Tu.P5.F-5
ARTIFICIAL INTELLIGENCE DRIVEN STROKE ASSESSMENT USING PHOTOPLETHYSMOGRAPHIC BIOSIGNALS
Rafita Haque, Armando Barreto, Malek Adjouadi, Florida International University; Chunlei Wang, Nezih Pala, University Of Miami
Session:
Tu.P5: Wearable and Contactless Monitoring and Analysis Poster
Track:
Biomedical Signal Processing
Location:
Hall E; Bay F, Board #5
Presentation Time:
Tuesday, 28 July, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session Tu.P5
Tu.P5.F-1: AAN-RPPG: A CLINICALLY VALIDATED PIPELINE WITH ADAPTIVE AMPLITUDE NORMALIZATION FOR ROBUST HEART RATE ESTIMATION
Hyunmin Lee, Seunghyun Ryu, Kibum Park, Guiyeom Kang, GBSoft Inc.
Tu.P5.F-2: A Multi-Sensor Wearable System for Quantifying Sleep Quality and Circadian Disruption in Shift Workers
Shivank Bhatia, Dhirubhai Ambani International School; Nikunj Parikh, OnMyOwntechnology
Tu.P5.F-3: Non-contact Heart Rate Estimation via Multi-view Spatiotemporal Compression Representation and Swin Transformer
Xiantai Jiang, Southern University of Science and Technology; Peixi Wu, Zijing You, Guanglin Li, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Zhiyu Tang, School of Electrical Engineering and Computer Science, Faculty of Architecture and Information Technology,The University of Queensland Brisbane; Nan Lou, University of Hong Kong Shenzhen Hospital; Yanan Diao, Guoru Zhao, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences
Tu.P5.F-4: Characterizing Negative Emotions Through Temporal Autonomic Coordination in Virtual Reality
Maria Mura, Elisa Facchini, Edoardo Maria Polo, Politecnico di Milano; Davide Ferraris, Lega Italiana Per La Lotta Contro I Tumori – LILT; Cristian Drudi, Riccardo Barbieri, Politecnico di Milano
Tu.P5.F-5: ARTIFICIAL INTELLIGENCE DRIVEN STROKE ASSESSMENT USING PHOTOPLETHYSMOGRAPHIC BIOSIGNALS
Rafita Haque, Armando Barreto, Malek Adjouadi, Florida International University; Chunlei Wang, Nezih Pala, University Of Miami
Tu.P5.F-6: CONTEXT-WEIGHTED, PERSON-SPECIFIC GESTURE SET SELECTION FOR CLASSIFICATION IN WEARABLE INTERFACES
Sudhir Zhuwawu, Mahonri Owen, Albert Bifet, Anany Dwivedi, University of Waikato
Tu.P5.F-7: SKIN-CONTACTLESS EMBEDDED SLEEP STAGE CLASSIFICATION SYSTEM
Adrien Thirion, Alexandra Haim, LAAS-CNRS, CNRS, Institut National Polytechnique de Toulouse, Univ. de Toulouse, Nanomade Lab; Hélène Tap, Blaise Mulliez, LAAS-CNRS, CNRS, Institut National Polytechnique de Toulouse, Univ. de Toulouse; Nicolas Dufour, Nanomade Lab
Tu.P5.F-8: KNEE INJURY RISK ESTIMATION USING DEEP LEARNING AND LARGE LANGUAGE MODELS (LLMS)
Oussama Messai, Dawood Al Chanti, Julien Frère, University Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, Grenoble, France
Tu.P5.F-9: EMBEDDING-BASED REPRESENTATION LEARNING FOR PERSONALIZED STRESS ASSESSMENT FROM WEARABLE TIME SERIES
Laura Ginestretti, Susanna Bardini, Sara Varone, Angelo Guarnerio, Marco Domenico Santambrogio, POLITECNICO DI MILANO
Tu.P5.F-10: UNSUPERVISED MORPHOLOGICAL LIBRARY CONSTRUCTION FOR SCALABLE PPG SIGNAL QUALITY MONITORING
Rémi Dagenais, McGill University; Joanna Sulkowska, University of Oslo; Junqi Wang, McGill University; Ulysse Côté-Allard, University of Oslo; Georgios Mitsis, McGill University
Tu.P5.F-11: A MULTI-STAGE MACHINE LEARNING FRAMEWORK FOR SMARTPHONE LOCATION RECOGNITION IN UNSUPERVISED MOTOR ASSESSMENT
Óscar Reyes, Indivi Technologies SL; Claudia Mazzà, Indivi AG; Andrea Cereatti, Politecnico di Torino; Emmanuel Bartholomé, Corrado Bernasconi, Shibeshih Belachew, Indivi AG
Tu.P5.F-12: FedSCS-XGB - Federated Server-centric surrogate XGBoost for continual health monitoring
Felix Walger, Chair of Information Theory and Data Analytics, RWTH Aachen University; Mehdi Ejtehadi, Spinal Cord Injury Artificial Intelligence (SCAI) Lab, ETH Zürich & Swiss Paraplegic Research (SPF); Anke Schmeink, Chair of Information Theory and Data Analytics, RWTH Aachen University; Diego Paez-Granados, Spinal Cord Injury Artificial Intelligence (SCAI) Lab, ETH Zürich & Swiss Paraplegic Research (SPF)
Tu.P5.F-13: WAKE/SLEEP CLASSIFICATION VIA A LABEL-EFFICIENT CONTRASTIVE LEARNING APPROACH
Safa Boudabous, Université Paris-Dauphine PSL; Juliette Millet, Mitral; Emmanuel Bacry, Université Paris-Dauphine PSL
Tu.P5.F-14: FROM IDENTIFIABILITY TO INVARIANCE: LEARNING PHYSIOLOGICAL REPRESENTATIONS FROM CARDIOVASCULAR DYNAMICS
Junqi Wang, Le Chen, McGill University; Roberta Saputo, University of Palermo; Rémi Dagenais, Ronald Schondorf, Georgios Mitsis, McGill University
Tu.P5.F-15: PRELIMINARY COMPARISON OF MULTI-LEVEL MECHANICAL AND THERMAL STIMULATION RESPONSE VIA EDA
Riley McNaboe, Amelia Plant, Lena Boldi, Camila Jimenez-Wong, Hugo Posada-Quintero, University of Connecticut
Tu.P5.F-16: Circadian Rhythms Using Ingestible IMUs
Ceara Byrne, MIT; Xintong Tong, Soft Transducers Lab (LMTS); Siheng You, Kristel Acuña García, MIT; Sophia You, Princeton University; Aaruni Arora, Imperial College London; Ian Ballinger, Adam Gierlach, Yubin Cai, Vicky Perepelook, MIT; Andrew Pettinari, University of Michigan; Benedict Laidlaw, Ashley Guevara, Maria Platero, Niora Fabian, Alison Hayward, Giovanni Traverso, MIT
Tu.P5.F-17: TIME-SERIES SEGMENTATION IN CLASSIFICATION OF ACTIVITIES OF DAILY LIVING FOR LONG-TERM HEALTH MONITORING
Mehdi Ejtehadi, André Muff, ETH Zurich & Swiss Paraplegic Research (SPF); Robert Riener, ETH Zurich & Balgrist University Hospital; Diego Paez-Granados, ETH Zurich & Swiss Paraplegic Research (SPF)
Resources
No resources available.