iRhythm Technologies. has been granted a patent for a monitor that processes continuous physiological signals to extract features and detect events. The system includes data encryption and transmission to a remote server, which uses machine learning to infer physiological events based on the processed data. GlobalData’s report on iRhythm Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on iRhythm Technologies, Treatment progress monitoring was a key innovation area identified from patents. iRhythm Technologies's grant share as of June 2024 was 52%. Grant share is based on the ratio of number of grants to total number of patents.
Wireless physiological signal processing and event inference system
The patent US11998342B2 describes a novel monitor designed to continuously detect and analyze physiological signals from users. The monitor incorporates a first sensor that captures a primary set of physiological signals, which may include Photoplethysmography (PPG) or electrocardiogram (ECG) data. A hardware processor processes these signals to extract relevant features, triggering a second sensor to detect a secondary set of physiological signals when certain thresholds are met. The data generated from these signals is processed through an encoder, producing an output that can be analyzed by an external computing system using a decoder or machine learning model to infer physiological events such as hypertension, depression, or sleep apnea. The monitor can be configured as a wearable patch or watch, and it may also encrypt the data output for secure transmission.
Additionally, the patent outlines various configurations for the monitor, including the use of machine learning networks to enhance signal processing. The system can derive signals from the first set to inform the detection of the second set, with the potential to predict physiological characteristics like arrhythmia likelihood or other heart-related abnormalities. The monitor's design allows for efficient data compression and transmission, ensuring that the output dimensions are manageable for further analysis. Overall, the technology aims to provide real-time monitoring and predictive insights into users' health conditions, leveraging advanced signal processing and machine learning techniques.
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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.
