Company: PFSA
Filing Date: 2025-10-29
Form Type: 424B3
Source: 0001213900-25-103174
Chunk: 192

Company: Profusa, Inc.
Filing Date: 2025-10-29
Form: 424B3
Chunk 192
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 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-detector pairs. The reader position and tissue absorptions
are computed by fitting the measurements to a principle-based optical 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-learning models 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-series data 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-bit encryption 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.

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| ● | App and Data Visualization |

Lumee Oxygen includes a tablet device
that is designed to provide real-time traces 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