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Keywords = sign phonemes

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13 pages, 294 KiB  
Article
The Impact of COVID-19 on Neuropsychological and Emotional-Behavioural Development in a Group of 8- and 9-Year-Old Children
by Angelica Marfoli, Giulia Speziale, Gaia Del Prete-Ferrucci, Harlan Cole, Angelica De Sandi, Denise Mellace, Daniela Chieffo, Sergio Barbieri, Alberto Priori, Bernardo Dell’Osso, Gabriella Pravettoni and Roberta Ferrucci
J. Clin. Med. 2024, 13(16), 4768; https://doi.org/10.3390/jcm13164768 - 14 Aug 2024
Cited by 2 | Viewed by 2997
Abstract
Introduction: The rapid spread of the COVID-19 pandemic has had a significant impact on the psychological well-being of millions of people around the world, and even more so among children. Contracting SARS-CoV-2, resulting in home confinement and restrictions on daily and school [...] Read more.
Introduction: The rapid spread of the COVID-19 pandemic has had a significant impact on the psychological well-being of millions of people around the world, and even more so among children. Contracting SARS-CoV-2, resulting in home confinement and restrictions on daily and school activities, led to negative effects on the mental health of the paediatric population. Although children suffering from COVID-19 had milder general symptoms compared to adults, impairments in cognitive, neuropsychological, and emotional-behavioural development were noted. Objective: The main aim of the present study was to detect possible changes in the neuropsychological and emotional-behavioural development of children after infection with the SARS-CoV-2 virus. The second aim was to investigate possible relationships between cognitive abilities and psychosocial characteristics. Methods: A total of 40 patients aged 8–9 years were recruited and divided into two groups: children who contracted (CG) and did not contract (NCG) SARS-CoV-2. The BVN 5–11 (Neuropsychological evaluation battery for developmental age from 5 to 11 years) instrument was administered to assess attention, memory, verbal recall, planning, phonemics, and categorical fluency domains in the paediatric population. Data on changes in emotional-behavioural profile and daily activities were collected through a questionnaire to parents. Results: The Wilcoxon signed-rank test revealed a significant change in mood after the COVID-19 period only in the CG participants (p = 0.019). However, the neuropsychological performance of the two identified groups on BVN 5–11 sub-items was below the cutoff of clinical significance. Correlations were found between sub-items of the BVN 5–11 battery, extracurricular activities, and children’s psycho-motor development. Significant positive correlations were observed between Naming on visual presentation and Reading time (p = 0.006), backward digit span and time of motor activity (p = 0.009), Visual attention and Reading time (p = 0.048), and Phonemic fluency and time observed using devices (p = 0.030). Positive statistically significant correlations were also found between Mood and Free behaviour (p = 0.000), between Mood and Structured behaviour (p = 0.005), and between Mood and peer Interaction (p = 0.013). Conclusions: SARS-CoV-2 infection negatively affected the emotional development of children contracting the virus. The neuropsychological functioning of the paediatric population was influenced by psychosocial variables and time spent on daily activities, which played a protective role in children’s cognitive development. Full article
(This article belongs to the Special Issue Pediatrics and COVID-19)
12 pages, 3092 KiB  
Article
Sign Language Dataset for Automatic Motion Generation
by María Villa-Monedero, Manuel Gil-Martín, Daniel Sáez-Trigueros, Andrzej Pomirski and Rubén San-Segundo
J. Imaging 2023, 9(12), 262; https://doi.org/10.3390/jimaging9120262 - 27 Nov 2023
Cited by 6 | Viewed by 5622
Abstract
Several sign language datasets are available in the literature. Most of them are designed for sign language recognition and translation. This paper presents a new sign language dataset for automatic motion generation. This dataset includes phonemes for each sign (specified in HamNoSys, a [...] Read more.
Several sign language datasets are available in the literature. Most of them are designed for sign language recognition and translation. This paper presents a new sign language dataset for automatic motion generation. This dataset includes phonemes for each sign (specified in HamNoSys, a transcription system developed at the University of Hamburg, Hamburg, Germany) and the corresponding motion information. The motion information includes sign videos and the sequence of extracted landmarks associated with relevant points of the skeleton (including face, arms, hands, and fingers). The dataset includes signs from three different subjects in three different positions, performing 754 signs including the entire alphabet, numbers from 0 to 100, numbers for hour specification, months, and weekdays, and the most frequent signs used in Spanish Sign Language (LSE). In total, there are 6786 videos and their corresponding phonemes (HamNoSys annotations). From each video, a sequence of landmarks was extracted using MediaPipe. The dataset allows training an automatic system for motion generation from sign language phonemes. This paper also presents preliminary results in motion generation from sign phonemes obtaining a Dynamic Time Warping distance per frame of 0.37. Full article
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20 pages, 5465 KiB  
Article
Sign Language Motion Generation from Sign Characteristics
by Manuel Gil-Martín, María Villa-Monedero, Andrzej Pomirski, Daniel Sáez-Trigueros and Rubén San-Segundo
Sensors 2023, 23(23), 9365; https://doi.org/10.3390/s23239365 - 23 Nov 2023
Cited by 1 | Viewed by 2326
Abstract
This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign phonemes provide information about sign characteristics like hand [...] Read more.
This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign phonemes provide information about sign characteristics like hand configuration, localization, or movements. The use of sign phonemes is crucial for generating sign motion with a high level of details (including finger extensions and flexions). The transformer-based approach also includes a stop detection module for predicting the end of the generation process. Both aspects, motion generation and stop detection, are evaluated in detail. For motion generation, the dynamic time warping distance is used to compute the similarity between two landmarks sequences (ground truth and generated). The stop detection module is evaluated considering detection accuracy and ROC (receiver operating characteristic) curves. The paper proposes and evaluates several strategies to obtain the system configuration with the best performance. These strategies include different padding strategies, interpolation approaches, and data augmentation techniques. The best configuration of a fully automatic system obtains an average DTW distance per frame of 0.1057 and an area under the ROC curve (AUC) higher than 0.94. Full article
(This article belongs to the Section Intelligent Sensors)
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32 pages, 3301 KiB  
Review
The Neurological Basis of Developmental Dyslexia and Related Disorders: A Reappraisal of the Temporal Hypothesis, Twenty Years on
by Michel Habib
Brain Sci. 2021, 11(6), 708; https://doi.org/10.3390/brainsci11060708 - 27 May 2021
Cited by 31 | Viewed by 24752
Abstract
In a now-classic article published a couple of decades ago (Brain, 2000; 123: 2373–2399), I proposed an “extended temporal processing deficit hypothesis of dyslexia”, suggesting that a deficit in temporal processing could explain not only language-related peculiarities usually noticed in dyslexic children, but [...] Read more.
In a now-classic article published a couple of decades ago (Brain, 2000; 123: 2373–2399), I proposed an “extended temporal processing deficit hypothesis of dyslexia”, suggesting that a deficit in temporal processing could explain not only language-related peculiarities usually noticed in dyslexic children, but also a wider range of symptoms related to impaired processing of time in general. In the present review paper, I will revisit this “historical” hypothesis both in the light of a new clinical perspective, including the central yet poorly explained notion of comorbidity, and also taking a new look at the most recent experimental work, mainly focusing on brain imaging data. First, consistent with daily clinical practice, I propose to distinguish three groups of children who fail to learn to read, of fairly equal occurrence, who share the same initial presentation (difficulty in mastering the rules of grapheme–phoneme correspondence) but with differing associated signs and/or comorbid conditions (language disorders in the first group, attentional deficits in the second one, and motor coordination problems in the last one), thus suggesting, at least in part, potentially different triggering mechanisms. It is then suggested, in the light of brain imaging information available to date, that the three main clinical presentations/associations of cognitive impairments that compromise reading skills acquisition correspond to three distinct patterns of miswiring or “disconnectivity” in specific brain networks which have in common their involvement in the process of learning and their heavy reliance on temporal features of information processing. With reference to the classic temporal processing deficit of dyslexia and to recent evidence of an inability of the dyslexic brain to achieve adequate coupling of oscillatory brain activity to the temporal features of external events, a general model is proposed according to which a common mechanism of temporal uncoupling between various disconnected—and/or mis-wired—processors may account for distinct forms of specific learning disorders, with reading impairment being a more or less constant feature. Finally, the potential therapeutic implications of such a view are considered, with special emphasis on methods seeking to enhance cross-modal connectivity between separate brain systems, including those using rhythmic and musical training in dyslexic patients. Full article
(This article belongs to the Special Issue Neurobiological Basis of Developmental Dyslexia)
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35 pages, 4227 KiB  
Article
Professional or Amateur? The Phonological Output Buffer as a Working Memory Operator
by Neta Haluts, Massimiliano Trippa, Naama Friedmann and Alessandro Treves
Entropy 2020, 22(6), 662; https://doi.org/10.3390/e22060662 - 15 Jun 2020
Cited by 10 | Viewed by 3923
Abstract
The Phonological Output Buffer (POB) is thought to be the stage in language production where phonemes are held in working memory and assembled into words. The neural implementation of the POB remains unclear despite a wealth of phenomenological data. Individuals with POB impairment [...] Read more.
The Phonological Output Buffer (POB) is thought to be the stage in language production where phonemes are held in working memory and assembled into words. The neural implementation of the POB remains unclear despite a wealth of phenomenological data. Individuals with POB impairment make phonological errors when they produce words and non-words, including phoneme omissions, insertions, transpositions, substitutions and perseverations. Errors can apply to different kinds and sizes of units, such as phonemes, number words, morphological affixes, and function words, and evidence from POB impairments suggests that units tend to substituted with units of the same kind—e.g., numbers with numbers and whole morphological affixes with other affixes. This suggests that different units are processed and stored in the POB in the same stage, but perhaps separately in different mini-stores. Further, similar impairments can affect the buffer used to produce Sign Language, which raises the question of whether it is instantiated in a distinct device with the same design. However, what appear as separate buffers may be distinct regions in the activity space of a single extended POB network, connected with a lexicon network. The self-consistency of this idea can be assessed by studying an autoassociative Potts network, as a model of memory storage distributed over several cortical areas, and testing whether the network can represent both units of word and signs, reflecting the types and patterns of errors made by individuals with POB impairment. Full article
(This article belongs to the Special Issue What Limits Working Memory Performance?)
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