Assessment of fall-risk by means of a neural network based on parameters assessed by a wearable device during posturography

Medical Engineering and Physics

Volumn 30, Issue 3, 2008, Pages 367-372

  Giansanti, Daniele ^a   Maccioni, Giovanni ^a   Cesinaro, Stefano ^a   Benvenuti, Francesco ^b   Macellari, Velio ^a  

^a ISTITUTO SUPERIORE DI SANITÀ   (Italy)

^b Dipartimento della Riabilitazione   (Italy)

Author keywords

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

Indexed keywords

ACCELEROMETERS; GYROSCOPES; NEURAL NETWORKS; PARAMETER ESTIMATION; PATIENT MONITORING;

FALL PREVENTION; HUMAN MOVEMENT ANALYSIS;

RISK ANALYSIS;

ACCELEROMETER; ACCURACY; ADULT; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; DEVICE; FALL RISK ASSESSMENT; FEMALE; HUMAN; KINEMATICS; MALE; NERVE CELL; NEUROLOGIC DISEASE; PATIENT MONITORING; PERCEPTRON; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; STABILOGRAPHY; VALIDATION STUDY;

ACCELERATION; ACCIDENTAL FALLS; ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BACK; BIOMECHANICS; EVALUATION STUDIES AS TOPIC; FEMALE; HUMANS; MALE; MIDDLE AGED; MUSCULOSKELETAL EQUILIBRIUM; NEURAL NETWORKS (COMPUTER); POSTURE; RISK ASSESSMENT; RISK FACTORS; ROC CURVE; ROTATION; TRANSDUCERS;

EID: 40149103814     PISSN: 13504533     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.medengphy.2007.04.006     Document Type: Article

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