Internet of things based multi-sensor patient fall detection system

Internet of things based multi-sensor patient fall detection system

Accidental falls of patients cannot be completely prevented. However, timely fall detection can help prevent further complications such as blood loss and unconsciousness. In this study, the authors present a cost-effective integrated system designed to remotely detect patient falls in hospitals in a...

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Bibliographic Details
Main Author: Khan, Sarah (author)
Other Authors: Qamar, Ramsha (author), Zaheen, Rahma (author), Al-Ali, Abdul-Rahman (author), Al Nabulsi, Ahmad (author), Al-Nashash, Hasan (author)
Format: article
Published: 2019
Subjects:
Pattern classification
Body sensor networks
Biomedical equipment
Gyroscopes
Geriatrics
Bayes methods
Medical signal processing
Microcomputers
Accelerometers
Patient monitoring
Internet of Things
Nearest neighbour methods
Cost-effective integrated system
Credit card-sized single board microcomputer
Visual-based classifier
Sensor data
Naive Bayes' classifiers
Internet of things based multisensor patient fall detection system
Nonfall motions classification
k-nearest neighbour
Online Access:http://hdl.handle.net/11073/16598
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http://hdl.handle.net/11073/16598

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