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Christian Poellabauer

Professor

Florida International University

United States

Research Interests

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About

Christian Poellabauer is an Associate Professor at Florida International University in the United States. His research areas encompass speech analysis for health monitoring, including concussion detection and Parkinson’s disease staging, as well as the application of machine learning in neurological disorders. He has contributed to various studies aimed at enhancing participant engagement and data quality in mental wellness and the use of digital health technology.

Articles (23)

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2023

Collaborators (7)

Dr Samaneh (Sam) Madanian

Associate Professor

University of Auckland

NEW ZEALAND

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Sandra Schneider

Professor

Saint Mary's College

UNITED STATES

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Ajit Narayanan

Professor

University of Auckland

NEW ZEALAND

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Abiy Tasissa

Tufts University

UNITED STATES

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John Michael Templeton

Assistant Professor

University of South Florida

UNITED STATES

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MEGAN OBRIEN

Shirley Ryan AbilityLab

UNITED STATES

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Ananda Mondal

Associate Professor

Florida International University

UNITED STATES

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Christian Poellabauer

Research Interests

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About

Articles (23)

Physiological Workload Estimation from Single-Lead ECG via Learnable Time–Frequency Representations

Speech-Based Concussion Detection Using CNNs: A Comparative Study of Acoustic Feature Representations for Digital Health Monitoring

Speech-based concussion detection in athletes using Mel-spectrograms and convolutional neural networks

Guided Clinical Reasoning with LLMs: Reconstructing the PHQ-9 from Multimodal Inputs

STEP-PD: Stage-Aware and Explainable Parkinson’s Disease Severity Classification Using Multimodal Clinical Assessments

Thesis Proposal: Stability-Aware, Evidence-Grounded Knowledge Graph for Substance Use Disorders and Social Determinants of Health

SCOPE-PD: Explainable AI on Subjective and Clinical Objective Measurements of Parkinson's Disease for Precision Decision-Making

Clinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders

Modernizing the Staging of Parkinson Disease Using Digital Health Technology

Exploring Speech Biosignatures for Traumatic Brain Injury and Neurodegeneration: Pilot Machine Learning Study

A Proof-of-Concept Development on Speech Analysis for Concussion Detection

Participant Engagement and Data Quality: Lessons Learned from a Mental Wellness Crowdsensing Study

A multi-dilated convolution network for speech emotion recognition

Reliable peak detection and feature extraction for wireless electrocardiograms

A Comprehensive Multifunctional Approach for Measuring Parkinson's Disease Severity

Identification of Persons Based on Electrocardiogram and Motion Data

Prediction of the Power of Low-Power Networks Using Inertial Sensors

MADSurv: An Uncertainty-Aware Framework for Multimodal Cancer Survival Analysis

Biometrics for Wearable Devices

GPS and Smartphone Technology for Real-World Measurement of Community Mobility in Healthcare

Actor-Independent Emotion Recognition: A Transformer-Based Approach to Speech and Facial Feature Fusion

Identification of Deployment Environments Based on Link Quality Fluctuation Patterns

Beyond Motor Symptoms: Toward a Comprehensive Grading of Parkinson's Disease Severity

Collaborators (7)

Dr Samaneh (Sam) Madanian

Sandra Schneider

Ajit Narayanan

Abiy Tasissa

John Michael Templeton

MEGAN OBRIEN

Ananda Mondal

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