Abstract
Fragile X syndrome (FXS) and Rett syndrome (RTT) are developmental disorders currently not diagnosed before toddlerhood. Even though speech-language deficits are among the key symptoms of ...both conditions, little is known about infant vocalisation acoustics for an automatic earlier identification of affected individuals. To bridge this gap, we applied intelligent audio analysis methodology to a compact dataset of 4454 home-recorded vocalisations of 3 individuals with FXS and 3 individuals with RTT aged 6 to 11 months, as well as 6 age- and gender-matched typically developing controls (TD). On the basis of a standardised set of 88 acoustic features, we trained linear kernel support vector machines to evaluate the feasibility of automatic classification of (a) FXS vs TD, (b) RTT vs TD, (c) atypical development (FXS+RTT) vs TD, and (d) FXS vs RTT vs TD. In paradigms (a)–(c), all infants were correctly classified; in paradigm (d), 9 of 12 were so. Spectral/cepstral and energy-related features were most relevant for classification across all paradigms. Despite the small sample size, this study reveals new insights into early vocalisation characteristics in FXS and RTT, and provides technical underpinnings for a future earlier identification of affected individuals, enabling earlier intervention and family counselling.
The past decade has evinced a boom of computer-based approaches to aid movement assessment in early infancy. Increasing interests have been dedicated to develop AI driven approaches to complement the ...classic Prechtl general movements assessment (GMA). This study proposes a novel machine learning algorithm to detect an age-specific movement pattern, the fidgety movements (FMs), in a prospectively collected sample of typically developing infants. Participants were recorded using a passive, single camera RGB video stream. The dataset of 2800 five-second snippets was annotated by two well-trained and experienced GMA assessors, with excellent inter- and intra-rater reliabilities. Using OpenPose, the infant full pose was recovered from the video stream in the form of a 25-points skeleton. This skeleton was used as input vector for a shallow multilayer neural network (SMNN). An ablation study was performed to justify the network's architecture and hyperparameters. We show for the first time that the SMNN is sufficient to discriminate fidgety from non-fidgety movements in a sample of age-specific typical movements with a classification accuracy of 88%. The computer-based solutions will complement original GMA to consistently perform accurate and efficient screening and diagnosis that may become universally accessible in daily clinical practice in the future.
The present study aimed to define differences between silent and oral reading with respect to spatial and temporal eye movement parameters. Eye movements of 22 German-speaking adolescents (14 ...females; mean age = 13;6 years;months) were recorded while reading an age-appropriate text silently and orally. Preschool cognitive abilities were assessed at the participants' age of 5;7 (years;months) using the Kaufman Assessment Battery for Children. The participants' reading speed and reading comprehension at the age of 13;6 (years;months) were determined using a standardized inventory to evaluate silent reading skills in German readers (Lesegeschwindigkeits- und -verständnistest für Klassen 6-12). The results show that (i) reading mode significantly influenced both spatial and temporal characteristics of eye movement patterns; (ii) articulation decreased the consistency of intraindividual reading performances with regard to a significant number of eye movement parameters; (iii) reading skills predicted the majority of eye movement parameters during silent reading, but influenced only a restricted number of eye movement parameters when reading orally; (iv) differences with respect to a subset of eye movement parameters increased with reading skills; (v) an overall preschool cognitive performance score predicted reading skills at the age of 13;6 (years;months), but not eye movement patterns during either silent or oral reading. However, we found a few significant correlations between preschool performances on subscales of sequential and simultaneous processing and eye movement parameters for both reading modes. Overall, the findings suggest that eye movement patterns depend on the reading mode. Preschool cognitive abilities were more closely related to eye movement patterns of oral than silent reading, while reading skills predicted eye movement patterns during silent reading, but less so during oral reading.
Prader-Willi syndrome (PWS) is a rare genetic disorder. Infants with PWS show a neurodevelopmental dysfunction which entails a delayed motor and language development, but studies on their spontaneous ...movements (i.e. general movements) or pre-linguistic speech-language development before 6 months of age are missing so far.
To describe early motor and pre-linguistic verbal development in an infant with PWS.
Prospective case report; in addition to the assessment of general movements and the concurrent movement repertoire, we report on early verbal forms, applying the Stark Assessment of Early Vocal Development-Revised.
General movements were abnormal on days 8 and 15. No fidgety movements were observed at 11 weeks; they only emerged at 17 weeks and lasted until at least 27 weeks post-term. The movement character was monotonous, and early motor milestones were only achieved with a delay. At 27 weeks the infant produced age-adequate types of vocalisations. However, none of the canonical-syllable vocalisations that typically emerge at that age were observed. Early vocalisations appeared monotonous and with a peculiarly harmonic structure.
Early motor and pre-linguistic verbal behaviours were monotonous in an infant with PWS throughout his first 6 months of life. This suggests that early signs of neurodevelopmental dysfunction (i.e. abnormal general movements) might already be diagnosed in infants with PWS during their first weeks of life, potentially enabling us to diagnose and intervene at an early stage.
In recent years, advancements in the field of artificial intelligence (AI) have impacted several areas of research and application. Besides more prominent examples like self-driving cars or media ...consumption algorithms, AI-based systems have further started to gain more and more popularity in the health care sector, however whilst being restrained by high requirements for accuracy, robustness, and explainability. Health-oriented AI research as a sub-field of digital health investigates a plethora of human-centered modalities. In this article, we address recent advances in the so far understudied but highly promising audio domain with a particular focus on speech data and present corresponding state-of-the-art technologies. Moreover, we give an excerpt of recent studies on the automatic audio-based detection of diseases ranging from acute and chronic respiratory diseases via psychiatric disorders to developmental disorders and neurodegenerative disorders. Our selection of presented literature shows that the recent success of deep learning methods in other fields of AI also more and more translates to the field of digital health, albeit expert-designed feature extractors and classical ML methodologies are still prominently used. Limiting factors, especially for speech-based disease detection systems, are related to the amount and diversity of available data, e. g., the number of patients and healthy controls as well as the underlying distribution of age, languages, and cultures. Finally, we contextualize and outline application scenarios of speech-based disease detection systems as supportive tools for health-care professionals under ethical consideration of privacy protection and faulty prediction.
Among ungulates, capital breeding males, especially in highly dimorphic species, support higher reproductive costs than females. Roe deer, a relatively monomorphic species, is defined as an ‘income ...breeder’, using a concurrent intake of energy from forage to pay for a reproductive attempt. In a Northern Apennines (Arezzo province, Tuscany, Central Italy) population, we detected sexual dimorphism in adult roe deer according to average body mass (males 11% heavier than females), mandible size (male mandibles are 2% longer than female ones), and tooth measurements (first lower molar 10% higher and mandible cheek teeth row 4% longer in males than in females, providing males with a larger surface for chewing). In our study, body mass and body condition of roe deer males decreased with increasing tooth wear as in females. However, males started losing weight at a lower tooth wear level than females; after losing about 15% (~3.2 kg) of body mass they had greater probability of death than females. For low‐dimorphic species like roe deer, these findings raise new considerations about the role of sexual dimorphism in feed intake efficiency.
In a Northern Apennines (Italy) population, we detected sexual dimorphism in adult roe deer according to body mass, mandible size, and tooth measurements. Moreover, we evaluated the role of tooth wear in causing senescence. Body mass and body condition of roe deer males decreased with increasing tooth wear. However, once they reached tooth wear values half of those of females, they were no longer able to support the intake of a necessary amount of energy, suggesting that chewing capacity in males has been compromised. Males also wear down a larger proportion of teeth than females over their lifetime; after losing about 15% of body mass, they have a greater probability of death than females. These data open up new questions for low‐dimorphic species like roe deer, that is, exploring sexual dimorphism in relation to feed intake efficiency among different populations.
We reviewed original research papers that used quantifiable technology to detect early autism spectrum disorder (ASD) and identified 376 studies from 34 countries from 1965 to 2013. Publications have ...increased significantly since 2000, with most coming from the USA. Electroencephalogram, magnetic resonance imaging and eye tracking were the most frequently used technologies.
Conclusion
The use of quantifiable technology to detect early ASD has increased in recent decades, but has had limited impact on early detection and treatment. Further scientific developments are anticipated, and we hope that they will increasingly be used in clinical practice for early ASD screening, diagnosis and intervention.
•Combination of auditory Gestalt perception and acoustic vocalisation analysis.•Co-occurrence of typical and atypical early vocalisations in Rett syndrome found.•More than half of extensive set of ...RTT-associated vocalisations perceived atypical.•Perceived atypicality mainly related to the auditory attribute ‘timbre’.•Prosodic, spectral, and voice quality features identified as atypicality markers.
Early speech-language development of individuals with Rett syndrome (RTT) has been repeatedly characterised by a co-occurrence of apparently typical and atypical vocalisations.
To describe specific features of this intermittent character of typical versus atypical early RTT-associated vocalisations by combining auditory Gestalt perception and acoustic vocalisation analysis.
We extracted N = 363 (pre-)linguistic vocalisations from home video recordings of an infant later diagnosed with RTT. In a listening experiment, all vocalisations were assessed for (a)typicality by five experts on early human development. Listeners’ auditory concepts of (a)typicality were investigated in context of a comprehensive set of acoustic time-, spectral- and/or energy-related higher-order features extracted from the vocalisations.
More than half of the vocalisations were rated as ‘atypical’ by at least one listener. Atypicality was mainly related to the auditory attribute ‘timbre’, and to prosodic, spectral, and voice quality features in the acoustic domain.
Knowledge gained in our study shall contribute to the generation of an objective model of early vocalisation atypicality. Such a model might be used for increasing caregivers’ and healthcare professionals’ sensitivity to identify atypical vocalisation patterns, or even for a probabilistic approach to automatically detect RTT based on early vocalisations.
Rett syndrome (RTT) is a rare, late detected developmental disorder associated with severe deficits in the speech-language domain. Despite a few reports about atypicalities in the speech-language ...development of infants and toddlers with RTT, a detailed analysis of the pre-linguistic vocalisation repertoire of infants with RTT is yet missing. Based on home video recordings, we analysed the vocalisations between 9 and 11 months of age of three female infants with typical RTT and compared them to three age-matched typically developing (TD) female controls. The video material of the infants had a total duration of 424 min with 1655 infant vocalisations. For each month, we (1) calculated the infants’ canonical babbling ratios with CBR
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, i.e., the ratio of number of utterances containing canonical syllables to total number of utterances, and (2) classified their pre-linguistic vocalisations in three non-canonical and four canonical vocalisation subtypes. All infants achieved the milestone of canonical babbling at 9 months of age according to their canonical babbling ratios, i.e. CBR
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≥ 0.15. We revealed overall lower CBRs
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and a lower proportion of canonical pre-linguistic vocalisations consisting of well-formed sounds that could serve as parts of target-language words for the RTT group compared to the TD group. Further studies with more data from individuals with RTT are needed to study the atypicalities in the pre-linguistic vocalisation repertoire which may portend the later deficits in spoken language that are characteristic features of RTT.
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