New neural network classifier of fall-risk based on the Mahalanobis distance and kinematic parameters assessed by a wearable device

Physiological Measurement

Volumn 29, Issue 3, 2008, Pages

  Giansanti, Daniele ^a   Macellari, Velio ^a   Maccioni, Giovanni ^a  

^a ISTITUTO SUPERIORE DI SANITÀ   (Italy)

Author keywords

Accelerometer; Accuracy; Fall prevention; Fall risk; Gyroscopes; Human movement analysis; Patient monitoring

Indexed keywords

ACCIDENT PREVENTION; CLASSIFICATION (OF INFORMATION); GYROSCOPES; KINEMATICS; PATIENT MONITORING; RISK ASSESSMENT; WEARABLE TECHNOLOGY;

ACCURACY; FALL PREVENTION; FALL RISK; HUMAN MOVEMENT ANALYSIS; KINEMATICS PARAMETERS; MAHALANOBIS DISTANCES; NEURAL NETWORKS CLASSIFIERS; NEURAL-NETWORKS; STATISTICAL CLASSIFIER; WEARABLE DEVICES;

ACCELEROMETERS;

ACCELEROMETER; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; CLASSIFIER; DEVICE; FALL RISK ASSESSMENT; FEMALE; GERIATRICS; HUMAN; KINEMATICS; MALE; PERCEPTRON; PRIORITY JOURNAL; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; STABILOGRAPHY; SUPPORT VECTOR MACHINE; VALIDATION STUDY;

EID: 41049085621     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/29/3/N01     Document Type: Article

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