Faculty

Institution

Unit

Venue

Mohammad Ghamari

Assistant Professor

Kettering University

Affiliations

College of Engineering

Department of Electrical and Computer Engineering

Mohammad Ghamari is currently serving as a College Of Engineering Assistant Professor at Kettering University.

Honors

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Experiences

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Education

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Mohammad Ghamari

Kettering University

Assistant Professor

You can click a keyword to filter the displayed items

physiological measurements systems engineering biosignal processing deep learning health sciences neural network (machine learning) health monitoring wireless communications patient monitoring ppg signals computer engineering sensors stress (biology) biomedical engineering wearable technology predictive analytics health technology stress biomarkers blood pressure wireless sensor networks digital health telecommunication networks circulatory physiology body area network communication engineering wavelet theory prediction modelling vascular aging vehicular technology digital medicine cardiovascular research mobile computing diabetes technology diabetes care wearable sensors particulate matter advanced driver-assistance system vehicle communication channel access method diversity techniques blood glucose monitoring real-time stress detection vascular age biomedical circuits wireless personal communication information technology laboratory investigation environmental technology wearable biosensors smart health mobile health connected health radio access protocol mobile communication wireless lan wearable systems wireless implantable devices medical technology sensor signal processing sensor design sensor technology nanobiotechnology nanosensors wearable photoplethysmography sensors potential future applications residential environments ehealthcare systems civil applications detailed examination packet collision model wearable health-monitoring applications non-invasive blood glucose deep cnn-mlp network stress assessment field evaluation stress detection model internet of things embedded machine learning

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Dilated CNN‐Based Model for Stress Detection Using Raw Ppg Signals. IET Wireless Sensor Systems (2025)

stress biomarkersstress (biology)

Contactless Health Monitoring: An Overview of Video‐Based Techniques Utilising Machine/Deep Learning. IET Wireless Sensor Systems (2025)

computer sciencehuman monitoringhealth monitoringdigital healthcomputer visiondeep learninghealth technologydata sciencedigital medicineremote patient monitoringcontactless health monitoring

Cuff-Less Blood Pressure Monitoring via Ppg Signals Using a Hybrid CNN-Bilstm Deep Learning Model With Attention Mechanism. Scientific Reports (2025)

attention mechanismdeep learningneural network (machine learning)blood pressureppg signalshypertension

Dynamic Event-Triggered Bipartite Consensus for Nonlinear Systems Using a Fuzzy Observer. (2025)

state observerfuzzy observersystems engineeringautomatic controlnonlinear systemsobserver patternfuzzy systemscontrol systemsdistributed control systemsnonlinear dynamicsstabilitydiscrete event systemsdynamical systems

Exploring the Potential of Five Machine Learning Regression Algorithms for Noninvasive Blood Pressure Estimation With Photoplethysmography. Health Informatics Journal (2025)

machine learning toolsbiostatisticspredictive analyticsbiosignal processingmachine learningpatient monitoringphysiological measurementsmachine learning researchdata scienceblood pressureregression algorithmsprediction modellingstatistics

Implementation of an Optimized Deep Learning Model to Assess Pediatric Sleep Apnea Severity Using Spo2 Signals on Resource-Limited Microcontrollers. (2025)

biostatisticspediatricssleep medicinepediatric pulmonologydeep learningsleepneural network (machine learning)sleep-related breathing disordersresource-limited microcontrollers

Koopman Operator-Based Linearization for Formation Control of Wheeled Mobile Multi-Agent Systems. (2025)

swarm roboticssystems engineeringautomatic controlnonlinear systemsdistributed roboticskoopman operator-based linearizationmultirobot systemcontrol systemsswarm intelligenceformation controlmultiagent systemsrobotics

Multimodal Signal Fusion for Stress Detection Using Deep Neural Networks: A Novel Approach for Converting 1D Signals to Unified 2D Images. Signal Image and Video Processing (2025)

medical image computingconvolutional neural networksdeep neural networksdeep learningfusion learningneural network (machine learning)digital image processingimage representationmultimodal signal fusionstress detectionmultimodal signal processingfeature fusion

Noninvasive Assessment of Arterial Stiffness Using Photoplethysmography: Feature Analysis and Machine Learning-Based Estimation of Carotid-Femoral Pulse Wave Velocity. IEEE Access (2025)

biostatisticscardiovascular diseasenoninvasive assessmentcirculatory physiologybiosignal processingblood vesselsradiologykinesiologypatient monitoringfeature analysisphysiological measurementscardiovascular imagingblood flow measurementmachine learning-based estimation

Non-Invasive Blood Glucose Monitoring Using Ppg Signals With Various Deep Learning Models and Implementation Using Tinyml. Scientific Reports (2025)

sensorsdiabetes caredeep learningblood glucose monitoringbiosignal processingdiabetes technologyneural network (machine learning)non-invasive blood glucoseppg signalsdiabetes

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Mohammad Ghamari

Assistant Professor

Kettering University

Affiliations

College of Engineering

Department of Electrical and Computer Engineering

Mohammad Ghamari is currently serving as a College Of Engineering Assistant Professor at Kettering University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Mohammad Ghamari

Kettering University

Assistant Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Dilated CNN‐Based Model for Stress Detection Using Raw Ppg Signals. IET Wireless Sensor Systems (2025)

stress biomarkersstress (biology)

Contactless Health Monitoring: An Overview of Video‐Based Techniques Utilising Machine/Deep Learning. IET Wireless Sensor Systems (2025)

computer sciencehuman monitoringhealth monitoringdigital healthcomputer visiondeep learninghealth technologydata sciencedigital medicineremote patient monitoringcontactless health monitoring

Cuff-Less Blood Pressure Monitoring via Ppg Signals Using a Hybrid CNN-Bilstm Deep Learning Model With Attention Mechanism. Scientific Reports (2025)

attention mechanismdeep learningneural network (machine learning)blood pressureppg signalshypertension

Dynamic Event-Triggered Bipartite Consensus for Nonlinear Systems Using a Fuzzy Observer. (2025)

Exploring the Potential of Five Machine Learning Regression Algorithms for Noninvasive Blood Pressure Estimation With Photoplethysmography. Health Informatics Journal (2025)

Implementation of an Optimized Deep Learning Model to Assess Pediatric Sleep Apnea Severity Using Spo2 Signals on Resource-Limited Microcontrollers. (2025)

biostatisticspediatricssleep medicinepediatric pulmonologydeep learningsleepneural network (machine learning)sleep-related breathing disordersresource-limited microcontrollers

Koopman Operator-Based Linearization for Formation Control of Wheeled Mobile Multi-Agent Systems. (2025)

Multimodal Signal Fusion for Stress Detection Using Deep Neural Networks: A Novel Approach for Converting 1D Signals to Unified 2D Images. Signal Image and Video Processing (2025)

Noninvasive Assessment of Arterial Stiffness Using Photoplethysmography: Feature Analysis and Machine Learning-Based Estimation of Carotid-Femoral Pulse Wave Velocity. IEEE Access (2025)

Non-Invasive Blood Glucose Monitoring Using Ppg Signals With Various Deep Learning Models and Implementation Using Tinyml. Scientific Reports (2025)

sensorsdiabetes caredeep learningblood glucose monitoringbiosignal processingdiabetes technologyneural network (machine learning)non-invasive blood glucoseppg signalsdiabetes

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10 / page

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Similar Faculty Members

Christopher Paolini

Institution

San Diego State University

internet of things

intelligent computing

Hamed Tabkhi

Institution

University of North Carolina at Charlotte

edge computing

field programmable gate array

Iraklis Anagnostopoulos

Institution

Southern Illinois University Carbondale

computer engineering

hardware architecture

Hui Guan

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University of Massachusetts Amherst

machine learning tool

learning classifier system

Shuguang Robert Cui

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University of California, Davis

industrial informatics

big data

Ganapati Bhat

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Washington State University

systems engineering

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Tao Han

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New Jersey Institute of Technology

edge computing

intelligent network

Chengmo Yang

Institution

University of Delaware

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industrial automation

Josiah Hester

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pervasive computing

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Texas A&M University

electrical engineering

systems engineering