17 research outputs found
A pilot study on the decoding of dynamic emotional expressions in major depressive disorder
No full textStudies investigating on the ability of depressed patients to decode emotional expressions have mostly exploited static stimuli (i.e., static facial expressions of basic emotions) showing that (even though this was not always the case) depressed patients are less accurate (in literature this is reported as a bias) in decoding negative emotions (fear, sadness and anger). However, static stimuli may not reflect the everyday situations and therefore this pilot study proposes to exploit dynamic stimuli involving both visual and auditory channels. We recruited 16 outpatients with Recurrent Major Depressive Disorder (MDD) matched with 16 healthy controls (HC). Their competence to decode emotional expressions was assessed through an emotion recognition task that included short audio (without video), video (without audio) and audio/video tracks. The results show that depressed patients are less accurate than controls, even though with no statistical significant difference, in decoding fear and anger, but not sadness, happiness and surprise where differences are significant. This is independent of the communication mode (either visual, auditory, or both, even though MDDs perform more worse than HCs in audio/video) and the severity of depressive symptoms, suggesting that the MDDs poorer decoding accuracy towards negative emotions is latent and emerges only during and after stressful events. The poorer decoding accuracy of happiness and (positive) surprise can be due to anhedonia
Age and culture effects on the ability to decode affect bursts
No full textThis paper investigates the ability of adolescents (aged 13–15 years) and young adults (aged 20–26 years) to decode affective bursts culturally situated in a different context (Francophone vs. South Italian). The effects of context show that Italian subjects perform poorly with respect to the Francophone ones revealing a significant native speaker advantage in decoding the selected affective bursts. In addition, adolescents perform better than young adults, particularly in the decoding and intensity ratings of affective bursts of happiness, pain, and pleasure suggesting an effect of age related to language expertise
Detection of Verbal and Nonverbal speech features as markers of Depression: results of manual analysis and automatic classification
No full textThe present PhD project was the result of a multidisciplinary work involving psychiatrists, computing scientists, social signal processing experts and psychology students with the aim to analyse verbal and nonverbal behaviour in patients affected by Depression. Collaborations with several Clinical Health Centers were established for the collection of a group of patients suffering from depressive disorders. Moreover, a group of healthy controls was collected as well. A collaboration with the School of Computing Science of Glasgow University was established with the aim to analysed the collected data.
Depression was selected for this study because is one of the most common mental disorder in the world (World Health Organization, 2017) associated with half of all suicides (Lecrubier, 2000). It requires prolonged and expensive medical treatments resulting into a significant burden for both patients and society (Olesen et al., 2012). The use of objective and reliable measurements of depressive symptoms can support the clinicians during the diagnosis reducing the risk of subjective biases and disorder misclassification (see discussion in Chapter 1) and doing the diagnosis in a quick and non-invasive way. Given this, the present PhD project proposes the investigation of verbal (i.e. speech content) and nonverbal (i.e. paralingiuistic features) behaviour in depressed patients to find several speech parameters that can be objective markers of depressive symptoms. The verbal and nonverbal behaviour are investigated through two kind of speech tasks: reading and spontaneous speech. Both manual features extraction and automatic classification approaches are used for this purpose. Differences between acute and remitted patients for prosodic and verbal features have been investigated as well. In addition, unlike other literature studies, in this project differences between subjects with and without Early Maladaptive Schema (EMS: Young et al., 2003) independently from the depressive symptoms, have been investigated with respect to both verbal and nonverbal behaviour.
The proposed analysis shows that patients differ from healthy subjects for several verbal and nonverbal features. Moreover, using both reading and spontaneous speech, it is possible to automatically detect Depression with a good accuracy level (from 68 to 76%). These results demonstrate that the investigation of speech features can be a useful instrument, in addition to the current self-reports and clinical interviews, for helping the diagnosis of depressive disorders.
Contrary to what was expected, patients in acute and remitted phase do not report differences regarding the nonverbal features and only few differences emerges for the verbal behaviour. At the same way, the automatic classification using paralinguistic features does not work well for the discrimination of subjects with and without EMS and only few differences between them have been found for the verbal behaviour. Possible explanations and limitations of these results will be discussed
How major depressive disorder affects the ability to decode multimodal dynamic emotional stimuli
No full textMost studies investigating the processing of emotions in depressed patients reported impairments in the decoding of negative emotions. However, these studies adopted static stimuli (mostly stereotypical facial expressions corresponding to basic emotions) which do not reflect the way people experience emotions in everyday life. For this reason, this work proposes to investigate the decoding of emotional expressions in patients affected by Recurrent Major Depressive Disorder (RMDDs) using dynamic audio/video stimuli. RMDDs’ performance is compared with the performance of patients with Adjustment Disorder with Depressed Mood (ADs) and healthy (HCs) subjects. The experiments involve 27 RMDDs (16 with acute depression - RMDD-A, and 11 in a compensation phase - RMDD-C), 16 ADs and 16 HCs. The ability to decode emotional expressions is assessed through an emotion recognition task based on short audio (without video), video (without audio) and audio/video clips. The results show that AD patients are significantly less accurate than HCs in decoding fear, anger, happiness, surprise and sadness. RMDD-As with acute depression are significantly less accurate than HCs in decoding happiness, sadness and surprise. Finally, no significant differences were found between HCs and RMDD-Cs in a compensation phase. The different communication channels and the types of emotion play a significant role in limiting the decoding accuracy
Effects of gender and luminance backgrounds on the recognition of neutral facial expressions
No full textIn this study we challenged the universal view of facial emotion perception evaluating the effects of gender and different luminance backgrounds on the recognition accuracy of neutral facial expressions. To this aim, we applied the Ekman standard paradigm for assessing the human ability to decode neutral facial expressions reproduced on black, white and grey backgrounds and portrayed by male and female actors. The exploited stimuli consisted of 10 different neutral faces (5 females) selected from the Dutch Radboud database (Langner et al. Cogn Emot, 2010 [21]) where luminance backgrounds were changed in black, grey and white. The resulted 30 stimuli were assessed by 31 subjects (16 females) who were asked to tag each of them with one of the six primary emotion labels. The data analysis demonstrates a significant gender effect where neutral male faces are less accurately decoded than females ones. On the other hand, no effects of luminance backgrounds have been identified
How Traders’ Appearances and Moral Descriptions Influence Receivers’ Choices in the Ultimatum Game.
No full textThis work reports on a series of experiments involving 960 participants (aged between 20-30 years and equally balanced by gender), asked to play the receiver role in a modified version of the Ultimatum Game, where together with information on the offer's fairness (e.g. 40 (fair) vs 10 (unfair) of 100 euros), a photo depicted the trader's appearance (trustworthy vs. untrustworthy) and a text provided his moral description (honest vs. dishonest). Receivers were asked to motivate their decision in connection with the appearance, moral judgment, and fairness of the offer, and report on how these variables affected their emotional feelings. Data analysis shows that, in all conditions containing a fair offer, the trader's appearance plays a significant role in the receivers' decisions in terms of acceptance rate. Moral descriptions play a significant role only in conditions containing an unfair offer. However, when asked to motivate their choices, subjects do not feel the interference of the social appearance, rather they provide more or less equal number of motivations with reference to the amount of offers and moral judgments. As for the emotions driving their decisions, non-converging feelings are observed both at intra and inter group level. © 2017 IEEE.PublishedBoston, MA, USA1VV. Altr
Handwriting and drawing features for detecting negative moods
No full textIn order to provide support to the implementation of on-line and remote systems for the early detection of interactional disorders, this paper reports on the exploitation of handwriting and drawing features for detecting negative moods. The features are collected from depressed, stressed, and anxious subjects, assessed with DASS-42, and matched by age and gender with handwriting and drawing features of typically ones. Mixed ANOVA analyses, based on a binary categorization of the groups, reveal significant differences among features collected from subjects with negative moods with respect to the control group depending on the involved exercises and features categories (in time or frequency of the considered events). In addition, the paper reports the description of a large database of handwriting and drawing features collected from 240 subjects
Age and Culture Effects on the Ability to Decode Affect Bursts
No full textThis paper investigates the ability of adolescents (aged 13–15 years) and young adults (aged 20–26 years) to decode affective bursts culturally situated in a different context (Francophone vs. South Italian). The effects of context show that Italian subjects perform poorly with respect to the Francophone ones revealing a significant native speaker advantage in decoding the selected affective bursts. In addition, adolescents perform better than young adults, particularly in the decoding and intensity ratings of affective bursts of happiness, pain, and pleasure suggesting an effect of age related to language expertise.Published1TM. Formazion
