Literature DB >> 24110020

Artificial Neural Networks as an alternative to traditional fall detection methods.

Marcela Vallejo, Claudia V Isaza, José D López.   

Abstract

Falls are common events among older adults and may have serious consequences. Automatic fall detection systems are becoming a popular tool to rapidly detect such events, helping family or health personal to rapidly help the person that falls. This paper presents the results obtained in the process of testing a new fall detection method, based on Artificial Neural Networks (ANN). This method intends to improve fall detection accuracy, by avoiding the traditional threshold - based fall detection methods, and introducing ANN as a suitable option on this application.Also ANN have low computational cost, this characteristic makes them easy to implement on a portable device, comfortable to be wear by the patient.

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Year:  2013        PMID: 24110020     DOI: 10.1109/EMBC.2013.6609833

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Survey on fall detection and fall prevention using wearable and external sensors.

Authors:  Yueng Santiago Delahoz; Miguel Angel Labrador
Journal:  Sensors (Basel)       Date:  2014-10-22       Impact factor: 3.576

2.  An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.

Authors:  I Putu Edy Suardiyana Putra; James Brusey; Elena Gaura; Rein Vesilo
Journal:  Sensors (Basel)       Date:  2017-12-22       Impact factor: 3.576

  2 in total

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