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Automatic and Efficient Fall Risk Assessment Based on Machine Learning
Nadav Eichler
, Shmuel Raz
,
Adi Toledano-Shubi
, Daphna Livne
,
Ilan Shimshoni
,
Hagit Hel-Or
Department of Computer Science
Department of Information Systems
Research output
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Contribution to journal
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Article
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peer-review
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Keyphrases
Machine Learning
100%
Berg Balance Scale
100%
Fall Risk Assessment
100%
Fall Risk
50%
Automated System
25%
Order of Accuracy
12%
Confidence Level
12%
Elderly People
12%
Scaling Test
12%
Physiotherapist
12%
Machine Learning Algorithms
12%
Spatio-temporal Features
12%
Fall Prevention
12%
Risk Prediction
12%
Medical Community
12%
Scale Assessment
12%
Statistical Evaluation
12%
Machine Learning Classifiers
12%
Efficient System
12%
Accuracy Evaluation
12%
Medical Tests
12%
Technology Learning
12%
Machine Learning System
12%
Scale Evaluation
12%
Motion Tracking System
12%
Multi-depth
12%
Human Tracking
12%
Human Motion
12%
Medical Assessment
12%
Accuracy Threshold
12%
Depth Camera
12%
Computer Science
Machine Learning
100%
Learning System
100%
Human Motions
66%
Temporal Feature
33%
Tracking System
33%
Machine Learning Algorithm
33%
Presented Approach
33%
Confidence Level
33%
Medical Community
33%
Prevention Program
33%