Operating room black-box device, system, method and computer readable medium for event and error prediction
AssigneeSurgical Safety Technologies Inc.
InventorsTeodor Pantchev GRANTCHAROV, Kevin Lee YANG
Life of this patent
Estimating the term…
Abstract
A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.
Claims41
A system for collecting and processing medical or surgical data comprising:
- a plurality of hardware units for collecting real-time medical or surgical data streams having a control interface coupled by a network to cameras, sensors, audio devices, and patient monitoring hardware, the real-time medical or surgical data streams relating to a real-time medical procedure within an operating or clinical site;
- an encoder with a network server for synchronizing and recording the real-time medical or surgical data streams to a common clock or timeline to generate a session container file;
- the network server configured to control a multi-nodal perception engine to:
- generate a protocol for data extraction from the session container file;
- process the data using the protocol to extract patterns for time-stamped clinical events within the session container file, each time-stamped clinical event associated with a confidence level;
- generate an interface indicator for a temporal sequence of the time-stamped clinical events within the session container file and error assessments, the interface indicator identifying each of the time-stamped clinical events and the associated confidence levels;
- and
- generate a predictive data model for refining protocol generation using support vector machines or artificial intelligence network data structures with neural networks for modelling correlation of data for interference and feature extraction.
A multi-channel encoder for collecting, integrating, synchronizing and recording medical or surgical data streams onto a single interface with a common timeline or clock, the medical or surgical data streams received as independent real-time or live data streams from a plurality of hardware units, the encoder having a network server for scheduling transmission of session file containers for the recordings, the encoder processing the medical or surgical data streams to generate measurement metrics relating to a real-time medical procedure, the encoder configured to generate a protocol for data extraction from the session container file;
- process the data using the protocol to define patterns for time-stamped clinical events within the session container file;
- generate an interface indicator for a visual sequence of the time-stamped clinical events within the session container file and correspondence assessments;
- generate a predictive data model for refining protocol generation using support vector machines or artificial intelligence network data structures.
A method for collecting and processing medical or surgical data comprising:
- receiving, at a multi-channel encoder, a plurality of live or real-time independent input feeds from one or more data capture devices located in an operating room or other patient intervention area, the input feeds relating to a live or real-time medical procedure;
- synchronizing, by the encoder, the plurality of live independent input feeds onto a single interface with a common timeline or clock;
- recording the synchronized input feeds using a network server;
- generating, by the encoder, an output session file using the synchronized input feeds;
- transmitting the output session file using the network server;
- generating a protocol for data extraction from the session container file;
- processing the data using the protocol to define patterns for time-stamped clinical events within the session container file;
- generating an interface indicator for a visual sequence of the time-stamped clinical events within the session container file and correspondence assessments;
- and
- generating a predictive data model for refining protocol generation using support vector machines or artificial intelligence network data structures.
A cloud based system for collecting and processing medical or surgical data comprising:
- an encoder having a control interface for, in response to receiving a control command, triggering collection of real-time medical or surgical data streams by smart devices including cameras, sensors, audio devices, and patient monitoring hardware, the medical or surgical data relating to a real-time medical procedure within an operating or clinical site, the encoder for authenticating the smart devices, the smart devices synchronizing the real-time medical or surgical data streams by embedding timestamp markers within the real-time medical or surgical data streams, the timestamp markers generated by each smart device by a device clock;
- a media management hub server with middleware and hardware for translating, connecting, formatting, and recording the real-time medical or surgical data streams to generate session container files on network accessible storage devices;
- wireless network infrastructure to provide a secure network connection between the encoder, the smart devices and the media management hub server for communication of the real-time medical or surgical data streams;
- a central content server for storing and distributing the session container files and providing a two-way communication interface for the media management hub to implement a file transfer handshake for the session container files, the central content server configured to:
- generate a protocol for data extraction from the session container file;
- process the data using the protocol to define patterns for time-stamped clinical events within the session container file;
- generate an interface indicator for a visual sequence of the time-stamped clinical events within the session container file and correspondence assessments;
- generate a predictive data model for refining protocol generation using support vector machines or artificial intelligence network data structures;
- and
- switching or gateway hardware to transmit the session container files from the media management hub to the central content server.
Dependencies are inferred from the claim text.