Machine learning for interconnected surgical theater architecture

    公开(公告)号:US11276001B1

    公开(公告)日:2022-03-15

    申请号:US17344813

    申请日:2021-06-10

    申请人: OrbSurgical Ltd.

    摘要: Each of a plurality of edge computing devices are configured to receive data streams generated by at least one sensor forming part of a respective medical device (e.g., a sensor-equipped surgical tool, etc.) which, in turn, characterizes use of the respective medical device in relation to a particular patient. Each of the edge computing devices can execute at least one machine learning model which generates or from which model attributes are derived. The generated model attributes are anonymized using an anonymization technique such as k-anonymity. The anonymized generated model attributes are homomorphically encrypted and transmitted to a central server. Encrypted model attribute updates to at least one of the machine learning models are later received from the central server which results in the machine learning models executing on one or more of the edge computing devices to be updated based on the received encrypted model attribute updates.

    Machine Learning-Assisted Surgery

    公开(公告)号:US20220367040A1

    公开(公告)日:2022-11-17

    申请号:US17540966

    申请日:2021-12-02

    申请人: OrbSurgical Ltd.

    摘要: Data is received that is generated by at least one sensor forming part of a surgical instrument. The sensor(s) on the surgical instrument can characterize use of the surgical instrument in relation to a patient. A first machine learning model can construct a force profile using the received data. The force profile includes a plurality of force patterns. In addition, a plurality of features are extracted from the received data. Thereafter, one or more attributes characterizing use of the surgical instrument are determined by a second machine learning model using the constructed force profile and the extracted features. Data characterizing the determination can be provided (e.g., displayed to a surgeon, etc.).