Abstract — Smart Dressing Sensor
China Prolonged chronic wound healing not only places great stress on patients but also increase the health care burden. Fortunately, the emergence of tissue-engineered dressings has provided a potential solution for these patients. Recently, the relationship between the wound microenvironment and wound healing has been gradually clarified. Therefore, the state of wounds can be roughly ascertained by monitoring the microenvironment in real time. Here, we designed a three-layer integrated smart dressing, including a biomimetic nanofibre membrane, microenvironment sensor and β-cyclodextrin-containing gelatine methacryloyl (GelMA + β-cd) UV-crosslinked hydrogel. The hydrogel helped increase the expression of vascular endothelial growth factor (VEGF) through hypoxia-inducible factor-1α (HIF-1α) to promote neovascularization and wound healing. The microenvironment sensor, combined with the biological dressings, exhibited satisfactory measurement accuracy, stability, durability and biocompatibility. A BLE4.0 antenna was used to receive, display and upload wound microenvironment data in real time. Such integrated smart dressings can not only achieve biological functions but also monitor changes in the wound microenvironment in real time. These dressings can overcome the challenge of not knowing the state of the wound during the healing process and provide support for clinical work.
Sensor Interfacing & Analog Front-End Conditioning
A poor local blood supply is a common feature of chronic wounds, which can have various causes ( Dinh and Veves, 2005 ; Chao and Cheing, 2009 ; Cahn et al., 2016 ). Therefore, determining how to promote wound angiogenesis to accelerate healing is a very important and challenging issue. Angiogenesis in wounds is a complex and multistep process that mainly occurs in the proliferation stage of healing, during which vascular endothelial cells (VECs) proliferate and form a neovascularization network through dynamic changes in shape and behavior. With the rapid development of material science and stem cell tissue engineering, active biological dressings have shown great potential in wound treatment ( Yang et al., 2014 ; Nurhasni et al., 2015 ; Peh et al., 2015 ; Shi et al., 2015 ). Biomedical hydrogels are one example of such dressings.
Bio-Signal Waveform Analysis & Simulation Findings
Compared with traditional dressings, biomedical hydrogels have obvious advantages in terms of, for example, antibacterial properties and biocompatibility ( Shevchenko et al., 2010 ). For example, biomedical hydrogels can better maintain the moist environment of the wound, and their more similar structure to that of the extracellular matrix (ECM) can provide scaffolds for cell adhesion and migration. The three-dimensional (3D) culture of cells based on a hydrogel matrix can better simulate the real ECM environment in vivo . Gelatine methacryloyl (GelMA) has high potential as a tissue engineering material because of its good biological properties and controllable physical properties, and GelMA hydrogels produced by UV crosslinking are widely used in the field of regenerative medicine ( Yue et al., 2015 ). The formation of vascular lumens by endothelial cells is a critical step in the angiogenic process that occurs during invasion and growth of the incipient vascular sprout ( Iruela-Arispe and Davis, 2009 ). Some researchers have used 3D printing technology to carve a lumen structure in GelMA hydrogels and found that these hydrogels could accelerate the proliferation and migration of VECs and promote wound neovascularization ( Lee and Mooney, 2001 ; Aubin et al., 2010 ; Nichol et al., 2010 ; Qi et al., 2010 ). Angiogenesis is a very complex process involving many factors. Vascular extracelluar matrix also plays an important role in the development of the functional circulation ( Davis et al., 2011 ). As a pharmaceutical excipient, β-cyclodextrin (β-cd) is widely used to increase cell permeability, thus increasing the uptake of small molecules such as glucose and nanoparticles. Recently, it has been found that β-cd can also adjust the physical and chemical properties of hydrogels and improve their biocompatibility ( Niu et al., 2018 ; Bezerra et al., 2020 ).
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 Smart Dressing Sensor 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