Focused review on artificial intelligence for disease detection in infants.

Over the last years, studies using artificial intelligence (AI) for the detection and prediction of diseases have increased and also concentrated more and more on vulnerable groups of individuals, such as infants. The release of ChatGPT demonstrated the potential of large language models (LLMs) and heralded a new era of AI with manifold application possibilities. However, the impact of this new technology on medical research cannot be fully estimated yet.

Ecology & computer audition: Applications of audio technology to monitor organisms and environment.

Among the 17 Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13th SDG is a call for action to combat climate change. Moreover, SDGs 14 and 15 claim the protection and conservation of life below water and life on land, respectively. In this work, we provide a literature-founded overview of application areas, in which computer audition - a powerful but in this context so far hardly considered technology, combining audio signal processing and machine intelligence - is employed to monitor our ecosystem with the potential to identify ecologically critical processes or states.

HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.

Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest.

Vocalisation Repertoire at the End of the First Year of Life: An Exploratory Comparison of Rett Syndrome and Typical Development.

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.

Triplet Loss-Based Models for COVID-19 Detection from Vocal Sounds.

This work focuses on the automatic detection of COVID-19 from the analysis of vocal sounds, including sustained vowels, coughs, and speech while reading a short text. Specifically, we use the Mel-spectrogram representations of these acoustic signals to train neural network-based models for the task at hand. The extraction of deep learnt representations from the Mel-spectrograms is performed with Convolutional Neural Networks (CNNs).

Automatic vocalisation-based detection of fragile X syndrome and Rett syndrome.

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).

The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.

Objectives: The coronavirus disease 2019 (COVID-19) has caused a crisis worldwide. Amounts of efforts have been made to prevent and control COVID-19's transmission, from early screenings to vaccinations and treatments. Recently, due to the spring up of many automatic disease recognition applications based on machine listening techniques, it would be fast and cheap to detect COVID-19 from recordings of cough, a key symptom of COVID-19.

Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell.

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.

The development of visual attention in early infancy: Insights from a free-viewing paradigm.

Theories of visual attention suggest a cascading development of subfunctions such as alertness, spatial orientation, attention to object features, and endogenous control. Here, we aimed to track infants' visual developmental steps from a primarily exogenously to more endogenously controlled processing style during their first months of life. In this repeated measures study, 51 infants participated in seven fortnightly assessments at postterm ages of 4-16 weeks.

Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder.

This study proposes a contrastive convolutional auto-encoder (contrastive CAE), a combined architecture of an auto-encoder and contrastive loss, to identify individuals with suspected COVID-19 infection using heart-rate data from participants with multiple sclerosis (MS) in the ongoing RADAR-CNS mHealth research project. Heart-rate data was remotely collected using a Fitbit wristband. COVID-19 infection was either confirmed through a positive swab test, or inferred through a self-reported set of recognised symptoms of the virus.

The voice of COVID-19: Acoustic correlates of infection in sustained vowels.

COVID-19 is a global health crisis that has been affecting our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity continuum. Many symptoms are related to pathological changes in the vocal system, leading to the assumption that COVID-19 may also affect voice production.

Novel AI driven approach to classify infant motor functions.

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.

Efficient Collection and Representation of Preverbal Data in Typical and Atypical Development.

Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child's first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized.

Canonical Babbling: A Marker for Earlier Identification of Late Detected Developmental Disorders?

Purpose Of Review: To summarize findings about the emergence and characteristics of canonical babbling in children with late detected developmental disorders (LDDDs), such as autism spectrum disorder, Rett syndrome, and fragile X syndrome. In particular, we ask whether infants' vocal development in the first year of life contains any markers that may contribute to earlier detection of these disorders.

Recent Findings: Only a handful studies have investigated canonical babbling in infants with LDDDs.

Cerebral Palsy: Early Markers of Clinical Phenotype and Functional Outcome.

The Prechtl General Movement Assessment (GMA) has become a cornerstone assessment in early identification of cerebral palsy (CP), particularly during the fidgety movement period at 3-5 months of age. Additionally, assessment of motor repertoire, such as antigravity movements and postural patterns, which form the Motor Optimality Score (MOS), may provide insight into an infant's later motor function. This study aimed to identify early specific markers for ambulation, gross motor function (using the Gross Motor Function Classification System, GMFCS), topography (unilateral, bilateral), and type (spastic, dyskinetic, ataxic, and hypotonic) of CP in a large worldwide cohort of 468 infants.

Early motor and pre-linguistic verbal development in Prader-Willi syndrome - A case report.

Background: 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.

On the lighter side: Medicine or etiquette? Rethinking a lecturer's teaching assignment.

To investigate the extent to which medical students demonstrate politeness. With respect to patient-physician interactions, politeness appears to be a factor in therapeutic success, perhaps because it might induce greater patient compliance. We assessed 354 third-semester medical students on one type of politeness, that is the percentage of students who greeted the teacher upon entering the lecture room.

Early Vocal Development in Autism Spectrum Disorder, Rett Syndrome, and Fragile X Syndrome: Insights from Studies using Retrospective Video Analysis.

This article provides an overview of studies assessing the early vocalisations of children with autism spectrum disorder (ASD), Rett syndrome (RTT), and fragile X syndrome (FXS) using retrospective video analysis (RVA) during the first two years of life. Electronic databases were systematically searched and a total of 23 studies were selected. These studies were then categorised according to whether children were later diagnosed with ASD (13 studies), RTT (8 studies), or FXS (2 studies), and then described in terms of (a) participant characteristics, (b) control group characteristics, (c) video footage, (d) behaviours analysed, and (e) main findings.

Typical vs. atypical: Combining auditory Gestalt perception and acoustic analysis of early vocalisations in Rett syndrome.

Background: Early speech-language development of individuals with Rett syndrome (RTT) has been repeatedly characterised by a co-occurrence of apparently typical and atypical vocalisations.

Aims: 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.

Methods And Procedures: We extracted N = 363 (pre-)linguistic vocalisations from home video recordings of an infant later diagnosed with RTT.

A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders.

Purpose Of Review: Substantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood.

Recent Findings: This early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention.

Eye Movements during Silent and Oral Reading in a Regular Orthography: Basic Characteristics and Correlations with Childhood Cognitive Abilities and Adolescent Reading Skills.

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 Relation between Reading Skills and Eye Movement Patterns in Adolescent Readers: Evidence from a Regular Orthography.

Over the past decades, the relation between reading skills and eye movement behavior has been well documented in English-speaking cohorts. As English and German differ substantially with regard to orthographic complexity (i.e.