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公开(公告)号：US20230329624A1
公开(公告)日：2023-10-19
申请号：US18336161
申请日：2023-06-16
Applicant: Medtronic, Inc.
Inventor： Lindsay A. Pedalty , Niranjan Chakravarthy , Rodolphe Katra , Tarek D. Haddad , Andrew Radtke , Siddharth Dani , Donald R. Musgrove
CPC classification number: A61B5/361 , A61B5/7264 , A61B5/742 , A61B5/7405 , A61B5/316 , A61B5/322 , A61B5/352 , A61B5/363 , A61B5/346
Abstract: Techniques are disclosed for explaining and visualizing an output of a machine learning system that detects cardiac arrhythmia in a patient. In one example, a computing device receives cardiac electrogram data sensed by a medical device. The computing device applies a machine learning model, trained using cardiac electrogram data for a plurality of patients, to the received cardiac electrogram data to determine, based on the machine learning model, that an episode of arrhythmia has occurred in the patient and a level of confidence in the determination that the episode of arrhythmia has occurred in the patient. In response to determining that the level of confidence is greater than a predetermined threshold, the computing device displays, to a user, a portion of the cardiac electrogram data, an indication that the episode of arrhythmia has occurred, and an indication of the level of confidence that the episode of arrhythmia has occurred.
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公开(公告)号：US11759131B2
公开(公告)日：2023-09-19
申请号：US17306474
申请日：2021-05-03
Applicant: Medtronic, Inc.
Inventor： John E. Burnes , James K. Carney , Jonathan L. Kuhn , Mark J. Phelps , Jesper Svenning Kristensen , Rodolphe Katra
IPC: A61B5/1459 , A61B5/145 , A61B5/0205 , A61B5/1473 , A61B5/00 , A61B5/20 , A61N1/375 , G01N21/64 , A61B5/07 , A61B5/08 , A61B5/024 , G01N21/01 , A61M5/172 , A61M5/142
CPC classification number: A61B5/1459 , A61B5/0031 , A61B5/0036 , A61B5/0071 , A61B5/02055 , A61B5/076 , A61B5/14507 , A61B5/14546 , A61B5/14735 , A61B5/201 , A61B5/4381 , A61B5/4833 , A61B5/4839 , A61B5/4848 , A61B5/4866 , A61B5/686 , A61B5/6861 , A61B5/7278 , A61N1/3756 , G01N21/6408 , G01N21/6428 , A61B5/02405 , A61B5/08 , A61M5/14276 , A61M5/1723 , A61M2205/3523 , A61M2205/3553 , G01N2021/0143 , G01N2021/6417 , G01N2021/6441
Abstract: In some examples, a medical system includes a medical device. The medical device may include a housing configured to be implanted in a target site of a patient, a light emitter configured to emit a signal configured to cause a fluorescent marker to emit a fluoresced signal into the target site, and a light detector that may be configured to detect the fluoresced signal. The medical system may include processing circuitry configured to determine a characteristic of the fluorescent marker based on the emitted signal and the fluoresced signal. The characteristic of the fluorescent marker may be indicative of a presence of a compound in the patient, and the processing circuitry may be configured to track the presence of the compound of the patient based on the characteristic of the fluorescent marker.
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公开(公告)号：US11723577B2
公开(公告)日：2023-08-15
申请号：US16850749
申请日：2020-04-16
Applicant: Medtronic, Inc.
Inventor： Lindsay A. Pedalty , Niranjan Chakravarthy , Rodolphe Katra , Tarek D. Haddad , Andrew Radtke , Siddharth Dani , Donald R. Musgrove
CPC classification number: A61B5/361 , A61B5/316 , A61B5/322 , A61B5/346 , A61B5/352 , A61B5/363 , A61B5/7264 , A61B5/742 , A61B5/7405
Abstract: Techniques are disclosed for explaining and visualizing an output of a machine learning system that detects cardiac arrhythmia in a patient. In one example, a computing device receives cardiac electrogram data sensed by a medical device. The computing device applies a machine learning model, trained using cardiac electrogram data for a plurality of patients, to the received cardiac electrogram data to determine, based on the machine learning model, that an episode of arrhythmia has occurred in the patient and a level of confidence in the determination that the episode of arrhythmia has occurred in the patient. In response to determining that the level of confidence is greater than a predetermined threshold, the computing device displays, to a user, a portion of the cardiac electrogram data, an indication that the episode of arrhythmia has occurred, and an indication of the level of confidence that the episode of arrhythmia has occurred.
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公开(公告)号：US11583687B2
公开(公告)日：2023-02-21
申请号：US16850833
申请日：2020-04-16
Applicant: Medtronic, Inc.
Inventor： Siddharth Dani , Tarek D. Haddad , Donald R. Musgrove , Andrew Radtke , Niranjan Chakravarthy , Rodolphe Katra , Lindsay A. Pedalty
Abstract: Techniques are disclosed for monitoring a patient for the occurrence of a cardiac arrhythmia. A computing system generates sample probability values by applying a machine learning model to sample patient data. The machine learning model determines a respective probability value that indicates a probability that the cardiac arrhythmia occurred during each respective temporal window. The computing system outputs a user interface comprising graphical data based on the sample probability values and receives, via the user interface, an indication of user input to select a probability threshold for a patient. The computing system receives patient data for the patient and applies the machine learning model to the patient data to determine a current probability value. In response to the determination that the current probability exceeds the probability threshold for the patient, the computing system generates an alert indicating the patient has likely experienced the occurrence of the cardiac arrhythmia.
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公开(公告)号：US11443852B2
公开(公告)日：2022-09-13
申请号：US17377763
申请日：2021-07-16
Applicant: Medtronic, Inc.
Inventor： Niranjan Chakravarthy , Siddharth Dani , Tarek D. Haddad , Donald R. Musgrove , Andrew Radtke , Rodolphe Katra , Lindsay A. Pedalty
IPC: G16H50/20 , A61B5/00 , A61B5/11 , G16H50/30 , G06N20/00 , G06N5/04 , G06N5/02 , A61B5/35 , A61B5/316
Abstract: Techniques are disclosed for using feature delineation to reduce the impact of machine learning cardiac arrythmia detection on power consumption of medical devices. In one example, a medical device performs feature-based delineation of cardiac electrogram data sensed from a patient to obtain cardiac features indicative of an episode of arrythmia in the patient. The medical device determines whether the cardiac features satisfy threshold criteria for application of a machine learning model for verifying the feature-based delineation of the cardiac electrogram data. In response to determining that the cardiac features satisfy the threshold criteria, the medical device applies the machine learning model to the sensed cardiac electrogram data to verify that the episode of arrhythmia has occurred or determine a classification of the episode of arrythmia.
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Patent Agency Ranking
公开(公告)号：US20220160310A1
公开(公告)日：2022-05-26
申请号：US17103432
申请日：2020-11-24
Applicant: Medtronic, Inc.
Inventor： Pranam Shetty , Niranjan Chakravarthy , Maneesh Shrivastav , Rodolphe Katra , Thomas Piaget , Arthur K. Lai
Abstract: This disclosure is directed to techniques for recording and recognizing physiological parameter patterns associated with symptoms. A medical device system includes a medical device including one or more sensors configured to generate a signal that indicates a parameter of a patient. Additionally, the medical device system includes processing circuitry configured to receive data indicative of a user indication of an experienced symptom; determine a plurality of parameter values of the parameter based on a portion of the signal corresponding to a period of time including a time before the user indication and a period of time after the user indication. Additionally, the processing circuitry is configured to identify, based on a reference set of parameter values of the plurality of parameter values, the experienced symptom. Additionally, the processing circuitry is configured to save, to a database in memory, a set of data including the experienced symptom and patient parameters.
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公开(公告)号：US20150217118A1
公开(公告)日：2015-08-06
申请号：US14562079
申请日：2014-12-05
Applicant: Medtronic, Inc.
Inventor： Rajan Prakash , Rodolphe Katra
CPC classification number: A61N1/36514 , A61B5/02028 , A61B5/11 , A61B5/686 , A61B5/6869 , A61M5/14276 , A61M5/1723 , A61M2005/1726 , A61M2205/04 , A61M2205/3303 , A61M2230/04 , A61N1/0587 , A61N1/36578 , A61N2001/0585
Abstract: A chronically implanted medical device, connected to a medical electrical lead that includes a sensor, is used to detect diastolic dysfunction. A LV accelerometer signal is sensed through the sensor. Based on the LV accelerometer signal, a determination is made as to whether diastolic dysfunction data exists.
Abstract translation: 连接到包括传感器的医用电导线的长期植入的医疗装置用于检测舒张功能障碍。 通过传感器感测LV加速度计信号。 基于LV加速度计信号，确定是否存在舒张功能障碍数据。
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公开(公告)号：US20250098993A1
公开(公告)日：2025-03-27
申请号：US18972232
申请日：2024-12-06
Applicant: Medtronic, Inc.
Inventor： John E. Burnes , James K. Carney , Jonathan L. Kuhn , Mark J. Phelps , Jesper Svenning Kristensen , Rodolphe Katra
IPC: A61B5/1459 , A61B5/00 , A61B5/0205 , A61B5/024 , A61B5/07 , A61B5/08 , A61B5/145 , A61B5/1473 , A61B5/20 , A61M5/142 , A61M5/172 , A61N1/375 , G01N21/01 , G01N21/64
Abstract: In some examples, a medical system includes a medical device. The medical device may include a housing configured to be implanted in a target site of a patient, a light emitter configured to emit a signal configured to cause a fluorescent marker to emit a fluoresced signal into the target site, and a light detector that may be configured to detect the fluoresced signal. The medical system may include processing circuitry configured to determine a characteristic of the fluorescent marker based on the emitted signal and the fluoresced signal. The characteristic of the fluorescent marker may be indicative of a presence of a compound in the patient, and the processing circuitry may be configured to track the presence of the compound of the patient based on the characteristic of the fluorescent marker.
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公开(公告)号：US12262153B2
公开(公告)日：2025-03-25
申请号：US17215419
申请日：2021-03-29
Applicant: Medtronic, Inc.
Inventor： Rodolphe Katra , Amie Bucksa , Niranjan Chakravarthy
IPC: H04N7/18 , A61B90/00 , G06N20/00 , G06T7/00 , G16H10/60 , G16H30/20 , G16H30/40 , G16H40/40 , G16H40/67 , G16H50/70 , H04N23/62 , A61N1/372 , G16H15/00 , G16H40/20 , G16H50/20
Abstract: Techniques for remote monitoring of a patient and corresponding medical device(s) are described. The remote monitoring comprises determining identification data and identifying implantable medical device (IMD) information, initiating an imaging device and determining an imaging program, receiving one or more frames of image data including image(s) of an implantation site, identifying an abnormality at the implantation site, triggering a supplemental image capture mode, receiving one or more supplemental images of the implantation site, and outputting the one or more supplemental images of the implantation site.
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公开(公告)号：US12161487B2
公开(公告)日：2024-12-10
申请号：US18304696
申请日：2023-04-21
Applicant: Medtronic, Inc.
Inventor： Niranjan Chakravarthy , Siddharth Dani , Tarek D. Haddad , Rodolphe Katra , Donald R. Musgrove , Lindsay A. Pedalty , Andrew Radtke
Abstract: Techniques are disclosed for monitoring a patient for the occurrence of cardiac arrhythmias. A computing system obtains a cardiac electrogram (EGM) strip for a current patient. Additionally, the computing system may apply a first cardiac rhythm classifier (CRC) with a segment of the cardiac EGM strip as input. The first CRC is trained on training cardiac EGM strips from a first population. The first CRC generates first data regarding an aspect of a cardiac rhythm of the current patient. The computing system may also apply a second CRC with the segment of the cardiac EGM strip as input. The second CRC is trained on training cardiac EGM strips from a smaller, second population. The second CRC generates second data regarding the aspect of the cardiac rhythm of the current patient. The computing system may generate output data based on the first and/or second data.
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