01
Physiological Sensing
PPG acquisition and preprocessing, physiological feature extraction, cuffless blood-pressure and respiratory-rate estimation, and signal-quality reasoning.
Biomedical Engineering Researcher
Huriye Sadat
Huriye Sadat
Sadeghi
Physiological sensing, PPG, AI-assisted health monitoring, and embedded medical systems — connecting signals, hardware, modeling, and clinically responsible validation.
VISUAL ACADEMIC PROFILE
Research at a glance
Academic profile · August 2026Click to enlarge
Physiological SensingPPG AnalysisAI for HealthcareEmbedded Medical SystemsDigital Health
RESEARCH IDENTITY
Engineering ideas into testable health systems.
My strongest demonstrated work connects physiological sensing, signal/data analysis, embedded implementation, machine learning, and careful validation in one end-to-end workflow.
SensePPG · MAX30102 · physiological signals
InterpretFiltering · landmarks · feature extraction
ModelRandom Forest · evaluation · MATLAB
DeployESP32 · alerts · logging · communication
02
AI for Healthcare
Random Forest regression, comparative ML workflows, clinical outcome prediction, intelligent monitoring, model evaluation, and decision-support concepts.
03
Embedded Medical Systems
ESP32-based prototyping, embedded C/C++, LCD and MicroSD integration, real-time timing, SIM808 GSM/GPS, and systematic sensor/circuit debugging.
04
Wearable & Digital Health
Vital-sign monitoring, remote monitoring concepts, intelligent alerting, Medical IoT, clinically responsible translation, and future miniaturization.
18.0/20M.Sc. GPA
1stM.Sc. cohort rank
1st authorScientific Reports publication
17 / 170participants / samples in thesis dataset
RESEARCH OUTPUT
Publications & research in progress.
A focused publication record centered on wearable physiological monitoring, with an adjacent collaboration in computational optimization.
01
Design and prototyping of an AI-powered wearable device for continuous vital signs monitoring with intelligent alerting
First-author output from the M.Sc. research, linking physiological sensing, embedded implementation, data analysis, debugging, and scientific writing.
View DOI ↗02
Olympic Champion Algorithm (OCA): A new human-inspired metaheuristic algorithm for solving optimization problems
Secondary collaboration with contribution centered on review/editing, data collection, and supporting implementation/debugging tasks.
View DOI ↗03
Review manuscript on wearable physiological monitoring
Ongoing review work extending the M.Sc. direction toward wearable sensing technologies, AI, validation, and future digital-health translation.
FLAGSHIP RESEARCH
AI-powered physiological monitoring prototype.
A build-oriented M.Sc. project that moved from concept to functioning laboratory proof-of-concept — integrating sensing, embedded software, PPG feature extraction, machine learning, storage, alerting, and emergency communication.
MAX30102ESP32PPGRandom ForestSMS/GPS
SENSORMAX30102fingertip PPG
→
PROCESSESP32acquire · integrate
→
MODELRF → equationsSBP · DBP · RR
LCDMicroSDAlertsSIM808
From optical signal to physiological features
Red/infrared sensing at 100 Hz, noise reduction using moving-average and Kalman filtering, and extraction of four waveform landmarks: foot, systolic peak, notch, and diastolic peak.
Random Forest with embedded trade-offs
Regression models were developed in MATLAB for SBP, DBP, and respiratory-rate estimation. Learned relationships were then translated into simplified quadratic expressions for microcontroller execution.
Cross-layer troubleshooting
Unstable readings were investigated across sensor, circuit, I²C communication, code, and data layers. The logic-level/pull-up arrangement was corrected to improve signal stability.
Proof-of-concept, not overclaiming
The study used 17 volunteers and 170 samples with a random 80/20 split. The prototype was fingertip-interfaced, not wrist-worn, and broader participant-wise and clinical validation remain future work.
SELECTED PROJECTS
Beyond the thesis.
Clinical Outcome Prediction
COVID-19 mortality and pediatric respiratory length-of-stay prediction using clinical/laboratory features, dimensionality reduction, and comparative machine-learning models.
Biomedical Monitoring & Wireless Communication
Arduino/Proteus projects involving Wi-Fi, Bluetooth, GPS, EEG-related workflows, and heart-rate analysis with hardware-software integration and verification.
Physiological Systems Modeling
MATLAB/Simulink electrical models of the eye, heart, blood vessels, muscle, knee, respiratory system, and circulatory responses.
Healthcare Optimization & Activity Recognition
Projects on radiotherapy dose-distribution optimization, bioimplant design/material selection, and CNN hyperparameter optimization for sensor-based human-activity recognition.
TRAJECTORY
Research, clinical practice & teaching.
2022–2025
Graduate Researcher — AI-Powered Physiological Monitoring Prototype
Department of Medical Physics & Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences.
End-to-end hardware/software integration, PPG analysis, ML modeling, debugging, data analysis, and manuscript development.
Apr–Jul 2024
Clinical Engineering Intern — Imam Hossein Hospital
Hands-on exposure to ventilators, autoclaves, electrosurgical units, neonatal cribs, defibrillators, patient monitors, and incubators.
2018–2020
Technical & Operations Staff — Danesh Baft Alborz Bioimplant Co.
Supported bioimplant production and quality assurance, documentation, registration-related activities, and cross-functional operations.
TEACHING & COMMUNICATION
Teaching as part of the research identity.
TA
Medical InstrumentationShahid Beheshti University of Medical Sciences · 2023–2024
TA
Medical Equipment Technology & Safety StandardsShahid Beheshti University of Medical Sciences · 2023–2024
EDU
Private Tutor — Mathematics & PhysicsProblem-solving and competition preparation · 2017–2020
EDU
Educational Consultant & Mathematics InstructorGhalamchi Cultural Institute · 2013–2015
HONORS & ACADEMIC SIGNALS
Evidence of sustained performance.
#1
Ranked 1st in the M.Sc. Biomedical Engineering — Bioelectric cohort.
#13
Ranked 13th in Iran's graduate entrance examination for Medical Engineering (Bioelectric Engineering).
Top 1%
Iran national B.Sc. entrance examination, among 162,879 candidates.
2nd
University Swimming Competitions.
TECHNICAL STACK
Signals, models, embedded systems — and the tools around them.
Strongest direct evidence comes from MATLAB-based analysis/modeling and hands-on embedded implementation; supporting tools are presented at an appropriately calibrated level.
PPG AcquisitionPhysiological Feature ExtractionMATLABESP32MAX30102Random ForestBiomedical InstrumentationSimulinkPythonEmbedded C/C++Arduino IDEProteusAltium DesignerLCD IntegrationMicroSDSIM808 GSM/GPSDS3231 RTCI²C DebuggingWi-Fi / Bluetooth / GPSMAE · RMSE · R² · MAPEScientific WritingLiterature ReviewData Visualization
FUTURE RESEARCH AGENDA
From proof-of-concept toward robust, clinically meaningful systems.
Doctoral research is the next step for strengthening generalization, validation rigor, wearability, and responsible translation.
Robust PPG under motion
Signal-quality assessment, artifact suppression, and robustness evaluation beyond controlled measurements.
Participant-wise validation
Participant-level splits, external cohorts, subgroup analysis, and clinically meaningful generalization.
Personalized cuffless BP/RR
Calibration, adaptive modeling, uncertainty-aware estimation, and individualized physiological relationships.
Multimodal sensing
Accelerometer, gyroscope, and environmental sensing for context awareness and artifact handling.
Miniaturized wearables
Lower-power hardware, BLE, edge intelligence, smaller footprint, and a true wrist-worn form factor.
Clinically responsible digital health
Personalized alerts, false-alarm reduction, secure data sharing, telehealth integration, and workflow compatibility.
ACADEMIC REFERENCES
Research supervision & academic mentorship.
MA
Dr. Mohsen Ahmadi
M.Sc. Thesis Advisor · Assistant Professor, Faculty of Medical Engineering, SBMU
PS
Prof. Pezhman Sasanpour
M.Sc. Thesis Advisor · Professor, Faculty of Medical Engineering, SBMU
RS
Dr. Reza Shahghadami
M.Sc. Thesis Referee & Course Professor · Assistant Professor, Faculty of Medical Engineering, SBMU
Contact details are available in the downloadable academic CV.
OPEN TO PhD & RESEARCH OPPORTUNITIES
Interested in research where sensing, AI, and embedded engineering meet human health.
Especially interested in physiological sensing, PPG, wearable/digital health, AI for healthcare, embedded medical systems, remote monitoring, and rigorous validation.
Tehran, IranPersian · NativeEnglish · Academic working proficiencyTOEFL iBT mock · 91/120