18463657. MACHINE LEARNING METHOD TO DETERMINE PATIENT BEHAVIOR USING VIDEO AND AUDIO ANALYTICS simplified abstract (Insight Direct USA, Inc.)

MACHINE LEARNING METHOD TO DETERMINE PATIENT BEHAVIOR USING VIDEO AND AUDIO ANALYTICS

Organization Name

Insight Direct USA, Inc.

Inventor(s)

Michael Griffin of Wayland MA (US)

Hailey Kotvis of Wauwatosa WI (US)

Josephine Miner of Hope RI (US)

Porter Moody of Wayland MA (US)

Kayla Poulsen of Natick MA (US)

Austin Malmin of Gilbert AZ (US)

Sarah Onstad-hawes of Seattle WA (US)

Gloria Solovey of Arlington MA (US)

Austin Streitmatter of Palm Harbor FL (US)

MACHINE LEARNING METHOD TO DETERMINE PATIENT BEHAVIOR USING VIDEO AND AUDIO ANALYTICS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18463657 titled 'MACHINE LEARNING METHOD TO DETERMINE PATIENT BEHAVIOR USING VIDEO AND AUDIO ANALYTICS

Simplified Explanation

The patent application describes a system for invoking an alert based on a patient's behavior as determined by a machine-learning model operating on a video stream of the patient. The system extracts video data, audio data, and semantic text data from the video stream, analyzes these data to identify features indicative of alerting behaviors, and compares the patient's behavior with the set of alerting behaviors to automatically invoke an alert when necessary.

• Machine-learning model determines patient behavior based on extracted data
• System compares patient behavior with set of alerting behaviors to invoke alert automatically

Potential Applications

This technology could be applied in healthcare settings to monitor patients and alert healthcare providers of any concerning behaviors or situations in real-time.

Problems Solved

This technology solves the problem of timely and accurate detection of alerting behaviors in patients, allowing for immediate intervention when necessary.

Benefits

The benefits of this technology include improved patient monitoring, early detection of potential issues, and timely alerts to healthcare providers for appropriate action.

Potential Commercial Applications

A potential commercial application of this technology could be in the development of patient monitoring systems for hospitals, nursing homes, and other healthcare facilities.

Possible Prior Art

One possible prior art for this technology could be existing patient monitoring systems that use machine learning and video analysis to detect abnormal behaviors in patients.

How does the system ensure patient privacy and data security?

The patent application does not provide details on how patient privacy and data security are maintained while extracting and analyzing video, audio, and text data.

What is the accuracy rate of the machine-learning model in detecting alerting behaviors?

The patent application does not mention the accuracy rate of the machine-learning model in determining patient behavior and invoking alerts based on the identified behaviors.

Original Abstract Submitted

Apparatus and associated methods relate to invoking an alert based upon a behavior of a patient as determined by a machine-learning model operating on a video stream of the patient. Video data, audio data, and semantic text data are extracted from a video stream of the patient. The video data are analyzed to identify first, second, and third features sets of video, audio, and semantic text features, respectively, which have been identified by a computer-implemented machine-learning engine as being indicative of at least one of a set of alerting behaviors corresponding to a patient classification of the patient. Using a computer-implemented machine-learning model, a patient behavior of the patient is determined based on the first, second, and/or third features sets. The patient's behavior is compared with the set of alerting behaviors, and, when the patient's behavior is determined to be included therein, the alert is automatically invoked.