TY - JOUR
T1 - Development of a Bathing Accident Monitoring System Using a Depth Sensor
AU - Endo, Yoshiaki
AU - Premachandra, Chinthaka
N1 - Publisher Copyright:
© 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2022/2/1
Y1 - 2022/2/1
N2 - Among the domestic accidents that occur globally, a few percent are due to accidental drowning, mostly related to bathing. This letter examines countermeasures against bathing accidents and proposes a bathing accident monitoring system to prevent accidental drowning due to loss of consciousness during bathing. This system considers the user's privacy and uses only the depth information acquired by a depth sensor installed in the bathroom. This system grasps the movement of the bather with a depth sensor and informs others, such as the bather's family, when drowning might be occurring. In this letter, we mainly analyzed depth data from depth sensors and developed automatic detection of drowning conditions. Automatic detection of the drowning state was experimentally evaluated in an actual bathroom. The scenario for the experiment was the natural flow of a series of general bathing movements (e.g., normal bathing, wiping the face, and touching the shoulders) and reproduction of the drowning state. As a result, it was shown that the automatic detection rate of the drowning state was at the applicable level.
AB - Among the domestic accidents that occur globally, a few percent are due to accidental drowning, mostly related to bathing. This letter examines countermeasures against bathing accidents and proposes a bathing accident monitoring system to prevent accidental drowning due to loss of consciousness during bathing. This system considers the user's privacy and uses only the depth information acquired by a depth sensor installed in the bathroom. This system grasps the movement of the bather with a depth sensor and informs others, such as the bather's family, when drowning might be occurring. In this letter, we mainly analyzed depth data from depth sensors and developed automatic detection of drowning conditions. Automatic detection of the drowning state was experimentally evaluated in an actual bathroom. The scenario for the experiment was the natural flow of a series of general bathing movements (e.g., normal bathing, wiping the face, and touching the shoulders) and reproduction of the drowning state. As a result, it was shown that the automatic detection rate of the drowning state was at the applicable level.
KW - Accidents
KW - Cameras
KW - Monitoring
KW - Nose
KW - Sensor systems
KW - Sensors
KW - Skeleton
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U2 - 10.1109/LSENS.2021.3139636
DO - 10.1109/LSENS.2021.3139636
M3 - Article
AN - SCOPUS:85122577485
SN - 2475-1472
VL - 6
JO - IEEE Sensors Letters
JF - IEEE Sensors Letters
IS - 2
ER -