Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model
Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides...
Main Authors: | Chia-Yeh Hsieh, Kai-Chun Liu, Chih-Ning Huang, Woei-Chyn Chu, Chia-Tai Chan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/17/2/307 |
Similar Items
-
Multiphase Identification Algorithm for Fall Recording Systems Using a Single Wearable Inertial Sensor
by: Chia-Yeh Hsieh, et al.
Published: (2021-05-01) -
Automatic Fall Monitoring: A Review
by: Natthapon Pannurat, et al.
Published: (2014-07-01) -
Fall Risk Assessment Using Wearable Sensors: A Narrative Review
by: Rafael N. Ferreira, et al.
Published: (2022-01-01) -
Elderly Fall Detection and Fall Direction Detection via Various Machine Learning Algorithms Using Wearable Sensors
by: Yılmaz Güven, et al.
Published: (2021-09-01) -
Optimization and Technical Validation of the AIDE-MOI Fall Detection Algorithm in a Real-Life Setting with Older Adults
by: Simon Scheurer, et al.
Published: (2019-03-01)