A Deep Learning-Based Approach for the Recognition of Sleep Disorders in Patients with Cognitive Diseases: A Case Study
Conference Paper
Publication Date:
2017
abstract:
Alzheimer's disease is the most common type of
dementia. Patients suffer from of this kind of disease could
show symptoms such as sleep disturbances, muscle rigidity or
other typical Alzheimer's movement irregularities. In our work,
we have focused on those types of disturbances related to sleep
disorders. Due to their not well-known nature, it is difficult to
develop software able to identify sleep disorders. In this work,
we have addressed the problem of the automatic recognition of
sleep disorders in patients with Alzheimer's disease by using deep
learning algorithms
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
deep learning; Convolutional Neural Network; Human Behaviors Recognition
List of contributors: