Company: PFSA
Filing Date: 2025-08-25
Form Type: 424B3
Source: 0001213900-25-080387
Chunk: 175

Company: Profusa, Inc.
Filing Date: 2025-08-25
Form: 424B3
Chunk 175
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 intensity, tissue optical properties, and position of the sensor. The hardware and firmware in the glucose system capture and store these raw measurements. The data processing on the glucose system is performed primarily on a mobile device. The mobile application computes glucose intensity changes and calibrates the values to establish a measurement of blood glucose. The glucose algorithm in the mobile application is designed to perform a series of corrections to account for changes in the optical signals that do not originate in the glucose dye. These include correcting for variability in the LED brightness at different temperatures; correcting for changes in the reader’s position relative to the sensor, by triangulating the position of the sensor using 4 opposing LEDs that excite the reference dye; and correcting for changes in the tissue’s light absorption using 72 source -detectorpairs. The reader position and tissue absorptions are computed by fitting the measurements to a principle -basedoptical model. Finally, the glucose signal intensity is corrected for temperature changes to account for the glucose dye’s sensitivity to temperature. The corrected optical glucose signal is calibrated into a measurement of blood glucose. Profusa’s calibration model includes support for different user calibration schemes. Profusa has also developed a collection of machine -learningmodels which use these same optical signals as inputs to improve corrections. These machine learning models include using the tissue optical property measurements as inputs to generate background fluorescence, a deep learning model which uses all the optical signals to generate a blood glucose estimate, and machine learning models to detect signal errors. Additionally, in conjunction of work with DARPA, Profusa developed machine learning models that operate over time -seriesdata to detect specific events. Both the glucose and oxygen systems have firmware and Bluetooth low energy (BLE) hardware designed to communicate between the reader and the mobile device. The mobile device is initially paired with the reader using a passkey and later utilizes 128 -bitencryption for data transmission. The reader identifies if the connection between the reader and the mobile device is disconnected. It retains the data and transmits the data once the connection is re -established. The mobile device also notifies the user if a disconnection occurs. • App and Data Visualization Lumee Oxygen includes a tablet device that is designed to provide real -timetraces of tissue oxygen levels from multiple readers simultaneously, and allow the operator to annotate events and normalize values at a point in time to identify the relative improvement of a patient’s tissue oxygen. The system also supports PDF and CSV data export. Profusa has also developed Lumee O2 Go, currently for research use only, that operates