An Artificial Intelligence model for smart post-stroke assessment using wearable sensors
Author:
Publisher
Elsevier BV
Subject
Modeling and Simulation,Applied Mathematics,Analysis,General Decision Sciences
Reference73 articles.
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2. Wearable sensors and machine learning in post-stroke rehabilitation assessment: A systematic review;Boukhennoufa;Biomed. Signal Process. Control,2022
3. Hand Extension Robot Orthosis (HERO) Grip Glove: enabling independence amongst persons with severe hand impairments after stroke;Yurkewich;J. Neuroeng. Rehabil.,2020
4. Heart disease and stroke statistics—2022 update: A report from the American heart association;Tsao;Circulation,2022
5. Handbook of Clinical Nutrition and Stroke;Corrigan,2013
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1. PSA-FL-CDM: A Novel Federated Learning-Based Consensus Model for Post-Stroke Assessment;Sensors;2024-08-06
2. Artificial intelligence and multimodal data fusion for smart healthcare: topic modeling and bibliometrics;Artificial Intelligence Review;2024-03-15
3. An Investigation into the Rise of Wearable Technologies in the Healthcare Sector;Lecture Notes in Computer Science;2024
4. Refined movement analysis in the Staircase test reveals differential motor deficits in mouse models of stroke;2023-10-23
5. AI in Sensor Research: A Reality Check and the Underestimated Potential of ChatGPT;ACS Sensors;2023-06-15
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