Fresenius Medical Care has patented a computing system that utilizes sensors to monitor a user’s oxygen levels and generates a personalized erythropoiesis model. This model predicts future hematocrit and hemoglobin measurements, enabling tailored health management actions based on individual user data. GlobalData’s report on Fresenius Medical Care 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 Fresenius Medical Care, Remote monitored dialysis machines was a key innovation area identified from patents. Fresenius Medical Care's grant share as of June 2024 was 54%. Grant share is based on the ratio of number of grants to total number of patents.
Personalized erythropoiesis model generation for user training strategy
The granted patent US12046375B2 describes a computing system designed to monitor and predict hematocrit and hemoglobin levels in users based on their partial pressure of oxygen (PO2) levels. The system comprises a user device equipped with sensors to measure PO2 levels over time, alongside processors and a non-transitory computer-readable medium containing executable instructions. These instructions enable the device to collect PO2 data, generate historical PO2 information, and transmit this data to a personalized erythropoiesis model generation platform. This platform, which also includes processors and executable instructions, processes the received PO2 information along with individualized user data—such as previous hematocrit and hemoglobin measurements—to create a tailored erythropoiesis model. This model is utilized to predict future hematocrit and hemoglobin levels and to inform subsequent actions based on these predictions.
Additionally, the patent outlines methods for refining the individualized erythropoiesis model by incorporating mathematical models for oxygen dosing and analyzing low oxygen events experienced by the user. The system can generate future PO2 scenarios and determine optimal conditions for achieving desired hematocrit and hemoglobin levels. It also includes provisions for developing systematic training strategies based on the optimal future PO2 information, which can be displayed to the user. The patent emphasizes the iterative nature of the model, allowing for re-evaluation and adjustment based on new PO2 data, thereby enhancing the accuracy of predictions and personalized recommendations for users.
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