Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control

2020 ◽

pp. 207-235

Author(s):

Juana Isabel Méndez ◽

Omar Mata ◽

Pedro Ponce ◽

Alan Meier ◽

Therese Peffer ◽

...

Keyword(s):

Artificial Intelligence ◽

Elderly People ◽

Sensor System

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Intelligent Real-Time Multimodal Fall Detection in Fog Infrastructure Using Ensemble Learning

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_3 ◽

2020 ◽

pp. 53-79 ◽

Cited By ~ 1

Author(s):

V. Divya ◽

R. Leena Sri

Keyword(s):

Real Time ◽

Ensemble Learning ◽

Fall Detection

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Detecting Human Activities Based on a Multimodal Sensor Data Set Using a Bidirectional Long Short-Term Memory Model: A Case Study

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_2 ◽

2020 ◽

pp. 31-51 ◽

Cited By ~ 1

Author(s):

Silvano Ramos de Assis Neto ◽

Guto Leoni Santos ◽

Elisson da Silva Rocha ◽

Malika Bendechache ◽

Pierangelo Rosati ◽

...

Keyword(s):

Human Activities ◽

Short Term Memory ◽

Sensor Data ◽

Memory Model ◽

Short Term ◽

Data Set ◽

Term Memory ◽

Long Short Term Memory

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A Novel Approach for Human Fall Detection and Fall Risk Assessment

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_10 ◽

2020 ◽

pp. 237-259

Author(s):

Yoosuf Nizam ◽

M. Mahadi Abdul Jamil

Keyword(s):

Risk Assessment ◽

Fall Risk ◽

Fall Detection ◽

Fall Risk Assessment ◽

Novel Approach

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Open Source Implementation for Fall Classification and Fall Detection Systems

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_1 ◽

2020 ◽

pp. 3-29

Author(s):

Hiram Ponce ◽

Lourdes Martínez-Villaseñor ◽

José Núñez-Martínez ◽

Ernesto Moya-Albor ◽

Jorge Brieva

Keyword(s):

Open Source ◽

Fall Detection ◽

Detection Systems

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An Interpretable Machine Learning Model for Human Fall Detection Systems Using Hybrid Intelligent Models

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_8 ◽

2020 ◽

pp. 181-205 ◽

Cited By ~ 2

Author(s):

Paulo Vitor C. Souza ◽

Augusto J. Guimaraes ◽

Vanessa S. Araujo ◽

Lucas O. Batista ◽

Thiago S. Rezende

Keyword(s):

Machine Learning ◽

Fall Detection ◽

Learning Model ◽

Detection Systems ◽

Interpretable Machine Learning ◽

Machine Learning Model ◽

Intelligent Models

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Application of Convolutional Neural Networks for Fall Detection Using Multiple Cameras

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_5 ◽

2020 ◽

pp. 97-120

Author(s):

Ricardo Espinosa ◽

Hiram Ponce ◽

Sebastián Gutiérrez ◽

Lourdes Martínez-Villaseñor ◽

Jorge Brieva ◽

...

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Fall Detection ◽

Multiple Cameras

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Classification of Daily Life Activities for Human Fall Detection: A Systematic Review of the Techniques and Approaches

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_7 ◽

2020 ◽

pp. 137-179 ◽

Cited By ~ 1

Author(s):

Yoosuf Nizam ◽

M. Mahadi Abdul Jamil

Keyword(s):

Systematic Review ◽

Daily Life ◽

Fall Detection ◽

Daily Life Activities

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Approaching Fall Classification Using the UP-Fall Detection Dataset: Analysis and Results from an International Competition

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_6 ◽

2020 ◽

pp. 121-133

Author(s):

Hiram Ponce ◽

Lourdes Martínez-Villaseñor

Keyword(s):

Fall Detection ◽

International Competition ◽

Dataset Analysis

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Wearable Sensors Data-Fusion and Machine-Learning Method for Fall Detection and Activity Recognition

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-38748-8_4 ◽

2020 ◽

pp. 81-96 ◽

Cited By ~ 2

Author(s):

Hristijan Gjoreski ◽

Simon Stankoski ◽

Ivana Kiprijanovska ◽

Anastasija Nikolovska ◽

Natasha Mladenovska ◽

...

Keyword(s):

Machine Learning ◽

Data Fusion ◽

Activity Recognition ◽

Wearable Sensors ◽

Fall Detection ◽

Machine Learning Method ◽

Learning Method

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Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control
Latest Publications

TOTAL DOCUMENTS

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Published By Springer International Publishing

Multi-sensor System, Gamification, and Artificial Intelligence for Benefit Elderly People

Intelligent Real-Time Multimodal Fall Detection in Fog Infrastructure Using Ensemble Learning

Detecting Human Activities Based on a Multimodal Sensor Data Set Using a Bidirectional Long Short-Term Memory Model: A Case Study

A Novel Approach for Human Fall Detection and Fall Risk Assessment

Open Source Implementation for Fall Classification and Fall Detection Systems

An Interpretable Machine Learning Model for Human Fall Detection Systems Using Hybrid Intelligent Models

Application of Convolutional Neural Networks for Fall Detection Using Multiple Cameras

Classification of Daily Life Activities for Human Fall Detection: A Systematic Review of the Techniques and Approaches

Approaching Fall Classification Using the UP-Fall Detection Dataset: Analysis and Results from an International Competition

Wearable Sensors Data-Fusion and Machine-Learning Method for Fall Detection and Activity Recognition

Export Citation Format

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and ControlLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Multi-sensor System, Gamification, and Artificial Intelligence for Benefit Elderly People

Intelligent Real-Time Multimodal Fall Detection in Fog Infrastructure Using Ensemble Learning

Detecting Human Activities Based on a Multimodal Sensor Data Set Using a Bidirectional Long Short-Term Memory Model: A Case Study

A Novel Approach for Human Fall Detection and Fall Risk Assessment

Open Source Implementation for Fall Classification and Fall Detection Systems

An Interpretable Machine Learning Model for Human Fall Detection Systems Using Hybrid Intelligent Models

Application of Convolutional Neural Networks for Fall Detection Using Multiple Cameras

Classification of Daily Life Activities for Human Fall Detection: A Systematic Review of the Techniques and Approaches

Approaching Fall Classification Using the UP-Fall Detection Dataset: Analysis and Results from an International Competition

Wearable Sensors Data-Fusion and Machine-Learning Method for Fall Detection and Activity Recognition

Challenges and Trends in Multimodal Fall Detection for Healthcare - Studies in Systems, Decision and Control
Latest Publications