Classification of healthy and abnormal swallows based on accelerometry and nasal airflow signals

Artificial Intelligence in Medicine

Volumn 52, Issue 1, 2011, Pages 17-25

  Lee, Joon ^a,b,c   Steele, Catriona M ^a,b,c   Chau, Tom ^a,d  

^a University of Toronto   (Canada)

^b TORONTO REHABILITATION INSTITUTE   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

^d UNIVERSITY OF TORONTO   (Canada)

Author keywords

Abnormal swallow detection; Accelerometry; Deglutition; Dysphagia; Nasal airflow; Swallowing

Indexed keywords

ABNORMAL SWALLOW DETECTION; ACCELEROMETRY; DEGLUTITION; DYSPHAGIA; NASAL AIRFLOW; SWALLOWING;

ACCELEROMETERS; BIOLOGICAL ORGANS; FEATURE EXTRACTION; RATING;

SIGNAL DETECTION;

ACCELEROMETRY; ADOLESCENT; ADULT; ARTICLE; AUTOMATION; BOOTSTRAPPING; CLASSIFICATION; CLINICAL ARTICLE; CLINICAL ASSESSMENT; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DISCRIMINANT ANALYSIS; DYSPHAGIA; FEMALE; FLUOROSCOPY; GENETIC ALGORITHM; GOLD STANDARD; HUMAN; MALE; NOSE AIRFLOW; PRIORITY JOURNAL; PYRIFORM SINUS; QUANTITATIVE DIAGNOSIS; SIGNAL DETECTION; SWALLOWING; VIDEORECORDING;

ADULT; ALGORITHMS; DEGLUTITION; DEGLUTITION DISORDERS; HUMANS; NOSE; PULMONARY VENTILATION;

EID: 79955979017     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2011.03.002     Document Type: Article

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