{"title":"What Could a Body Tell a Social Robot that It Does Not Know?","authors":"Dennis Küster, Arvid Kappas","doi":"10.5220/0004892503580367","DOIUrl":"https://doi.org/10.5220/0004892503580367","url":null,"abstract":"Humans are extremely efficient in interacting with each other. They not only follow goals to exchange information, but modulate the interaction based on nonverbal cues, knowledge about situational context, and person information in real time. What comes so easy to humans poses a formidable challenge for artificial systems, such as social robots. Providing such systems with sophisticated sensor data that includes expressive behavior and physiological changes of their interaction partner holds much promise, but there is also reason to be skeptical. We will discuss issues of specificity and stability of responses with view to different levels of context.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125160648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Near Infrared Spectroscopy to Index Temporal Changes in Affect in Realistic Human-robot Interactions","authors":"M. Strait, Matthias Scheutz","doi":"10.5220/0004902203850392","DOIUrl":"https://doi.org/10.5220/0004902203850392","url":null,"abstract":"Recent work in HRI found that prefrontal hemodynamic activity correlated with participants’ aversions to certain robots. Using a combination of brain-based objective measures and survey-based subjective measures, it was shown that increasing the presence (co-located vs. remote interaction) and human-likeness of the robot engaged greater neural activity in the prefrontal cortex and severely decreased preferences for future interactions. The results of this study suggest that brain-based measures may be able to capture participants’ affective responses (aversion vs. affinity), and in a variety of interaction settings. However, the brain-based evidence of this work is limited to temporally-brief (6-second) post-interaction samples. Hence, it remains unknown whether such measures can capture affective responses over the course of the interactions (rather than post-hoc). Here we extend the previous analysis to look at changes in brain activity over the time course of more realistic human-robot interactions. In particular, we replicate the previous findings, and moreover find qualitative evidence suggesting the measurability of fluctuations in affect over the course of the full","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128519817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Physiological Signals in Driving Scenario - How Heart Rate and Skin Conductance Reveal Different Aspects of Driver's Cognitive Load","authors":"T. Dang, A. Tapus","doi":"10.5220/0004901203780384","DOIUrl":"https://doi.org/10.5220/0004901203780384","url":null,"abstract":"Driver’s cognitive load has always been associated with the driver’s heart rate activity and his/her skin conductance activity. However, what aspects of cognitive load that these signals relate to have never been clearly studied. This paper presents our preliminary results about the relationship between the different physiological signals (heart rate and skin conductance) and the driver’s cognitive load. Via one experiment with simulated car driving environment and one experiment in real flying environment, our data suggests that subjects’ heart rate relates to the number of events to be processed by the human driver while the skin conductance relates to the novelty of the driving task. Given the small population involved in these experiments, tests on more subjects are planned and reported in the future.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133144255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Physiological Signal Processing for Emotional Feature Extraction","authors":"Peng Wu, D. Jiang, H. Sahli","doi":"10.5220/0004727500400047","DOIUrl":"https://doi.org/10.5220/0004727500400047","url":null,"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.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124096901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rapid Application Development to Create Proof-of-Concept Software Applications","authors":"M. Silva, Hugo Silva, Daniel Gonçalves","doi":"10.5220/0004698202990306","DOIUrl":"https://doi.org/10.5220/0004698202990306","url":null,"abstract":"Rapid application development are 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","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133095782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
John Edison Muñoz Cardona, A. Gonçalves, Tatiana Vieira, D. Cró, Yoram Chisik, S. Badia
{"title":"Space Connection - A Multiplayer Collaborative Biofeedback Game to Promote Empathy in Teenagers: A Feasibility Study","authors":"John Edison Muñoz Cardona, A. Gonçalves, Tatiana Vieira, D. Cró, Yoram Chisik, S. Badia","doi":"10.5220/0005948400880097","DOIUrl":"https://doi.org/10.5220/0005948400880097","url":null,"abstract":"Biofeedback videogames are physiologically driven games that offer opportunities to individually improve emotional self-regulation and produce mental and physical health benefits. To investigate the feasibility of a novel collaborative multiplayer methodology, we created Space Connection, a videogame to promote empathy in teenagers. Space Connection depicts a futuristic adventure aboard a spaceship in which players have to jointly use their powers to solve a set of physics-based puzzles. The game relies on the use of physiological self-regulation to activate the playing partner powers. Using a low-cost brain computer interface and a respiration rate sensor we provided players with two game powers, namely telekinesis and timemanipulation which are mapped to changes in attention and relaxation. In this paper we describe the game mechanics in three different scenarios: i) the cryogenic room, ii) the space ship corridor and iii) the cargo hold. Finally, we performed a feasibility study with 10 users (aged 22.2 ± 5.6) to evaluate the game experience. Results revealed high scores in enjoyment and empathy but low scores on interface control. Our preliminary data supports the use of novel biofeedback strategies combined with videogames to promote positive emotions and incentive collaboration and teamwork.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131361354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NeuRow: An Immersive VR Environment for Motor-Imagery Training with the Use of Brain-Computer Interfaces and Vibrotactile Feedback","authors":"A. Vourvopoulos, André Ferreira, S. Badia","doi":"10.5220/0005939400430053","DOIUrl":"https://doi.org/10.5220/0005939400430053","url":null,"abstract":"Motor-Imagery offers a solid foundation for the development of Brain-Computer Interfaces (BCIs), capable of direct brain-to-computer communication but also effective in alleviating neurological impairments. The fusion of BCIs with Virtual Reality (VR) allowed the enhancement of the field of virtual rehabilitation by including patients with low-level of motor control with limited access to treatment. BCI-VR technology has pushed research towards finding new solutions for better and reliable BCI control. Based on our previous work, we have developed NeuRow, a novel multiplatform prototype that makes use of multimodal feedback in an immersive VR environment delivered through a state-of-the-art Head Mounted Display (HMD). In this article we present the system design and development, including important features for creating a closed neurofeedback loop in an implicit manner, and preliminary data on user performance and user acceptance of","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125947518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Revealing Psychophysiology and Emotions through Thermal Infrared Imaging","authors":"A. Merla","doi":"10.5220/0004900803680377","DOIUrl":"https://doi.org/10.5220/0004900803680377","url":null,"abstract":"Thermal infrared imaging has been proposed as a tool for the non-invasive and contact-less evaluation of vital signs, psychophysiological responses and states. Several applications have been so far developed in many diversified fields, like social and developmental psychology, psychometrics, human-computer interaction, continuous monitoring of vital signs, stress and, even, deception detection. Thermal infrared imaging has been poorly exploited in the field of human-robot interaction. Therefore, the state of the art of thermal infrared imaging in computational physiology and psychophysiology is discussed in order to provide insights about its potentialities and limits for human-robot interaction and applications with","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121729430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of a Real-Time Psychophysiological Feedback, Its Display Format and Reliability on Cognitive Workload and Performance","authors":"Sami Lini, Lise Hannotte, Margot Beugniot","doi":"10.5220/0005939500750079","DOIUrl":"https://doi.org/10.5220/0005939500750079","url":null,"abstract":"For a long time, literature has identified some psychophysiological metrics that proved reliable to assess cognitive states in controlled conditions. Smaller, more reliable and more affordable sensors made the industrial community plan to design systems that would adapt themselves to the ability of their users to operate them. Thus an important human factors question must be asked: what is the impact of such a feedback on users’ performance and cognitive workload? Does the display format of this feedback have an influence over subjects? What if the feedback provides erroneous data? We designed a protocol to compare the influence of providing a cognitive load assessment gauge versus raw data versus no feedback in a Multiple Objects Tracking task. Reliability of this feedback was also evaluated. Performance in a dual task paradigm, pupil dilation and questionnaire were used to assess cognitive load. Trials duration and learning effect were used as control results. Raw feedback showed a negative effect while low reliability showed inconsistent results.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129949363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Matthews, Saeed Abdullah, Geri Gay, Tanzeem Choudhury
{"title":"Detecting and Capitalizing on Physiological Dimensions of Psychiatric Illness","authors":"M. Matthews, Saeed Abdullah, Geri Gay, Tanzeem Choudhury","doi":"10.5220/0005952600980104","DOIUrl":"https://doi.org/10.5220/0005952600980104","url":null,"abstract":"Serious mental illnesses, including bipolar disorders (BD), account for a large share of the worldwide healthcare burden—estimated at $62.7B in the U.S. alone. Bipolar disorders represent a family of common, lifelong illnesses associated with poor functional and clinical outcomes, high suicide rates, and huge societal costs. Interpersonal and Social Rhythm Therapy (IPSRT), a validated treatment for BD, helps patients lead lives characterized by greater stability of daily rhythms, using a 5 item paper-and-pencil self-monitoring instrument called the Social Rhythm Metric (SRM). IPSRT has been shown to improve patient outcomes, yet many patients struggle to monitor their daily routine or even access the treatment. In this paper we describe how biological characteristics of bipolar disorder can be taken into consideration when developing systems to detect and stabilize mood episodes. We describe the co-design of MoodRhythm, a smartphone and web app, with patients and therapists. It is designed to support patients in tracking their health passively and actively over a long period of time. MoodRhythm uses the phone’s onboard sensors to automatically track sleep and social activity patterns. We report results of a small clinical pilot with experienced IPSRT clinicians and patients with bipolar disorder and finish by describing the role physiological computing could have not just in monitoring psychiatric illnesses according to existing broad categories of diagnosis but in helping radically tailor diagnoses to each individual patient and develop interventions that take advantage of idiosyncratic characteristics of each person’s illness in order to increase patient engagement in and adherence to treatment.","PeriodicalId":326453,"journal":{"name":"International Conference on Physiological Computing Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130006424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}