PhyCS 2014 Abstracts


Area 1 - Methodologies and Methods

Full Papers
Paper Nr: 2
Title:

Seven Principles to Mine Flexible Behavior from Physiological Signals for Effective Emotion Recognition and Description in Affective Interactions

Authors:

Rui Henriques and Ana Paiva

Abstract: Measuring affective interactions using physiological signals has become a critical step to understand engagements with human and artificial agents. However, traditional methods for signal analysis are not yet able to effectively deal with the differences of responses across individuals and with flexible sequential behavior. In this work, we rely on empirical results to define seven principles for a robust mining of physiological signals to recognize and characterize affective states. The majority of these principles are novel and driven from advanced pre-processing techniques and temporal data mining methods. A methodology that integrates these principles is proposed and validated using electrodermal signals collected during human-to-human and human-to-robot affective interactions.

Paper Nr: 6
Title:

Directed Effort - A Generic Measurand for Higher Level Behavior Analysis

Authors:

Benedikt Gollan and Alois Ferscha

Abstract: Behavior and body language are essential components of human interaction. In this paper, we propose a meta-level representation of human behavior for interpretative, higher level applications in human-computer interaction systems called Directed Effort. A theoretical framework is described which is derived from behavioral and psychological sciences and which is designed to represent the commitment and interest of people towards objects via behavior analysis in real-life scenarios. Directed Effort, a score which allows the interpretation of detected behavior changes is introduced as a generic measurand. Furthermore, a prototypical implementation is documented to show the potential of the computed meta-level description of behavior.

Area 2 - Human Factors

Full Papers
Paper Nr: 10
Title:

Extracting Emotions and Communication Styles from Vocal Signals

Authors:

Licia Sbattella, Luca Colombo, Carlo Rinaldi, Roberto Tedesco, Matteo Matteucci and Alessandro Trivilini

Abstract: Many psychological and social studies highlighted the two distinct channels we use to exchange information among us—an explicit, linguistic channel, and an implicit, paralinguistic channel. The latter contains information about the emotional state of the speaker, providing clues about the implicit meaning of the message. In particular, the paralinguistic channel can improve applications requiring human-machine interactions (for example, Automatic Speech Recognition systems or Conversational Agents), as well as support the analysis of human-human interactions (think, for example, of clinic or forensic applications). In this work we present PrEmA, a tool able to recognize and classify both emotions and communication style of the speaker, relying on prosodic features. In particular, communication-style recognition is, to our knowledge, new, and could be used to infer interesting clues about the state of the interaction. We selected two sets of prosodic features, and trained two classifiers, based on the Linear Discriminant Analysis. The experiments we conducted, with Italian speakers, provided encouraging results (Ac=71% for classification of emotions, Ac=86% for classification of communication styles), showing that the models were able to discriminate among emotions and communication styles, associating phrases with the correct labels.

Area 3 - Devices

Full Papers
Paper Nr: 14
Title:

Multiresolution Analysis of an Information based EEG Graph Representation for Motor Imagery Brain Computer Interfaces

Authors:

Javier Asensio-Cubero, John Q. Gan and Ramaswamy Palaniappan

Abstract: Brain computer interfaces are control systems that allow the interaction with electronic devices by analysing the user’s brain activity. The analysis of brain signals, more concretely, electroencephalographic data, represents a big challenge due to its noisy and low amplitude nature. Many researchers in the field have applied wavelet transform in order to leverage the signal analysis benefiting from its temporal and spectral capabilities. In this study we make use of the so-called second generation wavelets to extract features from temporal, spatial and spectral domains. The complete multiresolution analysis operates over an enhanced graph representation of motor imaginary trials, which uses per-subject knowledge to optimise the spatial links among the electrodes and to improve the filter design. As a result we obtain a novel method that improves the performance of classifying different imaginary limb movements without compromising the low computational resources used by lifting transform over graphs.

Area 4 - Methodologies and Methods

Full Papers
Paper Nr: 19
Title:

A Hierarchical BCI System Able to Discriminate between Non Intentional Control State and Four Intentional Control Activities

Authors:

Julio Abascal, Andoni Arruti, José I. Martín and Javier Muguerza

Abstract: This paper presents a two-level hierarchical approach to recognising intentional and non intentional mental tasks on a brain-computer interface. A clustering process is performed at the first recognition level in order to differentiate Non intentional Control state (NC) patterns from Intentional Control (IC) patterns. At the second level, the IC detected patterns are classified by means of supervised learning techniques, applied to the type of movement (left hand, right hand, tongue or foot imagery movement). The objective is to achieve high correct movement recognition scores, with a low percentage of wrong decisions (that is, low false positive rates), to avoid user frustration. Offline evaluation of the proposed prototype shows 84.5% accuracy, with a 6.7% false positive rate.

Paper Nr: 21
Title:

Design and Validation of a Mental and Social Stress Induction Protocol - Towards Load-invariant Physiology-based Stress Detection

Authors:

Camille Jeunet, Fabien Lotte and Christian Mühl

Abstract: Stress is a major societal issue with negative impacts on health and economy. Physiological computing offers a continuous, direct, and unobtrusive method for stress level assessment and computer-assisted stress management. However, stress is a complex construct and its physiology can vary depending on its source: cognitive workload or social evaluation. To study the feasibility of physiology-based load-invariant psychosocial stress-detection, we designed a stress-induction protocol able to independently vary the relevant types of psychophysiological activity: mental and psychosocial stress. Here, we validate the efficacy of our protocol to induce psychosocial and mental stress. Our participants (N=24) had to perform a cognitive task associated with two workload conditions (low/high mental stress), in two contexts (low/high psychosocial stress), during which we recorded subjects’ self-reports, behaviour, physiology and neurophysiology. Questionnaires showed that the subjectively perceived level of stress varied with the psychosocial stress induction, while perceived arousal and mental effort levels vary with mental stress induction. Behaviour and physiology further corroborated the validity of our protocol. Heart rate and skin conductance globally increased after psychosocial stress induction relative to the non-stressful condition. Moreover, we demonstrated that higher workload tasks (mental stress) led to decrease in performance and a marked increase of heart rate.

Area 5 - Devices

Full Papers
Paper Nr: 23
Title:

Online Detection of P300 related Target Recognition Processes During a Demanding Teleoperation Task - Classifier Transfer for the Detection of Missed Targets

Authors:

Hendrik Woehrle and Elsa Andrea Kirchner

Abstract: The detection of event related potentials and their usage for innovative tasks became a mature research topic in the last couple of years for brain computer interfaces. However, the typical experimental setups are usually highly controlled and designed to actively evoke specific brain activity like the P300 event related potential. In this paper, we show that the detection and passive usage of the P300 related brain activity is possible in highly uncontrolled and noisy application scenarios where the subjects are performing demanding senso-motor task, i.e., telemanipulation of a real robotic arm. In the application scenario, the subject wears an exoskeleton to control a robotic arm, which is presented to him in a virtual scenario. While performing the telemanipulation task he has to respond to important messages. By online analysis of the subject’s electroencephalogram we detect P300 related target recognition processes to infer on upcoming response behavior or missing of response behavior in case a target was not recognized. We show that a classifier that is trained to distinguish between brain activity evoked by recognized task relevant stimuli and ignored frequent task irrelevant stimuli can be applied to classify between brain activity evoked by recognized task relevant stimuli and brain activity that is evoked in case that task relevant stimuli are not recognized.

Area 6 - Human Factors

Full Papers
Paper Nr: 24
Title:

Orientation of Attention in Visual Feedbacks during Neurofeedback Relaxation

Authors:

Mehdi Karamnejad, Diane Gromala, Amber Choo, Chris Shaw and Xin Tong

Abstract: The assumptions underlying differing approaches to interface design result, in part, on how attention is managed and categorized using theories from media studies. The authors propose the term intraface to refer to biofeedback or other interfaces that are designed to support users who direct their attention inward to inner physiological states. In this paper, the role of representing feedback data in abstract forms is compared in an experiment using Neurosky’s neurofeedback device. Although preliminary, the results suggest that mapping biofeedback data from a brain-computer interface (BCI) to highly abstract ambient animations is more effective for relaxation than mapping it to a highly familiar symbolic smiley face icon or to a progress bar. The authors propose that the relative success of the abstract ambient animation can be explained because this representation of biofeedback data is the form that requires the least amount of attention, and that designing biofeedback interfaces that distribute the attention, supports the need of users to the task of directing most of their attention to their inner physiological states.

Area 7 - Devices

Full Papers
Paper Nr: 26
Title:

An EOG-based Sleep Monitoring System and Its Application on On-line Sleep-stage Sensitive Light Control

Authors:

Chih-En Kuo, Sheng-Fu Liang, Yi-Chieh Li, Fu-Yin Cherng, Wen-Chieh Lin, Peng-Yu Chen, Yen-Chen Liu and Fu-Zen Shaw

Abstract: Human beings spend approximately one third of their lives sleeping. Conventionally, to evaluate a subjects sleep quality, all-night polysomnogram (PSG) readings are taken and scored by a well-trained expert. The development of an automatic sleep-staging system that does not rely upon mounting a bulky PSG or EEG recorder on the head will enable physiological computing systems (PhyCS) to progress toward easy sleep and comfortable monitoring. In this paper, an electrooculogram (EOG)-based sleep scoring system is proposed. Compared to PSG or EEG recordings, EOG has the advantage of easy placement, and can be operated by the user individually. The proposed method was found to be more than 83% accurate when compared with the manual scorings applied to sixteen subjects. In addition to sleep-quality evaluation, the proposed system encompasses adaptive brightness control of light according to online monitoring of the users sleep stages. The experiments show that the EOG-based sleep scoring system is a practicable solution for home-use sleep monitoring due to the advantages of comfortable recording and accurate sleep staging.

Area 8 - Methodologies and Methods

Full Papers
Paper Nr: 27
Title:

Stress Recognition - A Step Outside the Lab

Authors:

Julian Ramos, Jin-Hyuk Hong and Anind K. Dey

Abstract: Despite the potential for stress and emotion recognition outside the lab environment, very little work has been reported that is feasible for use in the real world and much less for activities involving physical activity. In this work, we move a step forward towards a stress recognition system that works on a close to real world data set and shows a significant improvement over classification only systems. Our method uses clustering to separate the data into physical exertion levels and later performs stress classification over the discovered clusters. We validate our approach on a physiological stress dataset from 20 participants who performed 3 different activities of varying intensity under 3 different types of stimuli intended to cause stress. The results show an f-measure improvement of 130\% compared to using classification only.

Paper Nr: 33
Title:

Addressing Signals Asynchronicity during Psychophysiological Inference - A Temporal Construction Method

Authors:

François Courtemanche, Aude Dufresne, Elise L. LeMoyne and Esma Aimeur

Abstract: Predicting the psychological state of the user using physiological measures is one of the main objectives of physiological computing. While numerous works have addressed this task with great success, a large number of challenges remain to be solved in order to develop recognition approaches that can precisely and reliably feed human-computer interaction systems. This paper focuses on one of these challenges which is the temporal asynchrony between different physiological signals within one recognition model. The paper proposes a flexible and suitable method for feature extraction based on empirical optimisation of windows’ latency and duration. The approach is described within the theoretical framework of the psychophysiological inference and its common implementation using machine learning. The method has been experimentally validated (46 subjects) and results are presented. Empirically optimised values for the extraction windows are provided.

Area 9 - Human Factors

Short Papers
Paper Nr: 4
Title:

R&D of the Japanese Input Method using Life Log on an Eye-controlled Communication Device for Users with Disabilities

Authors:

Kazuaki Shoji, Hiromi Watanabe and Shinji Kotani

Abstract: We aim to enable the smooth communication of persons physically unable to speak. In our past study, we proposed three Japanese input methods using a portable eye- controlled communication device for users with conditions such as cerebral palsy or amyotrophic lateral sclerosis (ALS). However, these methods require nearly 30 seconds to cycle through one Japanese character. In this paper, we suggest a method to estimate the input word using the clues of nearby characters and accumulated experience. In addition, to raise the precision of the prediction, we use the connection between words based on a thesaurus. We have realized precise word conversion via a few input letters, as proved by the result of the simulation experiment.

Area 10 - Methodologies and Methods

Short Papers
Paper Nr: 9
Title:

Inducing Behavior Change in Children with Autism Spectrum Disorders by Monitoring their Attention

Authors:

Margarida Lucas da Silva, Hugo Silva and Daniel Gonçalves

Abstract: Children with Autism Spectrum Disorders (ASD) generally suffer from disorders which affect multiple behavioral aspects, such as communication, emotional awareness, social interaction, lack of attention, among many others. Modern technologies, are opening up new possibilities for computer-mediated interactions with increased outcomes, enabling both children and tutors to have a more effective work in the development of communicative and cognitive skills. In this article we introduce a module implemented in a platform for human-computer interaction, specifically designed for children with ASD, to control their levels of attention and test inducing behavior change. This allows us to shape new behaviors and learning strategies both in tutors and children.

Paper Nr: 12
Title:

Bilateral Motion Spectra - Analysis and Representation of Human Movement

Authors:

Anthony Schultz

Abstract: The body’s bilateral symmetry allows for various kinds of human motion patterns. Our paper presents a method for analyzing and representing motion capture time series that effectively identifies spatial and temporal patterns. We develop a factored representation of joint angle data based on quaternions and a metric pair for comparing different physical states of articulation. This metric pair is used to generate a metric space pair over the set of time series states. The result is represented as a 2-dimensional color image termed a bilateral motion spectrum. Several spectral motifs are presented and characterized.

Area 11 - Human Factors

Short Papers
Paper Nr: 15
Title:

Review of the Use of Electroencephalography as an Evaluation Method for Human-Computer Interaction

Authors:

Jérémy Frey, Christian Mühl, Fabien Lotte and Martin Hachet

Abstract: Evaluating human-computer interaction is essential as a broadening population uses machines, sometimes in sensitive contexts. However, traditional evaluation methods may fail to combine real-time measures, an ``objective'' approach and data contextualization. In this review we look at how adding neuroimaging techniques can respond to such needs. We focus on electroencephalography (EEG), as it could be handled effectively during a dedicated evaluation phase. We identify workload, attention, vigilance, fatigue, error recognition, emotions, engagement, flow and immersion as being recognizable by EEG. We find that workload, attention and emotions assessments would benefit the most from EEG. Moreover, we advocate to study further error recognition through neuroimaging to enhance usability and increase user experience.

Paper Nr: 16
Title:

A Physiological Evaluation of Immersive Experience of a View Control Method using Eyelid EMG

Authors:

Masaki Omata, Satoshi Kagoshima and Yasunari Suzuki

Abstract: This paper describes that the number of blood-volume pulses (BVP) and the level of skin conductance (SC) increased more with increasing immersive impression with a view control method using eyelid electromyography in virtual environment (VE) than those with a mouse control method. We have developed the view control method and the visual feedback associated with electromyography (EMG) signals of movements of user’s eyelids. The method provides a user with more immersive experiences in a virtual environment because of strong relationship between eyelid movement and visual feedback. This paper reports a physiological evaluation experiment to compare it with a common mouse input method by measuring subjects’ physiological data of their fear of an open high place in a virtual environment. Based on the results, we find the eyelid-movement input method improves the user’s immersive impression more significantly than the mouse input method.

Area 12 - Devices

Short Papers
Paper Nr: 17
Title:

Flexible Pressure Mapping Platform for Mobility Monitoring Applications

Authors:

S. Cruz, D. Dias, J. C. Viana and L. A. Rocha

Abstract: The goal of the work presented here is the development, integration and testing of an innovative technological approach to be the basis for a new product and service for markets associated with the “Health” vector. Our research focuses on a Physiological computing approach, where a polymeric flexible detection system, working as the sensing element is used as an input channel, and a computing system is responsible for the physiological signals synthesis. The proposed solution provides a simpler, lower cost and larger scale manufacturing production of polymer based sensors, along with an electronic interface and the software design. The sensing platform consists in a flexible PCB (Printed Circuit Boards) manufactured using conventional technology (defining the electrical connections and the capacitors dimensions) together with two flexible polymeric membranes (TPU) printed with conductive ink (Plexcore®) for definition of the electrodes. A Capacitance to Digital Converter (CDC) is used to measure the capacitance of the sensors, and a graphical interface in MATLAB allows real-time visualization of data. Current results performed on the pressure sensors indicate the feasibility of the approach.

Area 13 - Methodologies and Methods

Short Papers
Paper Nr: 20
Title:

In-chair Movements of Healthy People during Prolonged Sitting

Authors:

Elisa Marenzi, Gian Mario Bertolotti and Giovanni Danese

Abstract: This paper describes a program designed to detect and give a classification of the in-chair movements done by healthy people while seated for long periods of time. The purpose of this work is to identify the frequency, duration and typology of movements performed by subjects that need to remain seated for a prolonged time. The software finds the time instants of each movement, its duration and whether it is in the sagittal or the lateral plane; in particular it distinguishes between a left and right movement (in the lateral plane) and a forward or backward trunk movement. This information can be useful in many different domains: first of all to monitor the fidgeting phenomenon and consequently the feeling of discomfort in the office environment; it can be adopted to evaluate the fatigue of car and truck drivers; but the most important outcome concerns the clinical setting, in which it can be very helpful for the medical staff in determining an appropriate and personalized rehabilitation strategy for patients with motor limitations in order to prevent the development of pressure ulcers.

Area 14 - Human Factors

Short Papers
Paper Nr: 28
Title:

Can Ultrasonic Doppler Help Detecting Nasality for Silent Speech Interfaces? - An Exploratory Analysis based on Alignement of the Doppler Signal with Velum Aperture Information from Real-Time MRI

Authors:

João Freitas, António Teixeira and Miguel Sales Dias

Abstract: This paper describes an exploratory analysis on the usefulness of the information made available from Ultrasonic Doppler signal data collected from a single speaker, to detect velum movement associated to European Portuguese nasal vowels. This is directly related to the unsolved problem of detecting nasality in silent speech interfaces. The applied procedure uses Real-Time Magnetic Resonance Imaging (RT-MRI), collected from the same speaker providing a method to interpret the reflected ultrasonic data. By ensuring compatible scenario conditions and proper time alignment between the Ultrasonic Doppler signal data and the RT-MRI data, we are able to accurately estimate the time when the velum moves and the type of movement under a nasal vowel occurrence. The combination of these two sources revealed a moderate relation between the average energy of frequency bands around the carrier, indicating a probable presence of velum information in the Ultrasonic Doppler signal.

Area 15 - Methodologies and Methods

Short Papers
Paper Nr: 29
Title:

Relevant Elderly Gait Features for Functional Fitness Level Grouping

Authors:

Marta S. Santos, Vera Moniz-Pereira, André Lourenço, Ana Fred and António P. Veloso

Abstract: Locomotor tasks characterization plays an important role in trying to improve the quality of life of a growing elderly population. This paper focuses on this matter by trying to characterize the locomotion of two population groups with different functional fitness levels (high or low) while executing three different tasks - gait, stair ascent and stair descent. Features were extracted from gait data, and feature selection methods were used in order to get the set of features that allow differentiation between functional fitness level. Unsupervised learning was used to validate the sets obtained and, ultimately, indicated that it is possible to distinguish the two population groups. The sets of best discriminate features for each task are identified and thoroughly analysed.

Area 16 - Devices

Short Papers
Paper Nr: 41
Title:

Precise 3D Deep Brain Stimulation Electrode Location based on Multimodal Neuroimage Fusion

Authors:

Nádia Moreira da Silva, Verena E. Rozanski, Sérgio Neves Tafula and João Paulo Silva Cunha

Abstract: The success of neurosurgery strongly depends on the pre-neurosurgical evaluation phase, in which the delineation of the areas to be removed or to be stimulated must be very accurate. For patients undergoing Deep Brain Stimulation (DBS) it is vital the delineation of the target area prior to surgery, and after the implantation of the DBS lead to confirm the electrodes positioning. In this paper we present a system to accurately determine the 3D position of DBS electrodes implanted within the brain of Parkinson and Dystonia patients. The system was tested using a multimodal dataset from 16 patients (8 with Parkinson`s disease and 8 with dystonia) and, on average, the differences between the detected electrodes positions and the ones estimated manually by an experienced physician were less than a voxel in all cases.

Area 17 - Human Factors

Short Papers
Paper Nr: 42
Title:

BITalino: A Novel Hardware Framework for Physiological Computing

Authors:

Hugo Plácido da Silva, José Guerreiro, André Lourenço, Ana Fred and Raúl Martins

Abstract: Physical computing has spun a true global revolution in the way in which the digital interfaces with the real world. From bicycle jackets with turn signal lights to twitter-controlled christmas trees, the Do-it-Yourself (DiY) hardware movement has been driving endless innovations and stimulating an age of creative engineering. This ongoing (r)evolution has been led by popular electronics platforms such as the Arduino, the Lilypad, or the Raspberry Pi, however, these are not designed taking into account the specific requirements of biosignal acquisition. To date, the physiological computing community has been severely lacking a parallel to that found in the DiY electronics realm, especially in what concerns suitable hardware frameworks. In this paper, we build on previous work developed within our group, focusing on an all-in-one, low-cost, and modular biosignal acquisition hardware platform, that makes it quicker and easier to build biomedical devices. We describe the main design considerations, experimental evaluation and circuit characterization results, together with the results from a usability study performed with volunteers from multiple target user groups, namely health sciences and electrical, biomedical, and computer engineering.

Area 18 - Methodologies and Methods

Short Papers
Paper Nr: 48
Title:

Does the Audience Hear My Heart? - Comparing the Physiological Responses of Listeners with Those of the Composer

Authors:

Benjamin Luke Evans, Nagisa Munekata and Tetsuo Ono

Abstract: Based on the assumption that composers compose with specific “intentions” in mind, we have conducted experiments to compare the “impressions” perceived by individual listeners with those “intentions” of the composer. We recorded physiological signals (skin conductance and finger tip temperature) of both the composer and listeners as they listened to the same music. Listener data was then cumulated and averaged for each song and compared to the data of the composer. Overall tendencies in physiological data, as well as a separate survey taken regarding emotions conveyed in the music, showed similarities between composer “intentions” and listener “impressions”, indicating positive possibilities for using physiological data as an objective index of composers in future studies.

Area 19 - Devices

Short Papers
Paper Nr: 51
Title:

A Telerehabilitation System based on Wireless Motion Capture Sensors

Authors:

Pedro Macedo, José A. Afonso, Luis A. Rocha and Ricardo Simoes

Abstract: The constant growth of the elderly population in the world creates new challenges and opportunities in health care systems. New technological solutions have to be found in order to meet the needs and demands of our aging society. The welfare and quality of life of the elderly population must be a priority. Continuous physical activity will play an important role, due to the increase of the retirement age. However, physiotherapy can be expensive, even when the desire movements are autonomous and simple, also requires people to move to rehabilitation centres. Within this context, this paper describes the development and preliminary tests of a wireless sensor network, based on wearable inertial and magnetic sensors, applied to the capture of human motion. This will enable a personalized home-based rehabilitation system for the elderly or people in remote physical locations.

Area 20 - Methodologies and Methods

Short Papers
Paper Nr: 52
Title:

Towards an Automatic Motion Coaching System - Feedback Techniques for Different Types of Motion Errors

Authors:

Norimichi Ukita, Daniel Kaulen and Carsten Röcker

Abstract: The development of a widely applicable automatic motion coaching system requires one to address a lot of issues including motion capturing, motion analysis and comparison, error detection as well as error feedback. In order to cope with this complexity, most existing approaches focus on a specific motion sequence or exercise. As a first step towards the development of a more generic system, this paper systematically analyzes different error and feedback types. A prototype of a feedback system that addresses multiple modalities is presented. The system allows to evaluate the applicability of the proposed feedback techniques for arbitrary types of motions in a next step.

Paper Nr: 54
Title:

Effectiveness of Three-Dimensional Kinematic Biofeedback on the Performance of Scapula-focused Exercises

Authors:

Ana Antunes, Inês Filipe, Sara Cordeiro, Joana Rosa, Filomena Carnide and Ricardo Matias

Abstract: Three-dimensional (3D) kinematic biofeedback can help identify scapular movement disorders and assist the subjects' motor relearning process by facilitating changes in physiological and biomechanical function through real-time knowledge of performance and result during or immediately after a task execution. This study assessed the effectiveness of 3D kinematic biofeedback on the quality of the scapula-focused exercises execution, and motor learning transfer during shoulder flexion and a daily activity. Thirty healthy adults with no history of shoulder pain or dysfunction were randomly distributed into two groups. Skin-mounted sensors allowed tracking of the thorax, scapula and humerus, and scapulothoracic and glenohumeral 3D angles were computed after reconstructing upper-extremity motions during daily activities and exercises for different phases of a motor relearning process. The results of this study demonstrate that the execution quality of scapula-focused exercises benefits of real-time 3D kinematic biofeedback and that transfer of learning occurs with a specific motor training intervention.

Area 21 - Devices

Posters
Paper Nr: 39
Title:

Physiological Signal Processing for Emotional Feature Extraction

Authors:

Peng Wu, Dongmei Jiang and Hichem Sahli

Abstract: This paper introduces new approaches of physiological signal processing prior to feature extraction from electrocardiogram (ECG) and electromyography (EMG). Firstly a new signal denoising approach based on the Empirical mode decomposition (EMD) is presented. The EMD can decompose the noisy signal into a number of Intrinsic Mode Functions (IMFs). The proposed algorithm estimates the noise level of each IMF. Experiments show that the proposed EMD-based method provides better denoising results compared to state-of-art. In addition, a real-time QRS detection approach is proposed to be directly applied on the noisy ECG signals. Moreover, an adaptive thresholding approach is employed for the EMG segmentation. Both approaches are validated using synthetic and real physiological data resulting in good performances.

Area 22 - Human Factors

Posters
Paper Nr: 40
Title:

Human Rating of Emotional Expressions - Scales vs. Preferences

Authors:

Marco Pasch, Andrea Kleinsmith and Monica Landoni

Abstract: Human ratings of emotional expressions are the foundation for building and training automatic affect recognition systems. We compare two rating schemes for labeling emotional expressions: likert scales and pair-wise preferences. A statistical analysis shows that while there is a strong correlation between the two schemes, there are also frequent mismatches. Our findings indicate that the schemes perform differently well per affect label. We discuss reasons for this and outline planned future work based on the findings.

Paper Nr: 43
Title:

Relationship between Affective Dimensions and Physiological Responses Induced by Emotional Stimuli - Base on Affective Dimensions: Arousal, Valence, Intensity and Approach

Authors:

Eun-Hye Jang, Mi-Sook Park, Byoung-Jun Park, Sang-Hyeob Kim, Myung-Ae Chung and Jin-Hun Sohn

Abstract: In HCI, emotion recognition using physiological signals have been noticed lately because physiological signals can be simply acquired with some sensors and are less sensitive to social and cultural difference, in particular, there is strong correlation between human emotional states and physiological reactions. We have investigated the relation between affective dimensions, i.e., arousal, valence, intensity and approach, and physiological responses such as electrocardiograph (ECG), electrodermal activity (EDA), skin temperature (SKT), and photoplethysmograph (PPG). Three hundred college students participated in the experiment. To successfully provoke basic emotions (anger, fear, sadness, boredom, interest, surprise, joy, pain, and neutral), emotion-provoking film clips were excerpted for each target emotion. Physiological signals (ECG, EDA, PPG and SKT) as emotional responses were measured during participants’ exposure to emotional stimuli and participants were asked to rate the specific emotions they had experienced on four affective dimensions, valence, arousal, intensity and approach. The result showed that there are correlations between affective dimensions and physiological responses. Contrary to valence and approach, arousal and intensity were positively related to heart rate (HR), skin conductance level (SCL) and skin conductance response (SCR), and showed negative relation to BVP and PTT. Our result suggests an availability of physiological signals for emotion recognition in HCI and can be helpful to provide the basis for the emotion recognition technique in HCI.

Area 23 - Devices

Posters
Paper Nr: 53
Title:

A Multimodal Low-cost Platform for Acquisition of Electrophysiological Signals Interfacing with Portable Devices

Authors:

A. Santos Ribeiro, D. Salvado, G. Evans, J. Soares Augusto and H. A. Ferreira

Abstract: Advances in low-voltage integrated circuits have enabled the development of low-cost, low-power, and downsized portable instrumentation. In the biomedical field, mobile sensing platforms provide an efficient way to monitor the physical condition of a subject. Moreover, these platforms provide an input for human-computer interaction. We developed a low-cost platform that can be adapted to acquire different electrophysiological signals, and interface with portable devices for storing, processing, and displaying of data. The developed platform was used to acquire electrocardiography (ECG), electromyography (EMG), electroencephalography (EEG), and electrooculography (EOG) signals, and the results were compared with signals obtained with the benchmark BIOPAC system. For the same frequency bands, results show that our portable platform was able to acquire electrophysiological signals with similar accuracy as those acquired with the BIOPAC system. Due to its simplicity, low-cost design, and easy implementation, the developed platform suits researchers, developers, and hobbyists, in the fields of physiological monitoring, human-computer interaction, and perceptual computing.

Area 24 - Applications

Full Papers
Paper Nr: 13
Title:

Influence of Electric Bicycle Usage on Biker Effort - On-road Monitoring Application in Lisbon, Portugal

Authors:

Magno Mendes, Gonçalo Duarte and Patricia Baptista

Abstract: Bicycle use in urban environments is an alternative mobility option, which enables people to travel longer, faster and with less effort than walking, with low environmental impacts. The use of electric bicycles (EB) has risen as another possibility to promote a more efficient transportation use. However, the quantification of the real impacts for the biker of shifting from conventional (CB) to EB is not yet quantified. This research work aims at estimating the impacts on physiological signals, namely, on heart rate, from using EB instead of CB, using a suitable methodology for on-road bio-signals data analysis. The on-road monitoring of 6 bikers, 2 routes and 3 bicycles in Lisbon presented a 57% average reduction in HR variation from using EB, since under high power demanding situations, the electric motor attenuates human effort. It was also possible to estimate the energy expenditure associated to the human effort that results from using the bicycles. For the CB the total energy spent reaches ≈70 Wh/km, while the EB presents ≈51 Wh/km of human energy (28% lower than the CB) and ≈9 Wh/km of electricity consumption, resulting in a total of ≈60 Wh/km. Consequently, the total energy per km is 14% lower in the EB compared to the CB.

Paper Nr: 18
Title:

Experimental Study and Evaluation of Paper-based Inkjet Electrodes for ECG Signal Acquisition

Authors:

Ana Priscila Alves, João Martins, Hugo Plácido da Silva, André Lourenço, Ana Fred and Hugo Ferreira

Abstract: Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices.

Short Papers
Paper Nr: 30
Title:

Mapping User Engagement to States of Affect via an Unobtrusive Biofeedback Device - A Dynamic Visualization of Real-time Assessment

Authors:

Anthony Psaltis, Charalampos Rizopoulos and Constantinos Mourlas

Abstract: The elicitation of affect can be regarded as an influencing factor upon a person’s cognition, emotional state, mood, attention and motivation. It is also recognizable as an inhibited physiological process expressed by the human brain as induced or suppressed hormonal and neural stimulation that subsequently instigates a physical and mental level of attentiveness attractiveness or aversiveness. Physical reactions to emotion causing events and stimuli in affective computing are classified by direct mapping of facial and postural expressions to corresponding patterns, by using visual and postural observation methods. Despite the fact that physiological assessment is generally more reliable and less error-prone, a higher amount of research has been devoted to visual and postural methods due to the greater complexity and specific knowledge requirements of the former. Concentrating more on the physiological aspect of assessing affect, we have developed a biofeedback device, sensing reactions instigated by emotion-causing events and results have been assessed in real-time using suitable visualization methods. In previous attempts to acquire this type of measurements, human subjects were physically and psychologically impaired by the electrodes and wiring attachments used for the acquisition of signals and therefore validity of data was to some extent in question. In order to achieve an uncompromising assessment environment we designed a system that acquires heart rate and stress measurements via an ordinarily looking computer mouse. Certain combinations of heart rate precipitation and tonic level / phasic response of stress levels were investigated as reactions to emotion-inducing events. Corresponding patterns of physiological measurements to a real time affect allocation model have reached interesting correlations of events with respective states of engagement to an impressive degree of coincidence.

Paper Nr: 31
Title:

ExciTube - Video Player for Sharing Viewer’s Excitement

Authors:

Takumi Shirokura, Nagisa Munekata and Tetsuo Ono

Abstract: We can share non-verbal emotional experiences, such as excitement and pleasure, by watching movies and sports events with others, like our friends and family. These shared experiences are thought to enhance excitement and pleasure compared to when watching videos alone. Our research provides this shared experience on the internet by sharing the viewer's excitement with others while watching videos that are on the web. We studied the relationship between users’ excitement while watching videos on the web and their impressions of those videos. Here, we introduce a video player called ExciTube that allows users to share their excitement and view other users’ excitement as visual information alongside the video they are watching. The user’s excitement is expressed and shared by using avatars. We carried out user-involved demonstrations of ExciTube at our laboratory and at a Japanese domestic Computer Entertainment Developers Conference, and confirmed that people did enjoy using the system and felt other people’s sense of excitement.

Paper Nr: 37
Title:

The Role of Personalization and Multiple EEG and Sound Features Selection in Real Time Sonification for Neurofeedback

Authors:

S. Mealla, A. Oliveira, X. Marimon, T. Steffert, S. Jordà and A. Väljamäe

Abstract: The field of physiology-based interaction and monitoring is developing at a fast pace. Emerging applications like fatigue monitoring often use sound to convey complex dynamics of biological signals and to provide an alternative, non-visual information channel. Most Physiology-to-Sound mappings in such auditory displays do not allow customization by the end-users. We designed a new sonification system that can be used for extracting, processing and displaying Electroencephalography data (EEG) with different sonification strategies. The system was validated with four user groups performing alpha/theta neurofeedback training (a/t) for relaxation that varied in feedback personalization (Personalized/Fixed) and a number of sonified EEG features (Single/Multiple). The groups with personalized feedback performed significantly better in their training than fixed mappings groups, as shown by both subjective ratings and physiological indices. Additionally, the higher number of sonified EEG features resulted in deeper relaxation than when training with single feature feedback. Our results demonstrate the importance of adaptation and personaliziation of EEG sonification according to particular applications, in our case, to a/t neurofeedback. Our experimental approach shows how user performance can be used for validating different sonification strategies.

Paper Nr: 45
Title:

Arduino based System for Indoor and Outdoor ECG Monitoring - Functions and Extended User Model Ontology

Authors:

Carmelo Pino and Alfio Costanzo

Abstract: In this paper a system for monitoring the environment and biometric parameters like ECG for cardiac patients is presented. Monitoring Health Environment can be considered important like monitoring the patient in direct way. In this paper we propose an architecture consisting of a sensors network to monitor the patient environment in conjunction with other biometric parameters like ECG with the aim to control the health status in outdoor and indoor conditions. The monitoring system makes use of different sensors such as: oxygen level, air quality, humidity, temperature, ECG, integrated with an Arduino controller. The observed data are sent via GPRS or Wi-Fi to a server to activate the regulation of the environment conditions. Patient environment and health status can be monitored in remote way by mobile thanks to a specific App.

Posters
Paper Nr: 1
Title:

A Survey of ICT Tools for Communication Development in Children with ASD

Authors:

Margarida Lucas da Silva and Daniel Gonçalves

Abstract: Several studies using Information and Communication Technologies (ICT) have been carried out over the years, trying to solve problems related with multiple dimensions of the limitations faced by children with Autism Spectrum Disorders (ASD). It is not yet possible to conclude that the use of ICT is more beneficial than the use of alternative or traditional educational approaches for children with ASD. In this paper we are going to look at several studies related with communication development in children with ASD, with the purpose of understanding the approaches available and some of their possible results.

Paper Nr: 7
Title:

Promoting Visual Biofeedback through a Medical Device for Physical Therapy and Physical and Rehabilitative Medicine

Authors:

Carlos Alcobia, Rui Costa, Luis Ferreira and Pedro Mendes

Abstract: The present paper synthesises the development of a medical device which promotes visual biofeedback for Physical Therapy and Physical and Rehabilitative Medicine. After the identification of a specific need, a solution extremely versatile with advantages for the patient and the health professional is presented. A brief reference to its technical development and its performance is presented, introducing the visual biofeedback interface and gathering a set of identified clinical applications. Finally, some possible further developments are listed.

Paper Nr: 8
Title:

Rapid Application Development to Create Proof-of-Concept Software Applications

Authors:

Margarida Lucas da Silva, Hugo Silva and Daniel Gonçalves

Abstract: Rapid application development is the best way to test prototypes by giving a solid performance for user’s tests, while rapid application customization it is the best approach to easily test the user’s needs, such as children with autism spectrum disorders. In this paper we present a framework of a platform designed with these concepts in mind. This platform is a standalone multimedia and rich content software, targeted at students with special needs, that allows to easily expand the functionalities and create proof-of-concept software applications.

Paper Nr: 46
Title:

An Arduino based Health Monitoring System for Elderly People Living at Home - Functions and Ontology

Authors:

Alfio Costanzo and Carmelo Pino

Abstract: In recent decades, people, especially the older ones, try to live at home in autonomous way. For this purpose it is useful to monitor their vital signs and the environment that surrounds them with the aim of activating suitable environment regulation and when needed to send alarms to family members, medical, or hospitals, according to the criticality of the subject. The paper aims at proposing a flexible and reliable monitoring system based on Arduino shields. The main feature of the system is that it allows the doctor and family members to monitor the patients at distance using their mobiles. A suitable communication with the first aid center is foreseen for a fast rescue of the patients in case of critical situations. The general user model ontology is used so that the personal data featuring the patients and the relevant context may be used by any diagnostic and first aid software, thus envisaging an open and interoperable health monitoring system for elderly people living at home.

Paper Nr: 49
Title:

ERP-based Speller with a New Paradigm

Authors:

Jin-Hun Sohn, Mi-Sook Park, Hye-Ryeon Yang, Young-Ji Eum and Jin-Sup Eom

Abstract: In most implementation of an ERP-based speller, standard row-column paradigm (RCP) was used. However, RCP is susceptible to adjacency-distraction errors because items in the same row or column of the target flash at the time of a half when the target item flashes. The adjacency-distraction errors could be reduced if the number of flanking items that flash with the target is diminished. This study presents a novel P300-based stimulus presentation called row-column-diagonal paradigm (RCDP) where characters on the main diagonal and the anti-diagonal in the matrix flash in addition to characters on the row and columns. In RCDP, items in the same row, column, main diagonal, and anti-diagonal of the target flashes at the time of a quarter when the target item flashes. Using a 6×6 matrix of alphanumeric characters and keyboard commands, ten college students used RCP and RCDP. Stepwise linear discriminant analysis (SWLDA) for the EEG signals recorded in calibration phases was used to calculate discrimininant function. By applying the discrimininant function to electroencephalography (EEG) signal recorded in the test phase, the probability whether the item was the target or not was evaluated. Average accuracy was 76.6% in RCP while 84.0% in RCDP. With RCP, most errors were occurred in the same row or column of the target; on the other hand, with RCDP in the same row, column, main diagonal, or anti-diagonal of the target. These findings indicate how RCDP reduces adjacency-distraction errors and might be able to contribute to develop more advanced stimulus presentation paradigm.