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Mostrando ítems 1-5 de 5
Artículo
AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks
(MDPI, 2021)
Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits ...
Ponencia
Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices
(ScitePress Digital Library, 2019)
Falls are one of the most frequent causes of injuries in elderly people. Wearable Fall Detection Systems provided a ubiquitous tool for monitoring and alert when these events happen. Recurrent Neural Networks (RNN) are ...
Ponencia
An Automated Fall Detection System Using Recurrent Neural Networks
(Springer, 2019)
Falls are the most common cause of fatal injuries in elderly people, causing even death if there is no immediate assistance. Fall detection systems can be used to alert and request help when this type of accident happens. ...
Ponencia
Lower-Limb Falling Detection System Using Gated Recurrent Neural Networks
(IARIA XPS Press, 2020-03-22)
Accidental falls are one of the most common causes of premature disability and mortality related to unnatural causes. This affects mainly the elderly population. With the current aging of the population, the rate of ...
Artículo
Wearable Fall Detector Using Recurrent Neural Networks
(MDPI, 2019)
Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. ...