Early motor signs of autism spectrum disorder in spontaneous position and movement of the head

Towards novel classification of infants' movement patterns supported by computerized video analysis

BACKGROUND

Positional preferences, asymmetry of body position and movements potentially indicate abnormal clinical conditions in infants. However, a lack of standardized nomenclature hinders accurate assessment and documentation of these preferences over time. Video tools offer a safe and reproducible method to analyze and describe infant movement patterns, aiding in physiotherapy management and goal planning. The study aimed to develop an objective classification system for infant movement patterns with particular emphasis on the specific distribution of muscle tension, using methods of computer analysis of video recordings to enhance accuracy and reproducibility in assessments.

METHODS

The study involved the recording of videos of 51 infants between 6 and 15 weeks of age, born at term, with an Apgar score of at least 8 points. Based on observations of a recording of infant spontaneous movements in the supine position, experts identified postural-motor patterns: symmetry and typical asymmetry linked to the asymmetrical tonic neck reflex. Deviations from the typical postural-motor system were indicated, and subcategories of atypical patterns were distinguished. A computer-based inference system was developed to automatically classify individual patterns.

RESULTS

The following division of motor patterns was used: (1) normal patterns, including (a) typical (symmetrical, asymmetrical: variants 1 and 2); and (b) atypical (variants: 1 to 4), (2) positional preference, and (3) abnormal patterns. The proposed automatic classification method achieved an expert decision mapping accuracy of 84%. For atypical patterns, the high reproducibility of the system's results was confirmed. Lower reproducibility, not exceeding 70%, was achieved with typical patterns.

CONCLUSIONS

Based on the observation of infant spontaneous movements, it is possible to identify movement patterns divided into typical and atypical patterns. Computer-based analysis of infant movement patterns makes it possible to objectify and satisfactorily reproduce diagnostic decisions.

The first six months of life: A systematic review of early markers associated with later autism

There is now good evidence that behavioural signs of autism spectrum conditions (autism) emerge over the first two years of life. Identifying clear developmental differences early in life may facilitate earlier identification and intervention that can promote longer-term quality of life. Here we present a systematic review of studies investigating behavioural markers of later autism diagnosis or symptomology taken at 0-6 months. The following databases were searched for articles published between 01/01/2000 and 15/03/2022: Embase, Medline, Scopus, PubMed, PsycINFO, CINAHL, Web of Science and Proquest. Twenty-five studies met inclusion criteria: assessment of behaviour at 0-6 months and later assessment of autism symptomology or diagnosis. Studies examined behaviours of attention, early social and communication behaviours, and motor behaviours, as well as composite measures. Findings indicated some evidence of measures of general attention, attention to social stimuli, and motor behaviours associated with later autism diagnosis or symptomology. Findings were inconsistent regarding social and communication behaviours, with a lack of repeated or validated measures limiting drawing firm conclusions. We discuss implications of the findings and suggest recommendations for future research.

A Comparison of the Clinical Presentation of Preterm Birth and Autism Spectrum Disorder: Commonalities and Distinctions in Children Under 3

Premature infants and infants later diagnosed with autism spectrum disorder (ASD) share many commonalities in clinical presentations. However, prematurity and ASD also have differences in clinical presentation. These overlapping phenotypes can lead to misdiagnoses of ASD or missing a diagnosis of ASD in preterm infants. We document these commonalities and differences in various developmental domains with the hope of aiding in the accurate early detection of ASD and timely intervention implementation in children born premature. Given the degree of similarities in presentation, evidence-based interventions designed specifically for preterm toddlers or toddlers with ASD may ultimately aid both populations.

Relationship between fidgety movement and frequency of movement toward midline: An observational study

BACKGROUND

Infants show other movements and posture patterns during the fidgety movement period, including movement toward midline (MTM). Few studies have quantified MTM occurring during the fidgety movement period.

AIMS

This study aimed to examine the relationship between fidgety movements (FMs) and MTM frequency and occurrence rate per minute, from two video data sets (video attached to Prechtl video manual and accuracy data from Japan).

STUDY DESIGN

Observational study.

SUBJECTS

It encompassed 47 videos. Of these, 32 were deemed normal FMs. The study amalgamated FMs that were sporadic, abnormal, or absent into a category of aberrant (n = 15).

OUTCOME MEASURES

Infant video data were observed. MTM item occurrences were recorded and calculated for occurrence percentage and MTM rate of occurrence per minute. The differences between groups for the upper limbs, lower limbs, and total MTM were statistically analysed.

RESULTS

Twenty-three infant videos of normal FMs and seven infant videos of aberrant FMs showed MTM. Eight infant videos of aberrant FMs showed no MTM, and only four with absent FMs were included. There was a significant difference in the total MTM rate of occurrence per minute between normal FMs versus aberrant FMs (p = 0.008).

CONCLUSIONS

This study presented MTM frequency and rate of occurrence per minute in infants who showed FMs during the fidgety movement period. Those who showed absent FMs also demonstrated no MTM. Further study may need a larger sample size of absent FMs and information on later development.

Prediction of autistic tendencies at 18 months of age via markerless video analysis of spontaneous body movements in 4-month-old infants

Early intervention is now considered the core treatment strategy for autism spectrum disorders (ASD). Thus, it is of significant clinical importance to establish a screening tool for the early detection of ASD in infants. To achieve this goal, in a longitudinal design, we analyzed spontaneous bodily movements of 4-month-old infants from general population and assessed their ASD-like behaviors at 18 months of age. A total of 26 movement features were calculated from video-recorded bodily movements of infants at 4 months of age. Their risk of ASD was assessed at 18 months of age with the Modified Checklist for Autism in Toddlerhood, a widely used screening questionnaire. Infants at high risk for ASD at 18 months of age exhibited less rhythmic and weaker bodily movement patterns at 4 months of age than low-risk infants. When the observed bodily movement patterns were submitted to a machine learning-based analysis, linear and non-linear classifiers successfully predicted ASD-like behavior at 18 months of age based on the bodily movement patterns at 4 months of age, at the level acceptable for practical use. This study analyzed the relationship between spontaneous bodily movements at 4 months of age and the ASD risk at 18 months of age. Experimental results suggested the utility of the proposed method for the early screening of infants at risk for ASD. We revealed that the signs of ASD risk could be detected as early as 4 months after birth, by focusing on the infant's spontaneous bodily movements.

Early Motor Signs in Autism Spectrum Disorder

A growing number of literature data suggest the presence of early impairments in the motor development of children with autism spectrum disorder, which could be often recognized even before the appearance of the classical social communication deficits of autism. In this narrative review, we aimed at performing an update about the available data on the early motor function in children with autism spectrum disorder. Early motor impairment in these children can manifest itself both as a mere delay of motor development and as the presence of atypicalities of motor function, such as a higher rate and a larger inventory, of stereotyped movements both with and without objects. In the perspective of a timely diagnosis, the presence of early motor signs can be an important clue, especially in an individual considered at high risk for autism. Motor and communication (both verbal and non-verbal) skills are connected and a pathogenetic role of early motor dysfunctions in the development of autism can be hypothesized. From this, derives the importance of an early enabling intervention aimed at improving motor skills, which could also have favorable effects on other aspects of development.

Early Developmental Signs in Children with Autism Spectrum Disorder: Results from the Japan Environment and Children’s Study

Autism spectrum disorder (ASD) is a developmental disability in early childhood. Early identification and intervention in children with ASD are essential for children and their families. This study aimed to identify the earliest signs of ASD. Using a large cohort including data from 104,062 fetal records in the Japan Environment and Children’s Study, we examined the Ages and Stages Questionnaires® (ASQ-3TM) scores of children with and without ASD. The ASQ-3 comprises five domains: communication, gross motor, fine motor, problem solving, and personal-social. The ASQ-3 scores were obtained at ages 6 months, 1 year, and 3 years. There were 64,501 children with available ASQ-3 data. The number of children diagnosed with ASD was 188 (0.29%) at 3 years of age. The highest relative risk (RR) for any domain below the monitoring score at 6 months was in the communication (RR 1.90, 95% CI 1.29–2.78, p = 0.0041), followed by fine motor (RR 1.50, 95% CI 1.28–1.76, p < 0.0001) domain. A low ASQ-3 score in the communication domain at 6 months was related to an ASD diagnosis at 3 years of age. The ASQ-3 score at 6 months can contribute to the early identification of and intervention for ASD.

Global entrainment in the brain-body-environment: retrospective and prospective views

We celebrate the 60th anniversary of Biological Cybernetics. It has also been 30 years since "Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment" was published in Biological Cybernetics (Taga et al. in Biol Cybern 65(3):147-159, 1991). I would like to look back on the creation of this paper and discuss its subsequent development and future perspectives.

Infant's Behaviour Checklist for low birth weight infants and later neurodevelopmental outcome

Assessment of the characteristics of spontaneous movements and behaviour in early infancy helps in estimating developmental outcomes. We introduced the Infant Behaviour Checklist (IBC) and examined the relationship between the behavioural characteristics of low-birth-weight infants and neurodevelopmental outcomes at 6 years of age. The behavioural characteristics during the neonatal (36-43 weeks, adjusted) and early infancy periods (49-60 weeks, adjusted) were assessed in very-low-birth-weight infants. The IBC includes 44 common behaviours. We assessed the appearance of individual behavioural characteristics at each period according to the neurodevelopmental outcome. Of the 143 infants assessed during the neonatal period, 89 had typical development (TD), 30 had intellectual disability (ID), and 24 had autism spectrum disorder (ASD). In 78 infants assessed during early infancy, 40, 21, and 17 had TD, ID, and ASD, respectively. The frequency of appearance of three behaviour-related items was significantly lower in the ID group than in the TD group. The frequency of appearance of three posture- and behaviour-related items was significantly lower, while that of two posture-related items was significantly higher, in the ASD group than in the TD group. Behavioural assessment using the IBC may provide promising clues when considering early intervention for low-birth-weight infants.

Exploring the effect of motor coordination on repetitive behaviours in children with autism spectrum disorder

Objective: This study was conducted to explore the effect of motor coordination on repetitive behaviors in children with Autism Spectrum Disorder (ASD) aged 5-15 years. Methods: The study employed the causal-comparative design, one of the correlational survey designs. The study was carried out with data obtained from parents of 241 children with ASD. The parents were administered the measurement tools of Gilliam Autism Rating Scale-2-Turkish Version to confirm the diagnosis of ASD, Demographic Information Form to obtain information about the child and the parent, Repetitive Behavior Scale-Revised-Turkish Version to evaluate the repetitive behaviors, and Developmental Coordination Disorder Questionnaire-07-Turkish Version to evaluate the motor coordination performance. The data were analyzed MANCOVA in the R package program. Results: The study results revealed that 72% of children with ASD had a risk of Developmental Coordination Disorder (DCD). The repetitive behaviors of children with and without DCD risk differed significantly. The severity and intensity of the repetitive behaviors of children with DCD risk were higher than those without DCD risk when age, gender, and comorbidity were taken under control. Conclusion: The motor coordination problems in children with ASD are effective on repetitive behaviors.

Is Smiling the Key? Machine Learning Analytics Detect Subtle Patterns in Micro-Expressions of Infants with ASD

Time is a key factor to consider in Autism Spectrum Disorder. Detecting the condition as early as possible is crucial in terms of treatment success. Despite advances in the literature, it is still difficult to identify early markers able to effectively forecast the manifestation of symptoms. Artificial intelligence (AI) provides effective alternatives for behavior screening. To this end, we investigated facial expressions in 18 autistic and 15 typical infants during their first ecological interactions, between 6 and 12 months of age. We employed Openface, an AI-based software designed to systematically analyze facial micro-movements in images in order to extract the subtle dynamics of Social Smiles in unconstrained Home Videos. Reduced frequency and activation intensity of Social Smiles was computed for children with autism. Machine Learning models enabled us to map facial behavior consistently, exposing early differences hardly detectable by non-expert naked eye. This outcome contributes to enhancing the potential of AI as a supportive tool for the clinical framework.

Computer vision in autism spectrum disorder research: a systematic review of published studies from 2009 to 2019

The current state of computer vision methods applied to autism spectrum disorder (ASD) research has not been well established. Increasing evidence suggests that computer vision techniques have a strong impact on autism research. The primary objective of this systematic review is to examine how computer vision analysis has been useful in ASD diagnosis, therapy and autism research in general. A systematic review of publications indexed on PubMed, IEEE Xplore and ACM Digital Library was conducted from 2009 to 2019. Search terms included ['autis*' AND ('computer vision' OR 'behavio* imaging' OR 'behavio* analysis' OR 'affective computing')]. Results are reported according to PRISMA statement. A total of 94 studies are included in the analysis. Eligible papers are categorised based on the potential biological/behavioural markers quantified in each study. Then, different computer vision approaches that were employed in the included papers are described. Different publicly available datasets are also reviewed in order to rapidly familiarise researchers with datasets applicable to their field and to accelerate both new behavioural and technological work on autism research. Finally, future research directions are outlined. The findings in this review suggest that computer vision analysis is useful for the quantification of behavioural/biological markers which can further lead to a more objective analysis in autism research.

Subplate Neurons as an Organizer of Mammalian Neocortical Development

Subplate neurons (SpNs) are one of the earliest born and matured neurons in the developing cerebral cortex and play an important role in the early development of the neocortex. It has been known that SpNs have an essential role in thalamocortical axon (TCA) pathfinding and the establishment of the first neural circuit from the thalamus towards cortical layer IV. In addition to this function, it has recently been revealed in mouse corticogenesis that SpNs play an important role in the regulation of radial neuronal migration during the mid-embryonic stage. Moreover, accumulating studies throw light on the possible roles of SpNs in adult brain functions and also their involvement in psychiatric or other neurological disorders. As SpNs are unique to mammals, they may have contributed to the evolution of the mammalian neocortex by efficiently organizing cortical formation during the limited embryonic period of corticogenesis. By increasing our knowledge of the functions of SpNs, we will clarify how SpNs act as an organizer of mammalian neocortical formation.

The shape of disposable diaper affects spontaneous movements of lower limbs in young infants

This study examined the characteristics of young infants' lower limb spontaneous movements based on differences in shape of diapers. Twenty-seven healthy infants (103 ± 16.3 days old) were enrolled in this study. We measured the spontaneous movements of their lower limbs in four conditions (Naked, wearing Normal type diapers, wearing Type A diapers, and wearing Type B diapers). The Normal diaper has a wider waist belt than the Type A diaper, and the Type B diaper has a narrower crotch area than the Type A diaper. We observed them in seven indices (the velocity of lower limb movements, the trajectory area of knee movement in the sagittal plane and the frontal plane, the distance between both knees and between side of abdomen and knee, and correlation of velocities between side of abdomen and knee and between left and right ankles). The results showed that the velocity of the lower limb movements in the Naked condition was higher than when wearing Normal diapers. The value for the trajectory area of knee movement in sagittal plane, which reflects the range of lower leg lifting movements and closeness of such movements to the trunk, for the Type B diaper condition was higher than that for the Normal diaper condition. This result indicates that the shape of the diaper affects the spontaneous movements of the lower limbs of young infants.

Evaluation of Fidgety Movements of Infants Based on Gestalt Perception Reflects Differences in Limb Movement Trajectory Curvature

BACKGROUND

Infants aged 2 to 5 months show spontaneous general movements (GMs) of the whole body, which are referred to as fidgety movements (FMs). Although previous studies have shown that evaluation of GMs by the General Movement Assessment (GMA) has predictive value about later neurological impairments, it remains unknown whether raters consistently perceive and rate such complex kinematic information.

OBJECTIVE

The purpose of this study was to construct a method to reveal which movement features are associated with each rater's evaluation of FMs based on the GMA.

DESIGN

GMA scores of 163 healthy infants aged 11 to 16 weeks postterm were matched with data obtained from a 3-dimensional motion analysis system.

METHODS

Three physical therapists performed the GMA and classified GMs into 9 types, from which we focused on 3 subtypes differing in the temporal organization of FMs (continual, intermittent, and sporadic FMs). We also calculated 6 movement indices (average velocity of limb movements, number of movement units, kurtosis of acceleration, jerk index, average curvature, and correlation between limb velocities) for arms and legs for each infant and analyzed which movement indices were associated with the ratings of the 3 FM subtypes by each rater.

RESULTS

Only the average curvature differed significantly among the ratings of the 3 FM subtypes for all 3 raters. Each rater showed significant differences in the average curvature in either arms or legs.

LIMITATIONS

It is difficult to generalize the present results to raters with various levels of expertise and experience in using the GMA. This issue calls for further research.

CONCLUSIONS

The method used revealed commonality and individuality about the perceived movement features that can be associated with the rating of FMs.

Computer vision and behavioral phenotyping: an autism case study

Despite significant recent advances in molecular genetics and neuroscience, behavioral ratings based on clinical observations are still the gold standard for screening, diagnosing, and assessing outcomes in neurodevelopmental disorders, including autism spectrum disorder. Such behavioral ratings are subjective, require significant clinician expertise and training, typically do not capture data from the children in their natural environments such as homes or schools, and are not scalable for large population screening, low-income communities, or longitudinal monitoring, all of which are critical for outcome evaluation in multisite studies and for understanding and evaluating symptoms in the general population. The development of computational approaches to standardized objective behavioral assessment is, thus, a significant unmet need in autism spectrum disorder in particular and developmental and neurodegenerative disorders in general. Here, we discuss how computer vision, and machine learning, can develop scalable low-cost mobile health methods for automatically and consistently assessing existing biomarkers, from eye tracking to movement patterns and affect, while also providing tools and big data for novel discovery.

Training Physical Therapists in Early ASD Screening

Physical therapists (PTs) are often one of the first professionals to evaluate children at risk. To examine the effect of an early screening training on pediatric PTs': (1) knowledge of autism spectrum disorder (ASD), (2) clinical self-efficacy, and (3) identification of markers. Twenty-six PTs participated in a 2-day "Early ASD Screening" workshop. The ASD Knowledge and Self-Efficacy Questionnaire, and video case study analysis were completed pre- and post-training. Changes following training were significant for ASD knowledge related to etiology and learning performance, early signs, risk factors, and clinical self-efficacy. Rating the videoed case study after the training, was significantly more accurate than it was before. Training PTs is important for enhancing early identification of ASD.

Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder

Evidence suggests that differences in motor function are an early feature of autism spectrum disorder (ASD). One aspect of motor ability that develops during childhood is postural control, reflected in the ability to maintain a steady head and body position without excessive sway. Observational studies have documented differences in postural control in older children with ASD. The present study used computer vision analysis to assess midline head postural control, as reflected in the rate of spontaneous head movements during states of active attention, in 104 toddlers between 16-31 months of age (Mean = 22 months), 22 of whom were diagnosed with ASD. Time-series data revealed robust group differences in the rate of head movements while the toddlers watched movies depicting social and nonsocial stimuli. Toddlers with ASD exhibited a significantly higher rate of head movement as compared to non-ASD toddlers, suggesting difficulties in maintaining midline position of the head while engaging attentional systems. The use of digital phenotyping approaches, such as computer vision analysis, to quantify variation in early motor behaviors will allow for more precise, objective, and quantitative characterization of early motor signatures and potentially provide new automated methods for early autism risk identification.

Motor Skills as Moderators of Core Symptoms in Autism Spectrum Disorders: Preliminary Data From an Exploratory Analysis With Artificial Neural Networks

Motor disturbances have been widely observed in children with autism spectrum disorder (ASD), and motor problems are currently reported as associated features supporting the diagnosis of ASD in the current Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Studies on this issue reported disturbances in different motor domains, including both gross and fine motor areas as well as coordination, postural control, and standing balance. However, they failed to clearly state whether motor impairments are related to demographical and developmental features of ASD. Both the different methodological approaches assessing motor skills and the heterogeneity in clinical features of participants analyzed have been implicated as contributors to variance in findings. However, the non-linearity of the relationships between variables may account for the inability of the traditional analysis to grasp the core problem suggesting that the "single symptom approach analysis" should be overcome. Artificial neural networks (ANNs) are computational adaptive systems inspired by the functioning processes of the human brain particularly adapted to solving non-linear problems. This study aimed to apply the ANNs to reveal the entire spectrum of the relationship between motor skills and clinical variables. Thirty-two male children with ASD [mean age: 48.5 months (SD: 8.8); age range: 30-60 months] were recruited in a tertiary care university hospital. A multidisciplinary comprehensive diagnostic evaluation was associated with a standardized assessment battery for motor skills, the Peabody Developmental Motor Scale-Second Edition. Exploratory analyses were performed through the ANNs. The findings revealed that poor motor skills were a common clinical feature of preschoolers with ASD, relating both to the high level of repetitive behaviors and to the low level of expressive language. Moreover, unobvious trends among motor, cognitive and social skills have been detected. In conclusion, motor abnormalities in preschoolers with ASD were widespread, and the degree of impairment may inform clinicians about the severity of ASD core symptoms. Understanding motor disturbances in children with ASD may be relevant to clarify neurobiological basis and ultimately to guide the development of tailored treatments.