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Machine learning based classification of normal, slow and fast walking by extracting multimodal features from stride interval time series.
Aziz, Wajid; Hussain, Lal; Khan, Ishtiaq Rasool; Alowibdi, Jalal S; Alkinani, Monagi H.
Affiliation
  • Aziz W; Department of Computer & AI, College of Computer Science and Engineering (CCSE), University of Jeddah, P.O. Box 80327, Jeddah 21589, Saudi Arabia.
  • Hussain L; Department of Computer Science & IT, University of Azad Jammu and Kashmir, King Abdullah Campus, Muzaffarabad 13100, Pakistan.
  • Khan IR; Department of Computer Science & IT, University of Azad Jammu and Kashmir, Neelum Campus, Athmuqam 13230, Pakistan.
  • Alowibdi JS; Department of Computer & AI, College of Computer Science and Engineering (CCSE), University of Jeddah, P.O. Box 80327, Jeddah 21589, Saudi Arabia.
  • Alkinani MH; Department of Computer & AI, College of Computer Science and Engineering (CCSE), University of Jeddah, P.O. Box 80327, Jeddah 21589, Saudi Arabia.
Math Biosci Eng ; 18(1): 495-517, 2020 12 10.
Article in En | MEDLINE | ID: mdl-33525104
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Walking / Machine Learning Type of study: Prognostic_studies Limits: Humans Language: En Journal: Math Biosci Eng Year: 2020 Document type: Article Affiliation country: Arabia Saudita
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Walking / Machine Learning Type of study: Prognostic_studies Limits: Humans Language: En Journal: Math Biosci Eng Year: 2020 Document type: Article Affiliation country: Arabia Saudita