An Embedded Device for Real-Time Noninvasive Intracranial Pressure Estimation

Area of Science:

• Biomedical Engineering
• Medical Devices
• Neurology

Background:

• Intracranial pressure (ICP) monitoring is crucial for neurological conditions but current methods are invasive.
• Existing invasive ICP monitoring limits its application to critically ill patients.
• There is a need for accessible, noninvasive ICP monitoring solutions.

Purpose of the Study:

• To develop and test an embedded device for real-time noninvasive ICP (nICP) estimation.
• To implement a model-based approach using cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) waveforms.
• To create a portable, low-cost device for nICP estimation.

Main Methods:

• An nICP estimation algorithm and preprocessing steps were implemented on an NXP LPC4337 microcontroller unit (MCU).
• A prototype device was developed with display, recording, and peripheral interfaces for ABP and CBFV sensors.
• The device performs computations in real-time for nICP estimation.

Main Results:

• The device provides mean ICP estimates approximately once per minute.
• Real-time computations are completed within 410 ms on average.
• The root-mean-square error between real-time and batch-mode estimates was 0.63 mmHg.

Conclusions:

• Real-time nICP estimation is feasible on a microprocessor platform.
• The developed device offers advantages of low cost, small size, and modularity.
• This technology advances the goal of bedside nICP monitoring in diverse clinical environments.