公开(公告)号：US20220125370A1

公开(公告)日：2022-04-28

申请号：US17077020

申请日：2020-10-22

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Umar Asif ,  Stefan von Cavallar ,  Jianbin Tang ,  Stefan Harrer

IPC: A61B5/00 ,  A61B5/0476 ,  G16H50/70

Abstract: A method, a computer program product, and a computer system determine abnormal motion from a patient. The method includes receiving sensory data of the patient and a location in which the patient is present. The sensory data includes video data over a period of time the patient is being monitored. The method includes generating contextual information based on the sensory data. The contextual information is indicative of surroundings of the patient and characteristics of the location. The method includes generating motion information based on the sensory data. The motion information is indicative of movement of the patient in the location. The method includes generating contextual motion data by incorporating the contextual information with the motion information. The method includes determining the abnormal motion based on the contextual motion data.

公开(公告)号：US11734453B2

公开(公告)日：2023-08-22

申请号：US17249132

申请日：2021-02-22

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Tian Hao ,  Umar Asif ,  Stefan Harrer ,  Jianbin Tang ,  Stefan von Cavallar ,  Deval Samirbhai Mehta ,  Jeffrey L. Rogers ,  Erhan Bilal ,  Stefan Renard Maetschke

IPC: G06F21/62 ,  G06V40/20 ,  G06F18/24

CPC classification number: G06F21/6263 ,  G06F18/24 ,  G06V40/20

Abstract: A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include collecting data corresponding to a user with one or more sensors and identifying one or more joints of the user based on the data. Embodiments may additionally include generating one or more 3D representations of the one or more joints of the user and anonymizing the one or more 3D representations by applying thereto a joint-centering and a random shuffling. Embodiments may further include classifying one or more actions of the user based on analysing the one or more 3D representations, and exporting at least one of the data and the one or more actions.

公开(公告)号：US20220280098A1

公开(公告)日：2022-09-08

申请号：US17249412

申请日：2021-03-02

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Tian Hao ,  Jeffrey L. Rogers ,  Umar Asif ,  Erhan Bilal ,  Deval Samirbhai Mehta ,  Stefan Harrer ,  Jianbin Tang ,  Stefan von Cavallar ,  Paolo Fraccaro

IPC: A61B5/00 ,  G16H50/30 ,  G16H50/20 ,  A61B5/11

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for assessing one or more Parkinson's disease symptoms. The exemplary embodiments may include collecting data of a user's motion, extracting one or more features from the collected data, and assessing one or more Parkinson's disease symptoms of the user based on applying one or more models to the data.

公开(公告)号：US20220269824A1

公开(公告)日：2022-08-25

申请号：US17249132

申请日：2021-02-22

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： TIAN HAO ,  Umar Asif ,  Stefan Harrer ,  Jianbin Tang ,  Stefan von Cavallar ,  Deval Samirbhai Mehta ,  JEFFREY L. ROGERS ,  Erhan Bilal ,  Stefan Renard Maetschke

IPC: G06F21/62 ,  G06K9/00 ,  G06K9/62

Abstract: A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include collecting data corresponding to a user with one or more sensors and identifying one or more joints of the user based on the data. Embodiments may additionally include generating one or more 3D representations of the one or more joints of the user and anonymizing the one or more 3D representations by applying thereto a joint-centering and a random shuffling. Embodiments may further include classifying one or more actions of the user based on analysing the one or more 3D representations, and exporting at least one of the data and the one or more actions.

公开(公告)号：US12126828B2

公开(公告)日：2024-10-22

申请号：US18361887

申请日：2023-07-30

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Umar Asif ,  Lenin Mehedy ,  Jianbin Tang

IPC: H04N19/54 ,  G06N20/00 ,  G06V10/46 ,  H04N19/23 ,  H04N21/234

CPC classification number: H04N19/54 ,  G06N20/00 ,  G06V10/462 ,  H04N19/23 ,  H04N21/23418

Abstract: A computer-implemented method of decoding video data in multiple resolution formats includes receiving an encoded video stream including a salient data and a non-salient data, the salient data having a higher resolution format than the non-salient data. The video stream is decoded into the non-salient data in a lower-resolution format and the salient data in the higher-resolution format. The non-salient data is reconstructed to a higher resolution format. The salient data and the reconstructed non-salient data are combined to form a video stream in the higher-resolution format of the salient data.

公开(公告)号：US20230334180A1

公开(公告)日：2023-10-19

申请号：US18343776

申请日：2023-06-29

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： TIAN HAO ,  Umar Asif ,  Stefan Harrer ,  Jianbin Tang ,  Stefan von Cavallar ,  Deval Samirbhai Mehta ,  JEFFREY L. ROGERS ,  Erhan Bilal ,  Stefan Renard Maetschke

IPC: G06F21/62 ,  G06V40/20

CPC classification number: G06F21/6263 ,  G06V40/20 ,  G06F18/24

Abstract: A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include identifying one or more joints of a user based on collected data and generating one or more 3D representations of the one or more joints of the user. Embodiments may further include anonymizing the one or more 3D representations, classifying one or more actions of the user based on the one or more 3D representations, wherein the classifying outputs an action score, and exporting at least one of the one or more actions and the action score.

公开(公告)号：US10552664B2

公开(公告)日：2020-02-04

申请号：US15821950

申请日：2017-11-24

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Umar Asif ,  Stefan Harrer ,  Jianbin Tang ,  Antonio Jimeno Yepes

IPC: G06K9/00 ,  G06K9/62 ,  A61B6/00 ,  G06T7/00 ,  A61B34/32 ,  A61B34/10

Abstract: A method for digital image classification and localization includes receiving a digital image of a biological organism from an imaging apparatus, the digital image comprising a plurality of intensities on a 2-dimensional grid of points, generating a plurality of discriminative representations of the 2D digital image by extracting dominant characteristics of the image from three different viewpoints, where the plurality of discriminative representations form a 3-dimensional digital image, combining the 3D digital image with the 2D digital image in a convolutional neural network that outputs a 3-channel feature map that localizes image abnormalities in each of the three channels and includes a detection confidence that each abnormalities is a neoplasm, providing the 3-channel feature map to a controller of a robotic surgical device where the robotic surgical device uses the 3-channel feature map to locate the neoplasm within the biological organism in a surgical procedure for treating the neoplasm.

公开(公告)号：US20240022759A1

公开(公告)日：2024-01-18

申请号：US18361887

申请日：2023-07-30

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Umar Asif ,  Lenin Mehedy ,  Jianbin Tang

IPC: H04N19/54 ,  H04N21/234 ,  G06N20/00 ,  H04N19/23 ,  G06V10/46

CPC classification number: H04N19/54 ,  H04N21/23418 ,  G06N20/00 ,  H04N19/23 ,  G06V10/462

Abstract: A computer-implemented method of decoding video data in multiple resolution formats includes receiving an encoded video stream including a salient data and a non-salient data, the salient data having a higher resolution format than the non-salient data. The video stream is decoded into the non-salient data in a lower-resolution format and the salient data in the higher-resolution format. The non-salient data is reconstructed to a higher resolution format. The salient data and the reconstructed non-salient data are combined to form a video stream in the higher-resolution format of the salient data.

公开(公告)号：US20220101185A1

公开(公告)日：2022-03-31

申请号：US17036248

申请日：2020-09-29

Applicant: International Business Machines Corporation

Inventor： Umar Asif ,  Stefan von Cavallar ,  Jianbin Tang ,  Stefan Harrer

IPC: G06N20/00 ,  G06K9/62

Abstract: A machine learning model can be updated based on collected data (i.e., initially unlabeled data). The unlabeled data can be labeled based on comparisons to labeled data. The newly labeled data, referred to as “weak labeled data” (as it was labeled without direct input of a professional) can then be used as training data in order to retrain the machine learning model.

公开(公告)号：US20220101184A1

公开(公告)日：2022-03-31

申请号：US17036218

申请日：2020-09-29

Applicant: International Business Machines Corporation

Inventor： Umar Asif ,  Stefan von Cavallar ,  Jianbin Tang ,  Stefan Harrer

IPC: G06N20/00 ,  G06N3/08

Abstract: A machine learning model can be optimized for deployment on a device based on hardware specifications of the device. An existing model is acquired and pruned to reduce hardware resource consumption of the model. The pruned model is then trained based on training data. The pruned model is also trained based on a collection of “teacher” models. Performance of the trained model is then evaluated and compared to performance requirements, which can be based on the hardware specifications of a device.