Search Results (33)

Detecting deceptive behaviour for surveillance and border protection is critical for a country’s security. With the advancement of technology in relation to sensors and artificial intelligence, recognising deceptive behaviour could be performed automatically. Following the success of affective computing in emotion recognition from verbal and nonverbal cues, we aim to apply a similar concept for deception detection. Recognising deceptive behaviour has been attempted; however, only a few studies have analysed this behaviour from gait and body movement. This research involves a multimodal approach for deception detection from gait, where we fuse features extracted from body movement behaviours from a video signal, acoustic features from walking steps from an audio signal, and the dynamics of walking movement using an accelerometer sensor. Using the video recording of walking from the Whodunnit deception dataset, which contains 49 subjects performing scenarios that elicit deceptive behaviour, we conduct multimodal two-category (guilty/not guilty) subject-independent classification. The classification results obtained reached an accuracy of up to 88% through feature fusion, with an average of 60% from both single and multimodal signals. Analysing body movement using single modality showed that the visual signal had the highest performance followed by the accelerometer and acoustic signals. Several fusion techniques were explored, including early, late, and hybrid fusion, where hybrid fusion not only achieved the highest classification results, but also increased the confidence of the results. Moreover, using a systematic framework for selecting the most distinguishing features of guilty gait behaviour, we were able to interpret the performance of our models. From these baseline results, we can conclude that pattern recognition techniques could help in characterising deceptive behaviour, where future work will focus on exploring the tuning and enhancement of the results and techniques. Full article

Technological progress has seamlessly integrated digital assistants into our everyday lives, sparking an interest in social robots that communicate through both verbal and non-verbal means. The potential of these robots to influence human behaviour and attitudes holds significant implications for fields such as healthcare, marketing, and promoting sustainability. This study investigates how the design and behavioural aspects of social robots affect their ability to persuade, drawing on principles from human interaction to enhance the quality of human–robot interactions. Conducted in three stages, the experiments involved 73 participants, offering a comprehensive view of human responses to robotic persuasion. Surprisingly, the findings reveal that individuals tend to be more receptive to a single robot than to groups of robots. Nao was identified as more effective and capable of persuasion than Pepper. This study shows that successful persuasion by robots depends on social influence, the robot’s appearance, and people’s past experiences with technology. Full article

Background: Attention deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterised by deficits in attention, hyperactivity, and impulsivity. Current treatments, such as stimulant medication and behavioural therapy, ameliorate symptoms but do not address the core cognitive dysfunctions. This study aimed to investigate the effects of two computerised neurocognitive training programs, attention functions training and executive functions training, in children with ADHD. Methods: Eighty children with ADHD (ages 8–13) were randomly assigned to one of three groups: Attention functions training (AFT), targeting sustained, selective-spatial, orienting, and executive attention; executive functions training (EFT), focusing on working memory, cognitive flexibility, and problem solving; or a passive control group. Training sessions were administered in small groups twice a week for nine weeks. Participants underwent comprehensive assessments of attention (Continuous Performance Test, Conjunctive Visual Search Task), executive functions (Corsi Block-Tapping Tasks), nonverbal reasoning (Raven’s Colored Progressive Matrices), parent-rated behavioural symptoms, and arithmetic performance at baseline, post-intervention, and follow-up. Results: The AFT group demonstrated significant improvements in sustained and selective-spatial attention, nonverbal reasoning, inattentive symptoms, and arithmetic performance, and most improvements persisted at follow-up. The EFT group showed gains in nonverbal reasoning and inattentive symptoms, although no improvements were documented in working memory or in parent ratings of executive functions. Conclusions: The AFT program that addressed core attentional functions in children with ADHD produced robust cognitive and behavioural benefits, whereas the EFT program yielded behavioural benefits and a limited improvement in executive functions. Future research should explore different training protocols for broader gains in executive functions. These findings support the potential of theory-driven, structured neurocognitive training targeting basic cognitive functions as an effective small-group intervention for ADHD. Full article

This paper compares three methods for evaluating computer-generated motion behaviour for animated characters: two commonly used direct rating methods and a newly designed questionnaire. The questionnaire is specifically designed to measure the human-likeness, appropriateness, and intelligibility of the generated motion. Furthermore, this study investigates the suitability of these evaluation tools for assessing subtle forms of human behaviour, such as the subdued motion cues shown when listening to someone. This paper reports six user studies, namely studies that directly rate the appropriateness and human-likeness of a computer character’s motion, along with studies that instead rely on a questionnaire to measure the quality of the motion. As test data, we used the motion generated by two generative models and recorded human gestures, which served as a gold standard. Our findings indicate that when evaluating gesturing motion, the direct rating of human-likeness and appropriateness is to be preferred over a questionnaire. However, when assessing the subtle motion of a computer character, even the direct rating method yields less conclusive results. Despite demonstrating high internal consistency, our questionnaire proves to be less sensitive than directly rating the quality of the motion. The results provide insights into the evaluation of human motion behaviour and highlight the complexities involved in capturing subtle nuances in nonverbal communication. These findings have implications for the development and improvement of motion generation models and can guide researchers in selecting appropriate evaluation methodologies for specific aspects of human behaviour. Full article

This paper investigates brain–behaviour associations between interictal epileptic discharges and cognitive performance in a population of children with self-limited focal epilepsy with centro-temporal spikes (SeLECTS). Sixteen patients with SeLECTS underwent an extensive neuropsychological assessment, including verbal short-term and episodic memory, non-verbal short-term memory, attentional abilities and executive function. Two quantitative EEG indices were analysed, i.e., the Spike Wave Index (SWI) and the Spike Wave Frequency (SWF), and one qualitative EEG index, i.e., the EEG score, was used to evaluate the spreading of focal SW to other parts of the brain. We investigated associations between EEG indices and neuropsychological performance with non-parametric Spearman correlation analyses, including correction for multiple comparisons. The results showed a significant negative correlation between (i) the awake EEG score and the Block Tapping Test, a visuo-spatial short-term memory task, and (ii) the sleep SWI and the Tower of London, a visuo-spatial planning task (p_corr < 0.05). These findings suggest that, in addition to the usual quantitative EEG indices, the EEG analysis should include the qualitative EEG score evaluating the spreading of focal SW to other parts of the brain and that neuropsychological assessment should include visuo-spatial skills. Full article

Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts. ECA dialogues have previously been designed to include relational cues to motivate patients to change their current behaviours and encourage adherence to a treatment plan. However, there is little understanding of who finds specific relational cues delivered by an ECA helpful or not. Drawing the literature together, we have categorised relational cues into empowering, working alliance, affirmative and social dialogue. In this study, we have embedded the dialogue of Alex, an ECA, to encourage healthy behaviours with all the relational cues (empathic Alex) or with none of the relational cues (neutral Alex). A total of 206 participants were randomly assigned to interact with either empathic or neutral Alex and were also asked to rate the helpfulness of selected relational cues. We explore if the perceived helpfulness of the relational cues is a good predictor of users’ intention to change the recommended health behaviours and/or development of a working alliance. Our models also investigate the impact of individual factors, including gender, age, culture and personality traits of the users. The idea is to establish whether a certain group of individuals having similarities in terms of individual factors found a particular cue or group of cues helpful. This will establish future versions of Alex and allow Alex to tailor its dialogue to specific groups, as well as help in building ECAs with multiple personalities and roles. Full article

According to the trait activation theory (TAT), personality characteristics are dormant until contextual elements stir them into action. Personality traits are expected to be activated in the context of abusive supervision. From this perspective, our paper examines whether abusive supervision affects organisational gossiping behaviour through the dark triad. To this end, this study examines the mediating effects of the dark triad on the relationship between abusive supervision and organisational gossip based on cross-sectional data gathered from two separate samples. Using the results from structural equation modelling, it is evident that abusive supervision activates the dark triad, and its context influences organisational gossip in line with the TAT. In addition, our results show that abusive supervision positively affects gossip for information gathering and relationship building, with the dark triad proving to be completely mediating. This finding implies that abusive supervision is a contextual factor, and as such, behaviours such as consistent ill treatment and non-violent, verbal or non-verbal hostile acts will have long-term and lasting effects on organisational communication in many organisations. This study offers significant policy implications concerning behavioural issues within education-centred organisations. Full article

A challenge in social marketing studies is the cognitive biases in consumers’ conscious and self-reported responses. To help address this concern, biometric techniques have been developed to obtain data from consumers’ implicit and non-verbal responses. A systematic literature review was conducted to explore biometric applications’ role in agri-food marketing to provide an integrated overview of this topic. A total of 55 original research articles and four review articles were identified, classified, and reviewed. It was found that there is a steady growth in the number of studies applying biometric approaches, with eye-tracking being the dominant method used to investigate consumers’ perceptions in the last decade. Most of the studies reviewed were conducted in Europe or the USA. Other biometric techniques used included facial expressions, heart rate, body temperature, and skin conductance. A wide range of scenarios concerning consumers’ purchase and consumption behaviour for agri-food products have been investigated using biometric-based techniques, indicating their broad applicability. Our findings suggest that biometric techniques are expanding for researchers in agri-food marketing, benefiting both academia and industry. Full article

Touch can have a strong effect on interactions between people, and as such, it is expected to be important to the interactions people have with robots. In an earlier work, we showed that the intensity of tactile interaction with a robot can change how much people are willing to take risks. This study further develops our understanding of the relationship between human risk-taking behaviour, the physiological responses by the user, and the intensity of the tactile interaction with a social robot. We used data collected with physiological sensors during the playing of a risk-taking game (the Balloon Analogue Risk Task, or BART). The results of a mixed-effects model were used as a baseline to predict risk-taking propensity from physiological measures, and these results were further improved through the use of two machine learning techniques—support vector regression (SVR) and multi-input convolutional multihead attention (MCMA)—to achieve low-latency risk-taking behaviour prediction during human–robot tactile interaction. The performance of the models was evaluated based on mean absolute error (MAE), root mean squared error (RMSE), and R squared score ($R^2$), which obtained the optimal result with MCMA yielding an MAE of 3.17, an RMSE of 4.38, and an $R^2$ of 0.93 compared with the baseline of 10.97 MAE, 14.73 RMSE, and 0.30 $R^2$. The results of this study offer new insights into the interplay between physiological data and the intensity of risk-taking behaviour in predicting human risk-taking behaviour during human–robot tactile interactions. This work illustrates that physiological activation and the intensity of tactile interaction play a prominent role in risk processing during human–robot tactile interaction and demonstrates that it is feasible to use human physiological data and behavioural data to predict risk-taking behaviour in human–robot tactile interaction. Full article

Recent studies state that, for a person with autism spectrum disorder, learning and improvement is often seen in environments where technological tools are involved. A robot is an excellent tool to be used in therapy and teaching. It can transform teaching methods, not just in the classrooms but also in the in-house clinical practices. With the rapid advancement in deep learning techniques, robots became more capable of handling human behaviour. In this paper, we present a cost-efficient, socially designed robot called ‘Tinku’, developed to assist in teaching special needs children. ‘Tinku’ is low cost but is full of features and has the ability to produce human-like expressions. Its design is inspired by the widely accepted animated character ‘WALL-E’. Its capabilities include offline speech processing and computer vision—we used light object detection models, such as Yolo v3-tiny and single shot detector (SSD)—for obstacle avoidance, non-verbal communication, expressing emotions in an anthropomorphic way, etc. It uses an onboard deep learning technique to localize the objects in the scene and uses the information for semantic perception. We have developed several lessons for training using these features. A sample lesson about brushing is discussed to show the robot’s capabilities. Tinku is cute, and loaded with lots of features, and the management of all the processes is mind-blowing. It is developed in the supervision of clinical experts and its condition for application is taken care of. A small survey on the appearance is also discussed. More importantly, it is tested on small children for the acceptance of the technology and compatibility in terms of voice interaction. It helps autistic kids using state-of-the-art deep learning models. Autism Spectral disorders are being increasingly identified today’s world. The studies show that children are prone to interact with technology more comfortably than a with human instructor. To fulfil this demand, we presented a cost-effective solution in the form of a robot with some common lessons for the training of an autism-affected child. Full article

In recent years, there have been many approaches to using robots to teach computer programming. In intelligent tutoring systems and computer-aided learning, there is also some research to show that affective feedback to the student increases learning efficiency. However, a few studies on the role of incorporating an emotional personality in the robot in robot-assisted learning have found different results. To explore this issue further, we conducted a pilot study to investigate the effect of positive verbal encouragement and non-verbal emotive behaviour of the Miro-E robot during a robot-assisted programming session. The participants were tasked to program the robot’s behaviour. In the experimental group, the robot monitored the participants’ emotional state via their facial expressions, and provided affective feedback to the participants after completing each task. In the control group, the robot responded in a neutral way. The participants filled out a questionnaire before and after the programming session. The results show a positive reaction of the participants to the robot and the exercise. Though the number of participants was small, as the experiment was conducted during the pandemic, a qualitative analysis of the data was carried out. We found that the greatest affective outcome of the session was for students who had little experience or interest in programming before. We also found that the affective expressions of the robot had a negative impact on its likeability, revealing vestiges of the uncanny valley effect. Full article

Background: Sex chromosome aneuploidies (SCAs) are a group of disorders characterised by an abnormal number of sex chromosomes. Collective prevalence rate of SCAs is estimated to be around 1 in 400–500 live births; sex chromosome trisomies (e.g., XXX, XXY, XYY) are most frequent, while tetra- and pentasomies (e.g., XXXX, XXXXX, XXXY, XXXXY) are rarer, and the most common is 48, XXYY syndrome. The presence of additional X and/or Y chromosomes is believed to cause neurodevelopmental differences, with increased risk for developmental delays, language-based learning disabilities, cognitive impairments, executive dysfunction, and behavioural and psychological disorders. Aim of the Study: Our review has the purpose of analysing the neurocognitive, linguistical and behavioural profile of patients affected by sex chromosomes supernumerary aneuploidies (tetrasomy and pentasomy) to better understand the specific areas of weakness, in order to provide specific rehabilitation therapy. Methods: The literature search was performed by two authors independently. We used MEDLINE, PubMed, and PsycINFO search engines to identify sources of interest, without year or language restrictions. At the end of an accurate selection, 16 articles fulfilled the inclusion and exclusion criteria. Results and Conclusions: International literature has described single aspects of the neuropsychological profile of 48, XXYY and 49, XXXXY patients. In 48, XXYY patients, various degrees of psychosocial/executive functioning issues have been reported and there is an increased frequency of behavioural problems in childhood. Developmental delay and behavioural problems are the most common presenting problems, even if anxiety, depression and oppositional defiant disorder are also reported. They also show generalized difficulties with socialization and communication. Cognitive abilities are lower in measures of verbal IQ than in measures of performance IQ. Visuospatial skills are a relative strength compared to verbal skills. In patients with 49, XXXXY, both intellectual and adaptive functioning skills fall into the disability range, with better non-verbal cognitive performance. Speech and language testing reveals more deficits in expressive language than receptive language and comprehension. Anxiety, thought problems, internalizing and externalizing problems, and deficits in social cognition and communication are reported. Behavioural symptoms lessen from school age to adolescence, with the exception of thought problems and anxiety. Individuals affected by sex chromosome aneuploidies show testosterone deficiency, microorchidism, lack of pubertal progression and infertility. Hormone replacement therapy (HRT) is usually recommended for these patients: different studies have found that testosterone-based HRT benefit a wide range of areas initiated in these disorders, affecting not only neuromotor, cognitive and behavioural profile but also structural anomalies of the brain (i.e., increase of volume of grey temporal lobe matter). In conclusion, further studies are needed to better understand the neuropsychological profile with a complete evaluation, including neurocognitive and psychosocial aspects and to establish the real impact of HRT on improving the cognitive and behavioural profile of these patients. Full article

Objective: Insomnia and daytime behavioral problems are common issues in pediatric autism spectrum disorder (ASD), yet specific underlying relationships with NonRapid Eye Movement sleep (NREM) and Rapid Eye Movement (REM) sleep architecture are understudied. We hypothesize that REM sleep alterations (REM%, REM EEG power) are associated with more internalizing behaviors and NREM sleep deficits (N3%; slow wave activity (SWA) 0.5–3 Hz EEG power) are associated with increased externalizing behaviors in children with ASD vs. typical developing controls (TD). Methods: In an age- and gender-matched pediatric cohort of n = 23 ASD and n = 20 TD participants, we collected macro/micro sleep architecture with overnight home polysomnogram and daytime behavior scores with Child Behavior Checklist (CBCL) scores. Results: Controlling for non-verbal IQ and medication use, ASD and TD children have similar REM and NREM sleep architecture. Only ASD children show positive relationships between REM%, REM theta power and REM beta power with internalizing scores. Only TD participants showed an inverse relationship between NREM SWA and externalizing scores. Conclusion: REM sleep measures reflect concerning internalizing behaviours in ASD and could serve as a biomarker for mood disorders in this population. While improving deep sleep may help externalizing behaviours in TD, we do not find evidence of this relationship in ASD. Full article

Yōkobo is a robject; it was designed using the principle of slow technology and it aims to strengthen the bond between members (e.g., a couple). It greets people at the entrance and mirrors their interactions and the environment around them. It was constructed by applying the notions of a human–robot–human interaction. Created by joint work between designers and engineers, the form factor (semi-abstract) and the behaviours (nonverbal) were iteratively formed from the early stage of the design process. Integrated into the smart home, Yōkobo uses expressive motion as a communication medium. Yōkobo was tested in our office to evaluate its technical robustness and motion perception ahead of future long-term experiments with the target population. The results show that Yōkobo can sustain long-term interaction and serve as a welcoming partner. Full article

Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster an elevated sense of social connectedness, non-contingent to occupying one’s personal space. Upon reflection of the newly adopted social distancing concept, we orchestrate a technological intervention, starting with interpersonal distance and sound at the core of interaction. Materialised as a set of sensory face-masks, a novel wearable system was developed and tested in the context of a live public performance from which we obtain the user’s individual perspectives and correlate this with patterns identified in the recorded data. We identify and discuss traits of the user’s behaviour that were accredited to the system’s influence and construct four fundamental design considerations for physically distanced sound interaction. The study concludes with essential technical reflections, accompanied by an adaptation for a pervasive sensory intervention that is finally deployed in an open public space. Full article