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公开(公告)号：US20200146619A1
公开(公告)日：2020-05-14
申请号：US16628186
申请日：2018-07-10
发明人： Gary Nelson Garcia MOLINA , Cristhian Mauricio POTES BLANDON , Pedro Miguel FERREIRA DOS SANTOS DA FONSECA , Bryan CONROY , Minnan XU
IPC分类号： A61B5/00 , A61B5/0205
摘要： A system (400) for monitoring an individual's sleep includes: (i) a patient monitor (410) configured to obtain a patient waveform, the patient waveform comprising information representative of a vital statistic of the patient; a processor (420) in communication with the patient monitor and configured to: (i) process the patient waveform to generate a segmented waveform; (ii) extract at least one feature from a segment of the waveform in a time domain and/or at least one feature from the segment of the waveform in the frequency domain; (iii) classify, using the at least one extracted feature, a sleep stage of the patient for the segment of the waveform; and (iv) generate, from classified sleep stages for a plurality of segments of the waveform, a sleep quality measurement; and a user interface (480) configured to report the generated sleep quality measurement.
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公开(公告)号：US20230024573A1
公开(公告)日：2023-01-26
申请号：US17785087
申请日：2020-12-10
发明人： Kathy Mi Young LEE , Ashequl QADIR , Claire Yunzhu ZHAO , Minnan XU , Jonathan RUBIN , Nikhil GALAGALI
摘要： A system and method for visualizing and annotating temporal trends of an abnormal condition in patient data. A classification and visualization module detects one or more conditions in one or more images, e.g. X-ray images, and visualizes the condition on the image. A temporal disease state extraction module analyzes text, e.g. radiology reports, for indications of a change in the condition. A multimodal disease state comparison module fuses the extracted data into a compact representation of the condition changes over time.
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公开(公告)号：US20210350933A1
公开(公告)日：2021-11-11
申请号：US17277619
申请日：2019-09-16
发明人： David Paul NOREN , Asif RAHMAN , Bryan CONROY , Minnan XU , Nikhil GALAGALI
摘要： Various embodiments of the present disclosure are directed to a general statistical classifier (40) and a personal statistical classifier (50) for executing a patient risk prediction method. In operation, the general statistical classifier (40) may render a singular general independent vital sign risk score for a singular vital sign and/or may render plural general independent vital sign risk scores for plural vital signs. The personal statistical classifier (50) may render a singular personal vital sign risk score from an integration of a singular patient feature into the singular general independent vital sign risk score, and/or may also render plural personal independent vital sign risk scores from individual integrations of plural patient features into the singular general independent vital sign risk score, individual integrations of a singular patient feature into the plural general independent vital sign risk scores, and/or individual integrations of plural patient features into the plural general independent vital sign risk scores.
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公开(公告)号：US20200022597A1
公开(公告)日：2020-01-23
申请号：US16577425
申请日：2019-09-20
IPC分类号： A61B5/024 , A61B5/0255 , A61B5/0444 , A61B5/00 , A61B5/0456 , A61B5/04 , A61B5/0472
摘要： System (10) for extracting a fetal heart rate from at least one maternal signal using a computer processor (26). The system includes sensors (12-18) attached to a patient to receive abdominal ECG signals and a recorder and digitizer (20) to record and digitize each at least one maternal signal in a maternal signal buffer (22A-22D). The system further includes a peak detector (40) to identify candidate peaks in the maternal signal buffer. The signal stacker (42) of the system stacks the divides at least one maternal signal buffer into a plurality of snippets, each snippet including one candidate peak and a spatial filter (44) to identify and attenuate a maternal QRS signal in the plurality of snippets of the maternal signal buffer, the spatial filter including at least one of principal component analysis and orthogonal projection, to produce a raw fetal ECG signal which is stored in a raw fetal ECG buffer. The system further includes a fetal QRS identifier (46) for identifying peaks in the raw fetal ECG buffer by at least one of principal component analysis and a peak-detector followed by rule based fQRS extraction and a merger (48) to calculate and merge the fetal heart rate from the identified peaks.
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公开(公告)号：US20220028565A1
公开(公告)日：2022-01-27
申请号：US17276708
申请日：2018-09-17
发明人： Nikhil GALAGALI , Minnan XU , Bryan CONROY , Asif RAHMAN , David Paul NOREN
摘要： A method of determining patient subtyping from disease progression trajectories, including: extracting patient data and related time stamps from patient record data related to a disease, wherein the extracted patient data is incomplete and irregular; building a continuous-time disease progression model based upon the extracted patient data; and building a mixture model for clustering of patient disease trajectory subtypes.
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公开(公告)号：US20200261059A1
公开(公告)日：2020-08-20
申请号：US16061455
申请日：2016-12-20
发明人： Minnan XU , Balasundar Iyyavu RAJU , Ajay ANAND
摘要： A Doppler ultrasound instrument (10) includes ultrasound pulse control and data acquisition electronics (12, 24, 26) for acquiring Doppler ultrasound data, an N-channel connector port (14) for simultaneously operatively connecting up to N ultrasound transducer patches (16) where N is an integer equal to or greater than two, and an electronic processor (30) programmed to concurrently determine up to N blood flow velocities corresponding to up to N patches operatively connected to the N channel connector port. The blood flow velocity for each patch may be determined by: determining transducer blood flow velocities for ultrasound transducers (60) of a transducer array of the patch; and determining the blood flow velocity for the patch as a highest determined transducer blood flow velocity or as an aggregation of highest determined transducer blood flow velocities.
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公开(公告)号：US20190139631A1
公开(公告)日：2019-05-09
申请号：US16097299
申请日：2017-05-04
发明人： Larry James ESHELMAN , Eric Thomas CARLSON , Lin YANG , Minnan XU , Bryan CONROY
摘要： The present disclosure relates to estimation and use of clinician assessment of patient acuity. In various embodiments, a plurality of patient feature vectors associated with a plurality of respective patients may be obtained (302, 304). Each patient feature vector may include one or more health indicator features indicative of observable health indicators of a patient, and one or more treatment features indicative of characteristics of treatment provided to the patient. A machine learning model (216) may be trained (306) based on the patient feature vectors to receive, as input, subsequent patient feature vectors, and to provide, as output, indications of levels of clinician acuity assessment. Later, a patient feature vector associated with a given patient may be provided (404) as input to the machine learning model. Based on output from the machine learning model, a level of clinician acuity assessment associated with the given patient may be estimated (406) and used (408-416) for various applications.
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公开(公告)号：US20210298686A1
公开(公告)日：2021-09-30
申请号：US17266684
申请日：2019-07-30
发明人： Claire Yunzhu ZHAO , Minnan XU , Bryan CONROY
摘要： Methods and systems for managing alerts. The methods and systems described herein receive a classification decision related to a patient. If the classification decision is a borderline classification decision, the systems and methods described herein apply one or more alert filters to patient data to determine an alert filter condition. Upon determining the alert filter condition contradicts the borderline classification, the systems and methods may issue a contextual data alert to a clinician to prompt the clinician to consider contextual data related to the patient.
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公开(公告)号：US20210038088A1
公开(公告)日：2021-02-11
申请号：US16969114
申请日：2019-01-31
IPC分类号： A61B5/0205 , A61B5/00 , A61B5/16 , A61B5/1455 , A61B5/103 , A61B5/11 , A61B3/11 , G16H40/67 , G16H50/30 , G06N3/08 , G06T11/00 , G10L25/63 , G10L25/30 , G06K9/00 , G06K9/62 , G10L25/66 , H04N7/14
摘要： The present disclosure pertains to a system for providing client-side physiological condition estimations during a live video session. In some embodiments, the system includes a first client computer system that is caused to: (i) store a neural network on one or more computer-readable storage media of the first client computer system, (ii) obtain a live video stream of an individual via a camera of the first client computer system during a video streaming session between the first client computer system and a second client computer system, (iii) provide, during the video streaming session, video data of the live video stream as input to the neural network to obtain physiological condition information from the neural network, and (iv) provide, during the video streaming session, the physiological condition information for presentation at the second client computer system.
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10.发明申请公开(公告)号：US20190029533A1
公开(公告)日：2019-01-31
申请号：US16075812
申请日：2017-02-04
发明人： Cristhian M. POTES , Minnan XU , Bryan CONROY
摘要： The present disclosure pertains to a system configured to determine a hemodynamic instability risk score for a pediatric subject. The system is configured to: obtain an age of the subject; obtain feature values for one or more features associated with physiological characteristics of the subject; determine one or more feature value thresholds for individual features that indicate risk of hemodynamic instability in the subject, the feature value thresholds determined based on the age of the subject; determine feature contribution prediction scores for the individual features based on whether the obtained feature values breach one or more of the determined feature value thresholds for the individual features; and aggregate the feature contribution prediction scores to determine the hemodynamic instability risk score for the subject.
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