Abstract — Intracranial Pressure Monitor
experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The accurate monitoring of vital physiological parameters, exemplified by heart rate, respiratory rate, and intracranial pressure (ICP), is of paramount importance, particularly for managing severe cranial injuries. Despite the rapid development of implantable ICP sensing systems over the past decades, they still suffer from, for example, wire connection, low sensitivity, poor resolution, and the inability to monitor multiple variables simultaneously. Here, we propose an ultrasensitive multimodal biotelemetric system that amalgamates an iontronic pressure transducer with exceptional point (EP) operation for the monitoring of ICP signals. The proposed system can exhibit extraordinary performance regarding the detection of minuscule ICP fluctuation, demonstrated by the sensitivity of 115.95 kHz/mmHg and the sensing resolution down to 0.003 mmHg. Our system excels not only in the accurate quantification of ICP levels but also in distinguishing respiration and cardiac activities from ICP signals, thereby achieving the multimodal monitoring of ICP, respiratory, and heart rates within a single system. Our work may provide a pragmatic avenue for the real-time wireless monitoring of ICP and thus hold great potential to be extended to the monitoring of other vital physiological indicators.
Sensor Interfacing & Analog Front-End Conditioning
Traumatic brain injury (TBI) represents a critical global health challenge, emerging as one of the primary pathogenes to mortality and morbidity in modern society 1 . Intracranial pressure (ICP), which reflects the balance among brain tissue, cerebral blood volume, and cerebrospinal fluid within the skull, is one of the key diagnostic parameters for TBI management 2 . Anomaly-increased ICP is the most common cause of death in patients having severe TBI 3 due to compromised cerebral blood flow, brain ischemia, inflammation, secondary neurovascular damage, and brain herniation 4 . This indeed necessitates swift intervention to mitigate risks such as brainstem compression and compromised brain circulation 3 . Consequently, precise and continuous monitoring of brain physiological parameters is imperative to prevent irreversible damage to TBI patients 5 .
Bio-Signal Waveform Analysis & Simulation Findings
Figure 1: Diagnostic Medical Waveform & Bio-Potential Clinical Trace for Intracranial Pressure Monitor Present ICP monitoring in clinics predominantly relies on the implanting of intraventricular catheters 6 . However, this approach is fraught with drawbacks, including restricted patient mobility due to wire connections (catheters) and heightened risks of complications like infection and hemorrhage, which may further worsen brain damage or result in new neurological disorders 7 . Although various non-invasive systems have been developed 8 , 9 , 10 in the recent past, their effectiveness has been compromised by the ICP range, rendering them inadequate for use alone in patients with severe TBI 11 , 12 .
Scope & Clinical Applications
- Real-time multi-parameter vital signs telemetry (ECG, Heart Rate, SpO2, Temperature, Respiration)
- Low-noise Analog Front-End (AFE) conditioning with active Driven Right Leg (DRL) 50 Hz cancellation
- Digital signal processing in MATLAB: Pan-Tompkins QRS detection, FIR/IIR notch, and Continuous Wavelet Transforms
- Finite element tissue bio-electromagnetics and orthopedic mechanical simulations in COMSOL & ANSYS
- Complete Arduino firmware .INO sketches, circuit schematics, and university dissertation reports
Bio-Potential Sensors
ECG, EEG, EMG & PPG optical probes
Low-Noise AFE
INA128 / AD8232 instrumentation amps
Arduino Firmware
Real-time ADC interrupt sampling & BLE
MATLAB Bio-DSP
Pan-Tompkins QRS & wavelet transforms
COMSOL Multiphysics
Tissue electro-thermal & SAR simulation
IEC 60601-1 Safety
Galvanic optical & magnetic isolation
Biomedical Sensors, Electronics & Simulation Suites
Engineered using clinical-grade bio-transducers, low-noise analog amplifiers, and multi-physics simulation platforms.
| Subsystem / Software | Diagnostic & Engineering Role | Instrumentation Tier |
|---|---|---|
| Arduino / ESP32 MCU | High-speed SPI/I2C sensor polling, 500 Hz timer interrupt ADC sampling, BLE telemetry streaming | Embedded Hardware |
| MATLAB R2024b | Pan-Tompkins QRS detection, 50 Hz Butterworth notch filtering, wavelet decomposition, SpO2 ratio | Signal Analytics |
| COMSOL Multiphysics | Electromagnetic tissue absorption (SAR), bio-heat thermal transfer, acoustic transducer wave propagation | Tissue Physics |
| ANSYS Mechanical | Orthopedic bone-implant contact mechanics, prosthetic socket stress distribution, dental load FEA | Biomechanics FEA |
| AD8232 / ADS1298 AFE | Medical-grade 3-lead ECG front-end with built-in instrumentation amp, DRL feedback, and high CMRR | Clinical AFE IC |
Biomedical Acquisition & Multi-Physics Simulation Workflow
Comprehensive signal flow from human bio-potential electrodes and optical sensor probes to embedded Arduino firmware, MATLAB DSP, and COMSOL tissue modeling.
(ECG/EEG/PPG/Temp)
(INA128 / DRL Loop)
500Hz ADC Sampling
& QRS Detection
Tissue FEA Models
& EHR Dashboard
Verified Medical Waveforms, Diagnostic Images & Sensor Circuits
Advantages of the Intracranial Pressure Monitor Project
Why this biomedical engineering project delivers superior academic grades and provides high technical evaluation standing.
Clinical Diagnostic Precision
Combines high-CMRR analog front-ends with precision digital filtering to extract microvolt bio-potentials with high SNR (> 35 dB).
Rigorous IEC 60601-1 Patient Safety
Incorporates dual galvanic isolation barriers (optical/magnetic) ensuring patient auxiliary leakage currents remain strictly under 10 μA.
Multi-Sensor Vital Signs Fusion
Simultaneously captures ECG, PPG, SpO2, Core Temperature, and Respiration for comprehensive physiological health monitoring.
Real-Time Arduino Embedded Firmware
Features optimized C++ interrupt-driven ADC sampling routines ready for immediate deployment on Arduino, ESP32, and STM32.
Validated Pan-Tompkins QRS Algorithm
Executes derivative, squaring, moving-window integration, and dual-threshold peak detection with > 99% R-peak accuracy.
COMSOL & ANSYS Multi-Physics Coupling
Models complex anatomical tissue structures, bio-electromagnetic Specific Absorption Rates (SAR), and prosthetic stress fields.
Driven Right Leg (DRL) Noise Suppression
Actively senses and neutralizes 50/60 Hz powerline hum and common-mode displacement currents without loading patient electrodes.
DICOM Medical Imaging Pipeline
Processes clinical MRI, CT, and Ultrasound scans using MATLAB contrast enhancement and morphological lesion boundary segmentation.
Direct Telehealth & Hospital IoT Readiness
Streams validated vital signs to mobile dashboards and electronic health records over encrypted BLE and MQTT protocols.
Complete Turnkey Project Package
Delivered with full Arduino .INO sketches, circuit schematics, MATLAB .m algorithms, university-format report, and viva defense slides.
Sample Arduino Firmware, ECG Waves & Sensor Telemetry
Representative excerpts illustrating the embedded sensor acquisition loop, live physiological waveform traces, and clinical parameter schedules.
[*] Initializing Analog Front-End (AFE) Signal Acquisition... [✓] Driven Right Leg (DRL) Active Feedback: 50 Hz Hum Attenuated by 42 dB ──────────────────────────────────────────────────────────────────────── [10:14:02.102] TRACE ECG Lead-II: ---__/\_/\_/\___ (Baseline: 0.02 mV | Normal ST Segment) [10:14:02.115] QRS R-Peak Registered (Fiducial Trigger: 1.24 mV | R-R Interval: 832 ms) [10:14:02.128] VITALS Heart Rate: 72.1 BPM | SpO2: 98.5% | PR Interval: 156 ms [10:14:02.140] TRACE ECG Lead-II: ---__/\_/\_/\___ (Baseline Stable | SNR = 36.8 dB) ──────────────────────────────────────────────────────────────────────── [✓] Diagnostic Evaluation: Sinus Rhythm Verified. Zero Ectopic Ventricular Beats.
[*] Synchronizing vital signs telemetry stream across bio-sensor channels...
| Physiological Parameter | Primary Transducer | Measured Amplitude | Sampling Bandwidth | Clinical Status |
|---|---|---|---|---|
| Cardiac Electrocardiogram (ECG) | Ag/AgCl + AD8232 AFE | 1.24 mV (R-Peak) | 0.05 Hz - 150 Hz | NORMAL SINUS |
| Pulse Oximetry (SpO₂) | MAX30102 Dual Red/IR | 98.5% Saturation | 100 Hz Optical | OPTIMAL |
| Heart Rate (HR) | R-R Peak Derivative | 72.1 BPM | 30 - 220 BPM range | EUKINETIC |
| Core Body Temperature | NTC Medical Thermistor | 36.8 °C | 0.1 Hz Thermal | AFEBRILE |
[✓] Diagnostic Evaluation: Patient physiological parameters within verified clinical tolerance band.
Frequently Asked Questions
Project Deliverables & Support
Everything needed from project inception to final viva defense — delivered with expert biomedical support.
.INO Sketches
Schematics
Algorithms
Report
Slides
Models
Datasets
Q&A
Support
Extension