Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System

Human motion analysis using a smartphone-embedded accelerometer sensor provided important context for the identification of static, dynamic, and complex sequence of activities. Research in smartphone-based motion analysis are implemented for tasks, such as health status monitoring, fall detection an...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 20; no. 21; p. 6300
Main Authors:	Alo, Uzoma Rita, Nweke, Henry Friday, Teh, Ying Wah, Murtaza, Ghulam
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 05.11.2020 MDPI
Subjects:	acceleration sensor Accelerometers activity identification Algorithms Data collection Deep learning deep stacked autoencoder Delivery of Health Care Discriminant analysis Global positioning systems GPS health monitoring Human Activities Humans Identification Internet of Things Machine Learning Movement Obesity Physiology Questionnaires Sensors smart healthcare Smartphone Smartphones Support vector machines Weight control deep stacked autoencoder deep learning activity identification smart healthcare health monitoring acceleration sensor
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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