UnitedHealth Group had three patents in internet of things during Q4 2023. The UnitedHealth Group Inc filed patents for an automated eating detection system using a continuous glucose monitor and accelerometer to identify eating episodes and generate individual models for future detection. Another patent involves a balance detection and correction system using sensors in the ear and on the body to track the user’s head position and detect imbalances in posture or movements, triggering a response action. GlobalData’s report on UnitedHealth Group gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

UnitedHealth Group grant share with internet of things as a theme is 33% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Methods and systems to detect eating (Patent ID: US20230346306A1)

The patent filed by UnitedHealth Group Inc. describes methods and systems for automated eating detection using a continuous glucose monitor, accelerometer, and processing unit. The system identifies eating episodes based on glucose readings and acceleration data during a first time period, then generates an individual model to detect eating episodes using only acceleration data. Additional sensor types like PPG or heart rate can also be used to enhance the detection process. The patent includes computer-implemented methods and systems for receiving acceleration readings, providing glucose-related predictions, and training predictive models based on glucose or light-based readings to identify eating episodes accurately.

The computer-implemented methods and systems outlined in the patent involve processing acceleration data to predict glucose-related information, indicating potential eating episodes. By utilizing wearable devices to capture glucose or light-based readings during specific time periods, the system can effectively identify eating episodes based on predetermined criteria. The use of predictive models such as LSTM, recursive neural network classifiers, or hidden Markov models further enhances the accuracy of detecting eating episodes using acceleration data. Overall, the patent presents a comprehensive approach to automated eating detection that leverages multiple sensor inputs and advanced predictive modeling techniques to improve health monitoring and management.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.