Data Processing and Machine Learning for Assistive and Rehabilitation Technologies

This Special Issue (SI), “Data Processing and Machine Learning for Assistive and Rehabilitation Technologies”, aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [......

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Published inBioengineering (Basel) Vol. 12; no. 1; p. 70
Main Authors Tigrini, Andrea, Sbrollini, Agnese, Mengarelli, Alessandro
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.01.2025
MDPI
Subjects
Alzheimer's disease
Artificial intelligence
Bioengineering
Brain research
Data processing
Disease
Electronic data processing
Machine learning
Medical imaging
Methods
n/a
Neuroimaging
Neuroplasticity
Rehabilitation
Robotics
Self-help devices for the disabled
Sleep disorders
Stroke
Technology application
Italy
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Abstract This Special Issue (SI), “Data Processing and Machine Learning for Assistive and Rehabilitation Technologies”, aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...]
AbstractList This Special Issue (SI), “Data Processing and Machine Learning for Assistive and Rehabilitation Technologies”, aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...]
This Special Issue (SI), "Data Processing and Machine Learning for Assistive and Rehabilitation Technologies", aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...].This Special Issue (SI), "Data Processing and Machine Learning for Assistive and Rehabilitation Technologies", aimed to collect cutting-edge research papers that frame how data-driven approaches and machine learning techniques are advancing the field of assistive and rehabilitation technologies [...].
Audience Academic
Author Tigrini, Andrea
Mengarelli, Alessandro
Sbrollini, Agnese
AuthorAffiliation Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy a.mengarelli@staff.univpm.it (A.M.)
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Cites_doi 10.3390/bioengineering10060648
10.3390/bioengineering11030206
10.3390/bioengineering10050553
10.3390/bioengineering10080950
10.3390/bioengineering10050557
10.20944/preprints202303.0510.v1
10.3390/bioengineering10030281
10.3390/bioengineering10080990
10.3390/bioengineering10020219
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2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2025 by the authors. 2025
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SubjectTerms Alzheimer's disease
Artificial intelligence
Bioengineering
Brain research
Data processing
Disease
Electronic data processing
Machine learning
Medical imaging
Methods
n/a
Neuroimaging
Neuroplasticity
Rehabilitation
Robotics
Self-help devices for the disabled
Sleep disorders
Stroke
Technology application
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Title Data Processing and Machine Learning for Assistive and Rehabilitation Technologies
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