Innovative Head-Mounted System Based on Inertial Sensors and Magnetometer for Detecting Falling Movements

Autor: Chien-Hsu Chen, Peng Ting Chen, Pi Shan Sung, Chih-Lung Lin, Fu Hsing Chen, Ping Hsiao Hsieh, Chih Cheng Hsu, Ting Ching Chu, Chou Ching K. Lin, Wen Ching Chiu, Yuan Hao Ho
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Computer science
Movement
Acceleration
02 engineering and technology
head-mounted devices
lcsh:Chemical technology
01 natural sciences
Biochemistry
Article
Analytical Chemistry
law.invention
Wearable Electronic Devices
triaxial magnetometer
law
Inertial measurement unit
Injury prevention
Activities of Daily Living
0202 electrical engineering
electronic engineering
information engineering
Humans
Computer vision
lcsh:TP1-1185
Sensitivity (control systems)
Electrical and Electronic Engineering
triaxial accelerometer
Instrumentation
business.industry
Orientation (computer vision)
010401 analytical chemistry
Gyroscope
triaxial gyroscope
Atomic and Molecular Physics
and Optics
0104 chemical sciences
orientation filter
fall detection
Filter (video)
020201 artificial intelligence & image processing
Accidental Falls
Artificial intelligence
Falling (sensation)
business
signal detecting and processing
Algorithms
Zdroj: Sensors, Vol 20, Iss 5774, p 5774 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 20
ISSN: 1424-8220
Popis: This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer&rsquo
s head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer
as such, a Madgwick&rsquo
s filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.
Databáze: OpenAIRE
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