In this paper, we describe our investigation of traces naturally occurring emotions in electrical brain signals, that can be used to build interfaces respond emotional state.This study confirms a number known affective correlates realistic, uncontrolled environment for the valence (or pleasure), arousal and dominance: (1) significant decrease frontal power theta range is found increasingly positive valence, (2) increase alpha associated with increasing arousal, (3) right posterior delta (4)...

Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and one of the enabling technologies for disaster early-warning systems. Event detection functionality WSNs can be great help importance (near) real-time of, example, meteorological natural hazards wild residential fires. From data-mining perspective, many real world events exhibit specific patterns, which detected by applying machine learning (ML)...

Brain-computer interfaces (BCIs) are not only being developed to aid disabled individuals with motor substitution, recovery, and novel communication possibilities, but also as a modality for healthy users in entertainment gaming.This study investigates whether the incorporation of BCI popular game World Warcraft (WoW) has effects on user experience.A control channel based parietal alpha band power is used shape function avatar game.In experiment, participants , mix experienced inexperienced...

In electronic health (eHealth) research, limited insight has been obtained on process outcomes or how the use of technology contributed to users' ability have a healthier life, improved well-being, activate new attitudes in their daily tasks. As result, eHealth is often perceived as black box. To open this box eHealth, methodologies must extend beyond classic effect evaluations. The analyses log data (anonymous records real-time actions performed by each user) can provide continuous and...

Human Activity Recognition is focused on the use of sensing technology to classify human activities and infer behavior. While traditional machine learning approaches hand-crafted features train their models, recent advancements in neural networks allow for automatic feature extraction. Auto-encoders are a type network that can learn complex representations data commonly used anomaly detection. In this work we propose novel multi-class algorithm which consists an ensemble auto-encoders where...

The multimodal, multi-paradigm brain-computer interfacing (BCI) game Bacteria Hunt was used to evaluate two aspects of BCI interaction in a gaming context. One goal examine the effect feedback on ability user manipulate his mental state relaxation. This done by having one condition which subject played with real feedback, and another sham feedback. did not seem affect experience (such as sense control tension) or objective indicators relaxation, alpha activity heart rate. results are...

Automatic sleep staging on an online basis has recently emerged as a research topic motivated by fundamental research. The aim of this paper is to find optimal signal processing methods and machine learning algorithms achieve the single EEG signal. classification performance obtained using six different signals various feature sets compared kappa statistic which very become popular in A variable duration segment (or epoch) decide stage also analyzed. Spectral-domain, time-domain, linear,...

Currently the field of brain–computer interfacing is increasingly focused on developing usable interfaces (BCIs) to better ensure technology transfer and acceptance. Many studies have investigated usability BCI applications as a whole. Here we aim investigate one specific component an electroencephalogram (EEG)-based system: acquisition component. This study compares three different EEG headsets in context P300-based application for communication. Thirteen participants took part...

Brain-computer interfaces (BCI) come with a lot of issues, such as delays, bad recognition, long training times, and cumbersome hardware. Gamers are large potential target group for this new interaction modality, but why would healthy subjects want to use it? BCI provides combination information features that no other input modality can offer. But general acceptance technology, usability user experience will need be taken into account when designing systems. This paper discusses the...

A brain-computer interface (BCI) enables direct communication from the brain to devices, bypassing traditional pathway of peripheral nerves and muscles. Traditional approaches BCIs require user train for weeks or even months learn control BCI. In contrast, based on machine learning only a calibration session less than an hour before system can be used, since adapts user's existing signals. However, this has repeated each use BCI due inter-session variability, which makes using still...

For an artifact such as a robot or virtual agent to respond appropriately human social touch behavior, it should be able automatically detect and recognize touch. This paper describes the data collection of CoST: Corpus Social Touch, set containing 7805 captures 14 different gestures. All gestures were performed in three variants: gentle, normal rough on pressure sensor grid wrapped around mannequin arm. Recognition these gesture classes using various classifiers yielded accuracies up 60 %;...

Touch behavior is of great importance during social interaction. To transfer the tactile modality from interpersonal interaction to other areas such as Human-Robot Interaction (HRI) and remote communication automatic recognition touch necessary. This paper introduces CoST: Corpus Social Touch, a collection containing 7805 instances 14 different gestures. The gestures were performed in three variations: gentle, normal rough, on sensor grid wrapped around mannequin arm. Recognition rough...

Abstract We propose a novel approach to developing tractable affective dialogue model for probabilistic frame-based systems. The model, based on Partially Observable Markov Decision Process (POMDP) and Dynamic Network (DDN) techniques, is composed of two main parts: the slot-level manager global manager. It has new features: (1) being able deal with large number slots (2) take into account some aspects user's state in deriving adaptive strategies. Our implemented prototype can handle...

Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and one of the enabling technologies for early-warning disaster systems. Event detection functionality WSNs can be great help importance (near) real-time of, example, meteorological natural hazards wild residential fires. From data-mining perspective, many real world events exhibit specific patterns, which detected by applying machine learning (ML)...

Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of pose space. In this paper, we assume that a silhouette can be extracted monocular input. We compare three shape descriptors are used encoding silhouettes: Fourier descriptors, contexts Hu moments. An example-based approach taken recover upper body these descriptors. perform experiments with deformed silhouettes test each descriptor's robustness...