feature values from the bio-signal based on the internally dividing points to perform bio-information estimation. The plurality of characteristic points may include a first time point and a second time point when the pulse wave signal includes a first component pulse wave that has a maximum amplitude at the first time point, and a second component pulse wave that has a maximum amplitude at the second time point.

An apparatus for estimating bio-information of a user may include a first sensor configured to measure a first signal from the user; a second sensor configured to measure a second signal from the user; and a processor configured to obtain a first characteristic point from the first signal; obtain a second characteristic point from the second signal based on the first characteristic point and a pre-defined probability distribution function; and estimate the bio-information of the user based on the second characteristic point.

An apparatus for estimating blood pressure is provided. The apparatus for estimating blood pressure according to an example embodiment includes: a sensor configured to measure a photoplethysmogram (PPG) signal from an object; and a processor configured to detect a position of a dicrotic notch based on a local maximum point and a local minimum point of a second-order derivative signal of the PPG signal, to obtain a first value and a second value from a first section and a second section of the PPG signal divided based on the dicrotic notch of the PPG signal, to obtain a pulse pressure feature value based on the first value and the second value, and to estimate blood pressure based on a variation in the obtained pulse pressure feature value compared to a reference pulse pressure feature value.

An apparatus for generating a blood pressure estimation model includes: a signal acquirer configured to receive input a first signal and a second signal from a user; and a processor configured to obtain a pulse transit time (PTT) as a first predictor variable value based on the first signal and the second signal, to extract at least one feature from the second signal, to obtain a second predictor variable value based on the extracted at least one feature, and to generate a blood pressure estimation model based on the first predictor variable value and the second predictor variable value.

Apparatus and method for generating blood pressure estimation model, and apparatus for estimating blood pressure

Provided is an apparatus for estimating bio-information. The apparatus for estimating bio-information according to an embodiment includes a processor configured to obtain a pulse wave signal from a user; extract components of a plurality of element waveforms which constitute a waveform of the pulse wave signal; and obtain a cardiovascular feature based on the extracted components of the plurality of element waveforms. The processor is configured to extract a component of at least one element waveform based on a component of an adjacent element waveform.

An apparatus for estimating blood pressure is provided. According to one embodiment, the apparatus for estimating blood pressure may include a sensor configured to measure a bio-signal from a subject, and a processor configured to acquire, form the bio-signal, a first feature value associated with cardiac output (CO) and a second feature value associated with total peripheral resistance (TPR), determine whether a current mechanism of blood pressure change of the subject is a post-exercise hypotension mechanism based on the first feature value and the second feature value, and estimate blood pressure according to determination of whether the current mechanism is the post-exercise hypotension mechanism.

Growing community of inventors

Hwaseong-si, South Korea

Ui Kun Kwon