Orbsurgical Ltd.

National Research Council of Canada

Sanju Lama

Garnette Roy Sutherland

Rahul Singh

Amir Baghdadi

Hamidreza Hoshyarmanesh

Kourosh Zareinia

Mehdi Arbabi-Ghahroudi

Liu Shi Gan

Tomas Jens Hirmer

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.).

Machine learning-assisted surgery

A local haptic hand controller is provided for enabling an operator to remotely perform fine manipulation, such as microsurgery, in conjunction with a remotely located robotic manipulator, for example at which the microsurgery is to be performed. The local haptic hand controller includes a base, a kinematic structure in communication with the base and comprises a gimbal as an end effector. A local surgical tool is provided at the gimbal and has a shape and construction substantially similar to a remote surgical tool provided at the remote robotic manipulator. A control system is in communication with the local surgical tool and with the remote surgical tool, and configured to enable operation of the local haptic hand controller when a local surgical tool identifier matches a remote surgical tool identifier.

Microsurgery-specific haptic hand controller

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 for interconnected surgical theater architecture

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 force profile segmentation model can construct a force profile using the received data. The force profile includes a plurality of force patterns. The force profile segmentation model includes at least one first machine learning trained using historical surgical instrument usage data. 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 force profile pattern recognition model using the constructed force profile and the extracted features. The force profile pattern recognition model includes at least one second machine learning model. Data characterizing the determination can be provided (e.g., displayed to a surgeon, etc.).

Machine learning-based surgical instrument characterization

Bipolar forceps of the type where each of the prongs has a manually engageable portion spaced from the tip for manual squeezing of the prongs and an electrical supply system for applying a high-frequency electric current between tool tips to dissect through tissue planes and/or seal blood vessels includes a set of force measuring sensors for measuring forces, particularly squeezing forces, applied to the prongs at the tip. A temperature sensor is included to provide temperature information and temperature compensation. The sensors are applied to each prong in opposing pairs on the inside and outside surfaces and the outputs thereof are applied to a bridge arrangement. The signals are sent to a processor for generating warning signals and for recording forces for training purposes where a haptic system can be used.

Bipolar forceps with force measurement

The present invention relates to Tau-specific antibodies, fragments thereof, and uses thereof. More specifically, the present invention relates to Tau-specific antibodies, fragments thereof, and conjugates thereof with conjugated to a superparamagnetic nanoparticle. The molecules of the present invention may be used in visualizing damage from traumatic brain injury.

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Calgary, Canada

Sanju Lama