Extended Reality Telemedicine Collaboration System Using Patient Avatar Based on 3D Body Pose Estimation.

Recent advances in extended reality (XR) technology have opened the possibility of significantly improving telemedicine systems. This is primarily achieved by transferring 3D information about patient state, which is utilized to create more immersive experiences on VR/AR headsets. In this paper, we propose an XR-based telemedicine collaboration system in which the patient is represented as a 3D avatar in an XR space shared by local and remote clinicians.

Emotion Recognition Using a Reduced Set of EEG Channels Based on Holographic Feature Maps.

An important function of the construction of the Brain-Computer Interface (BCI) device is the development of a model that is able to recognize emotions from electroencephalogram (EEG) signals. Research in this area is very challenging because the EEG signal is non-stationary, non-linear, and contains a lot of noise due to artifacts caused by muscle activity and poor electrode contact. EEG signals are recorded with non-invasive wearable devices using a large number of electrodes, which increase the dimensionality and, thereby, also the computational complexity of EEG data.

Cochlea-inspired speech recognition interface.

Automatic speech recognition (ASR) technology provides a natural interface for human-machine interaction. Typical ASR systems can achieve high performance in quiet environments but, unlike humans, perform poorly in real-world situations. To better simulate the human auditory periphery and improve the performance in realistic noisy scenarios, we propose two models of speech recognition front-ends based on a biophysical cochlear model.