Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Analysis of a Smartphone-Based Architecture with Multiple Mobility Sensors for Fall Detection.An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.Determine the Foot Strike Pattern Using Inertial Sensors

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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wetenschappelijk artikel

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наукова стаття, опублікована у 2016

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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P1476

Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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P2093

Amy Loutfi

http://www.w3.org/2001/XMLSchema#string

Gregory Koshmak

http://www.w3.org/2001/XMLSchema#string

Maria Linden

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P2860

Challenges, issues and trends in fall detection systems

Comparison and characterization of Android-based fall detection systems.

Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform.

Seamless tracing of human behavior using complementary wearable and house-embedded sensors

Smartphone-based solutions for fall detection and prevention: challenges and open issues

Ambient assisted living healthcare frameworks, platforms, standards, and quality attributes.

Evaluation of accelerometer-based fall detection algorithms on real-world falls.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

A ubiquitous and low-cost solution for movement monitoring and accident detection based on sensor fusion.

Appearance-based multimodal human tracking and identification for healthcare in the digital home.

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1-12

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1155/2016/6931789

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P478

2016

http://www.w3.org/2001/XMLSchema#string

P577

2016-01-01T00:00:00Z

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Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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P2860

P2860

Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

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P1433

P1476

P2093

P2860

P304

P31

P356

P478

P577

P356

P1433

P1476

P2093

P2860

P304

P31

P356

P478

P577