Contactless Fall Detection by Means of Multiple Bioradars and Transfer Learning.

Fall detection in humans is critical in the prevention of life-threatening conditions. This is especially important for elderly people who are living alone. Therefore, automatic fall detection is one of the most relevant problems in geriatrics.

Fall Detection Using Multiple Bioradars and Convolutional Neural Networks.

A lack of effective non-contact methods for automatic fall detection, which may result in the development of health and life-threatening conditions, is a great problem of modern medicine, and in particular, geriatrics. The purpose of the present work was to investigate the advantages of utilizing a multi-bioradar system in the accuracy of remote fall detection. The proposed concept combined usage of wavelet transform and deep learning to detect fall episodes.

Challenges and Potential Solutions of Psychophysiological State Monitoring with Bioradar Technology.

Psychophysiological state monitoring provides a promising way to detect stress and accurately assess wellbeing. The purpose of the present work was to investigate the advantages of utilizing a new unobtrusive multi-transceiver system on the accuracy of remote psychophysiological state monitoring by means of a bioradar technique. The technique was tested in laboratory conditions with the participation of 35 practically healthy volunteers, who were asked to perform arithmetic and physical workload tests imitating different types of stressors.

Estimation of a priori probabilities of sleep stages: A cycle-based approach.

This paper presents a model for the estimation of a priori probabilities of sleep epoch classes based on the epoch location in a sleep cycle. These probabilities are used as additional features for sleep stage classification based on the analysis of respiratory effort. The model was validated with data of 685 subjects selected from the Sleep Heart Health Study dataset.

Automated long-term contactless temperature monitoring in animals via a thermographic camera.

The paper deals with a problem of a remote prolonged temperature monitoring of biological objects. It presents an algorithm for automatic analysis and processing of video recording from a thermographic camera. Special attention is paid to the limitation of the method taking into account the possibility of its utilizing in laboratory conditions.