APPLICATION OF DECISION TREES TO THE FALL DETECTION OF ELDERLY PEOPLE USING DEPTH-BASED SENSORS

Piotr Bilski, Paweł Mazurek, Jakub Wagner, Wiesław Winiecki
Abstract:
The paper presents application of the Decision Tree (DT) to the fall detection of elderly people monitored by the infrared depth sensors. The decision making system works on data acquired by the sensor, recording movement of the person and raising the alarm if his/her behaviour suggests that the accident occurred. From the measurement data so-called morphological features are extracted, further processed by the DT. Various configurations of the classifier have been verified, proving its usefulness to solve the presented task, but also revealing disadvantages.
Keywords:
fall detection, decision tree, depth sensor, binary classification
Download:
IMEKO-WC-2015-TC18-349.pdf
DOI:
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Event details
Event name:
XXI IMEKO World Congress
Title:

Measurement in Research and Industry

Place:
Prague, CZECH REPUBLIC
Time:
30 August 2015 - 04 September 2015
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