NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework.

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

The impact for DCD - USA study: The current state of Developmental Coordination Disorder (DCD) in the United States of America.

BACKGROUND: Developmental Coordination Disorder (DCD) is among the most under-recognized and under-supported disorders worldwide. AIMS: To present a preliminary national study that evaluated the unmet needs of children with DCD in the USA using the Impact for DCD survey. METHODS AND PROCEDURES: 232 parents of individuals aged 5-18 years provided responses from 36 items in five domains (diagnosis, activity/participation, education, therapy, and social/emotional health). OUTCOMES AND RESULTS: Most children (81.9%) had a formal diagnosis for movement difficulties, and 91.6% of parents reported that receiving a diagnosis was helpful, but most had not heard of the diagnosis before. The most common co-occurring diagnoses were childhood apraxia of speech and other speech-language disorders (24.6%), ADHD (23.1%), and anxiety (18.8%). Most parents reported that their children withdrew from or avoided movement-related activities (53%), and nearly all (94.8%) were concerned about the impact of motor difficulties on their children's social and emotional health. Only 37% of parents reported feeling that their child received sufficient therapy. CONCLUSIONS AND IMPLICATIONS: Generally, parents reported feeling frustrated with others' understanding and awareness of the condition and with therapy services. The results shown here provide timely data that can support efforts for increased awareness, improved diagnosis, and increased availability of services for DCD in the USA.

Motor problems in autism: Co-occurrence or feature?

Motor features of autism have long been acknowledged by clinicians, researchers, and community stakeholders. Current DSM-5 and ICD-11 guidelines allow clinicians to assign a co-occurring diagnosis of developmental [motor] coordination disorder (DCD) for autistic individuals with significant motor problems. DCD is characterized by poor motor proficiency with an onset of symptoms in early development. Studies have shown considerable overlap in the behavioral motor features observed in autism and DCD. However, others indicate that motor problems in autism and DCD may stem from different underlying sensorimotor mechanisms. Regardless of whether autism has a unique motor phenotype or an overlap with DCD, changes need to be made in the clinical pipeline to address motor problems in autism at the stages of recognition, assessment, diagnosis, and intervention. Consensus is needed to address unmet needs in research on the etiology of motor problems in autism and their overlap with DCD, to optimize clinical practice guidelines. The development of screening and assessment tools for motor problems that are valid and reliable for use with autistic individuals is essential, and an evidence-based clinical pipeline for motor problems in autism is urgently needed. WHAT THIS PAPER ADDS: Motor problems in autism are highly prevalent, yet underdiagnosed and poorly managed. An evidence-based clinical pipeline for motor problems in autism is urgently needed.

Motor differences in autism during a human-robot imitative gesturing task.

BACKGROUND: Difficulty with imitative gesturing is frequently observed as a clinical feature of autism. Current practices for assessment of imitative gesturing ability-behavioral observation and parent report-do not allow precise measurement of specific components of imitative gesturing performance, instead relying on subjective judgments. Advances in technology allow researchers to objectively quantify the nature of these movement differences, and to use less socially stressful interaction partners (e.g., robots). In this study, we aimed to quantify differences in imitative gesturing between autistic and neurotypical development during human-robot interaction. METHODS: Thirty-five autistic (n = 19) and neurotypical (n = 16) participants imitated social gestures of an interactive robot (e.g., wave). The movements of the participants and the robot were recorded using an infrared motion-capture system with reflective markers on corresponding head and body locations. We used dynamic time warping to quantify the degree to which the participant's and robot's movement were aligned across the movement cycle and work contribution to determine how each joint angle was producing the movements. FINDINGS: Results revealed differences between autistic and neurotypical participants in imitative accuracy and work contribution, primarily in the movements requiring unilateral extension of the arm. Autistic individuals imitated the robot less accurately and used less work at the shoulder compared to neurotypical individuals. INTERPRETATION: These findings indicate differences in autistic participants' ability to imitate an interactive robot. These findings build on our understanding of the underlying motor control and sensorimotor integration mechanisms that support imitative gesturing in autism which may aid in identifying appropriate intervention targets.

Community-based postural control assessment in autistic individuals indicates a similar but delayed trajectory compared to neurotypical individuals.

Autistic individuals exhibit significant sensorimotor differences. Postural stability and control are foundational motor skills for successfully performing many activities of daily living. In neurotypical development, postural stability and control develop throughout childhood and adolescence. In autistic development, previous studies have focused primarily on individual age groups (e.g., childhood, adolescence, adulthood) or only controlled for age using age-matching. Here, we examined the age trajectories of postural stability and control in autism from childhood through adolescents using standardized clinical assessments. In study 1, we tested the postural stability of autistic (n = 27) and neurotypical (n = 41) children, adolescents, and young adults aged 7-20 years during quiet standing on a force plate in three visual conditions: eyes open (EO), eyes closed (EC), and eyes open with the head in a translucent dome (Dome). Postural sway variability decreased as age increased for both groups, but autistic participants showed greater variability than neurotypical participants across age. In study 2, we tested autistic (n = 21) and neurotypical (n = 32) children and adolescents aged 7-16 years during a dynamic postural control task with nine targets. Postural control efficiency increased as age increased for both groups, but autistic participants were less efficient compared to neurotypical participants across age. Together, these results indicate that autistic individuals have a similar age trajectory for postural stability and control compared to neurotypical individuals, but have lower postural stability and control overall.

Autistic Children Use Less Efficient Goal-Directed Whole Body Movements Compared to Neurotypical Development.

Autistic children have differences in their movements which impact their functional performance. Virtual-reality enables researchers to study movement in safe, engaging environments. We used motion-capture to measure how 7-13-year-old autistic and neurotypical children make whole-body movements in a virtual-reality task. Although children in both groups were successful, we observed differences in their movements. Autistic children were less efficient moving to the target. Autistic children did not appear to use a movement strategy. While neurotypical children were more likely to overshoot near targets and undershoot far targets, autistic children did not modulate their strategy. Using kinematic data from tasks in virtual-reality, we can begin to understand the pattern of movement challenges experienced by autistic children.

Movement smoothness during dynamic postural control to a static target differs between autistic and neurotypical children.

BACKGROUND: Autistic children and adults have known differences in motor performance, including postural instability and atypical gross motor control. Few studies have specifically tested dynamic postural control. This is the first study to quantify movement smoothness and its relationship to task performance during lateral dynamic postural control tasks in autism. RESEARCH QUESTION: We sought to test the hypothesis that autistic children would have less smooth movements to lateral static targets compared to neurotypical children, and that this difference would relate to specific movement strategies. METHODS: We used camera-based motion-capture to measure spatiotemporal characteristics of lateral movement of a marker placed on the C7 vertebrae, and of markers comprising trunk and pelvis segments during a dynamic postural movements to near and far targets administered in an immersive virtual environment. We tested a sample of 15 autistic children and 11 age-matched neurotypical children. We quantified movement smoothness using log dimensionless jerk. RESULTS: Autistic children exhibited more medial-lateral pelvic position range of motion compared to neurotypical children, and used a stepping strategy more often compared to neurotypical children. Autistic children also had higher log dimensionless jerk than neurotypical children for motion of the C7 marker. All participants had higher log dimensionless jerk for far targets than for near targets. Autistic children had longer trial durations than neurotypical children, and younger children had longer trial durations than older children across diagnostic groups. SIGNIFICANCE: The stepping strategy observed more often in the autistic group likely contributed to log dimensionless jerk and reduced movement smoothness. This strategy is indicative of either an attempt to prevent an impending loss of balance, or an attempt to compensate for and recover from a loss of balance once it is detected.

Effects of Intersectionality Along the Pathway to Diagnosis for Autistic Children With and Without Co-occurring Attention Deficit Hyperactivity Disorder in a Nationally-Representative Sample.

Children with complex behavioral profiles (e.g., ASD + ADHD) may experience delays in obtaining a final diagnosis. Low-resource or underrepresented groups may be at even greater risk for delayed diagnosis. We assessed the effect of sociodemographic factors, symptom complexity and co-occurring conditions, and identifier of first symptoms on diagnostic trajectories among children aged 3-17 years diagnosed with ASD (n = 52) or ASD + ADHD (n = 352) from a nationally-representative sample. Race/ethnicity and gender disparities were evident in both groups. Race, symptom complexity, and co-occuring conditions predicted age of final diagnosis and wait time between first concern and final diagnosis, both of which were staggeringly high. Results suggest a complex influence of sociodemographic factors on the diagnostic pathway, and risk of health disparities as a function of intersectionality.

Identity and Discourse Among #ActuallyAutistic Twitter Users With Motor Differences.

Despite a growing awareness of the prevalence of motor differences in the autistic community, their functional impact is poorly understood. Social media offers the ideal setting to observe this discourse in a less-contrived setting than lab-based structured interviews. The aims of the present study were (a) to determine the proportion of Twitter users who self-identify as autistic and dyspraxic/having developmental coordination disorder, relative to autistic alone, and (b) to identify common themes emerging from two moderated chat threads with motor-related prompts. Using the Twitter research application programming interface, we harvested data from users' public profiles and tweets containing terms related to autism and developmental coordination disorder within a 1-month time period. We also harvested data from two #AutChat threads related to motor skills, which included 151 tweets from 31 unique autistic users (two with co-occurring developmental coordination disorder). Of these tweets, 44 were explicitly about motor differences, while the remainder consisted of discussion topics more loosely associated with motor skills. The following common themes were quantified: manual dexterity, lower extremity, oral motor, gross motor, posture, balance, stimming, movement pain, and coordination. Together, these findings indicate that motor differences are highly recognized and discussed among autistic individuals but are not overtly integrated into their identities at the same rate.

Social Media as a Tool for Understanding the Role of Motor Differences in Neurodivergent Identity and Lived Experience.

Social media offers an exciting opportunity for the field of motor development and behavior research. With platforms such as Twitter offering access to historical data from users' public bios and posts, there is untapped potential to examine community perspectives on the role of motor differences in identity and lived experience. Analysis of online discourse offers advantages over traditional qualitative methods like structured interviews or focus groups, including a less-contrived setting, global geographic and cultural representation, and ease of sampling. The aim of this special section is to present a pipeline for harvesting and analysis of Twitter data related to users' identities and discourse characteristics, specifically situated in the context of motor development and behavior. This pipeline is demonstrated in two independent studies, one on autistic users and one on developmental coordination disorder (DCD)/dyspraxic users. These studies demonstrate the utility of Twitter data for research on neurodivergent and disabled people's perspectives on their motor differences, and whether they are expressed as part of their identity. Implications of results are discussed for each study, as well as in the larger context of future research using a variety of approaches to analysis of social media data, including those from predominantly image- and video-based platforms.

#DCD/Dyspraxia in Real Life: Twitter Users' Unprompted Expression of Experiences With Motor Differences.

Little is known about adults' experiences with developmental coordination disorder (DCD; sometimes also referred to as dyspraxia). Social media is an accessible opportunity for those who identify as dyspraxic or as having DCD to provide valuable insight into the lifespan impact of this condition on functional ability, participation, compensatory strategies, and well-being. We used the Twitter research application programming interface to identify users who self-identified with the keywords Developmental Coordination Disorder, #DCD, #dyspraxic (or # dyspraxia), or clumsy in their profile descriptions between October 10 and November 10, 2021. During that period, 818 tweets were harvested with 524 remaining after removing duplicates (e.g., multiple promotions of a single resource) and unrelated tweets. They were labeled according to motor differences (general motor, coordination, fine motor skills, oral motor skills, manual dexterity, driving, gross motor skills, movement pain and fatigue, posture and balance, and lower extremity); functional impact (advocacy/awareness, support for others, resources, information, and education, intervention, accommodation, and work); or other related topics (stimming and sensory, co-occurrence and diagnostic overlap, cognitive, social and communication speech, and emotional and mental health). The DCD/dyspraxic community has clearly identified a lifelong impact of motor differences across multiple contexts. DCD/dyspraxic Twitter users shared compensatory strategies that could help others, and offered insight into their experience of co-occurring conditions and cognitive/emotional sequelae of motor challenges.

Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python.

Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and community discussions about specific characteristics (e.g., motor skills, burnout) associated with a diagnostic group. These data are useful for understanding the perspectives of a diverse, international group of self-advocates representing a wide range of clinical populations. Here, we provide a framework for how to harvest data from Twitter through their free, academic researcher application programming interface access using Python, a free, open-source programming language. We also provide a sample data set harvested using this framework and a set of analyses on these data specifically related to motor differences in neurodevelopmental conditions. This framework offers a cost-effective and flexible means of harvesting and analyzing Twitter data. Researchers should utilize these resources to advance our understanding of the lived experiences of clinical populations through social media platforms and to determine the critical questions that are of most importance to improving quality of life.

Assessing the Satisfaction and Acceptability of an Online Parent Coaching Intervention: A Mixed-Methods Approach.

Background: Parent-mediated intervention (PMI) has been studied in promoting skill acquisition or behavior change in the children with autism spectrum disorder. Most studies emphasize on the improvement of child's core symptoms or maladaptive behaviors, making parental perceived competence and self-efficacy secondary. Yet, the evaluations of intervention implementation are under-reported, especially when translating such interventions into a new population or context. This research investigated the intervention implementation of a 12-week parent coaching intervention which was delivered through telehealth and tailored to Chinese population. The intervention was based on the Parent-mediated Early Start Denver Model with culturally adapted lectures, manuals, and demonstration and commentary videos. This study aimed to evaluate the intervention implementation by assessing parents' satisfaction, acceptability, appropriateness, and feasibility. Method: A randomized controlled trial was conducted with two telehealth conditions: self-directed and web+group therapy. Parents in the self-directed condition received intervention individually through the online learning platform. The web+group therapy condition navigated the same program with weekly 1.5-h group coaching sessions via videoconferencing. This mixed-methods study used a concurrent convergent design to evaluate the intervention implementation at post-intervention. The quantitative data was collected from the Program Evaluation Survey and the qualitative data was collected from five focus groups. Results: Parents in self-directed group reported significantly lower scores in total perceived competence than parents in web+group therapy condition, while there was no group difference on the total self-efficacy. Tailored feedback, demonstration and commentary videos, peer commenting, live coaching, and guided reflection were the top-five acceptable telehealth strategies that were strongly endorsed by parents. Family centered care, home-based intervention, strategies relative to daily activities, the remote learning platform, and the program-based community were elements that parents considered when evaluating the program's appropriateness. Parent modeling, step-by-step instructions, and tailored feedback were key components in making intervention strategies feasible for parents to implement at home. Conclusion: Findings indicate the application of telehealth was acceptable, appropriate, and feasible for Chinese parents. Group-based parent coaching intervention via videoconferencing could be a promising home-based service model to increase parental perceived competence. A large-scale RCT is needed to investigate the effectiveness of group-based PMI via telehealth.

Motor skills predict adaptive behavior in autistic children and adolescents.

It is well-documented that intelligence quotient (IQ) is a poor predictor of adaptive behavior scores in autism, with autistic children having lower adaptive behavior scores than would be predicted based on their IQ scores. Differences in motor skills may explain the variability in their adaptive behavior scores. The current study examined how motor skills might explain autistic individuals' low adaptive behavior scores and which individual components of IQ (i.e., verbal comprehension and perceptual reasoning) and motor skills (i.e., manual dexterity, aiming and catching, and balance) may drive this effect. We examined the associations between IQ, motor skills, calibrated severity, and adaptive behavior scores in 45 autistic children and adolescents. Using a t-test, we found a significant difference (p <0.001) between full-scale IQ and adaptive behavior scores, indicating that our participants' adaptive behavior scores were lower than would be expected given their full-scale IQ. Using a linear regression, we investigated whether motor skills predicted adaptive behavior in autistic children and adolescents and found that motor skills scores were associated with adaptive behavior scores (p = 0.022). To further investigate these associations, we used another linear regression to examine how individual components of IQ and motor skills predicted adaptive behavior scores in autistic children and adolescents. Our results indicated that manual dexterity scores were associated with adaptive behavior scores (p = 0.036). These findings clearly illustrate the need for further understanding of autistic individuals' difficulties with adaptive behavior and the potential role of motor skill difficulties that may underlie these difficulties. LAY SUMMARY: Autistic children have lower adaptive behavior scores (e.g., daily living skills, social skills, communication) than intelligence scores (e.g., verbal and perceptual skills) along with difficulties with motor skills. Motor skills may explain the gap between adaptive behavior and intelligence. We found motor skills were associated with adaptive behavior in autistic children and adolescents. In particular, hand coordination was associated with adaptive behavior. We need to better understand how autistic individuals' motor skills impact their adaptive behavior to provide effective supports.

Post-processing integration and semi-automated analysis of eye-tracking and motion-capture data obtained in immersive virtual reality environments to measure visuomotor integration.

Mobile eye-tracking and motion-capture techniques yield rich, precisely quantifiable data that can inform our understanding of the relationship between visual and motor processes during task performance. However, these systems are rarely used in combination, in part because of the significant time and human resources required for post-processing and analysis. Recent advances in computer vision have opened the door for more efficient processing and analysis solutions. We developed a post-processing pipeline to integrate mobile eye-tracking and full-body motion-capture data. These systems were used simultaneously to measure visuomotor integration in an immersive virtual environment. Our approach enables calculation of a 3D gaze vector that can be mapped to the participant's body position and objects in the virtual environment using a uniform coordinate system. This approach is generalizable to other configurations, and enables more efficient analysis of eye, head, and body movements together during visuomotor tasks administered in controlled, repeatable environments.

What Can We Do to Promote Mental Health Among Individuals With Developmental Coordination Disorder?

PURPOSE OF THE REVIEW: It is well-documented that individuals with DCD experience mental health problems, in both psychosocial and psychiatric domains. In this review, we propose a series of diverse options to improve mental health among individuals with DCD. RECENT FINDINGS: Despite recognition of mental health problems in DCD, relatively little work has been done to develop effective interventions. There is an urgent need for action in this matter. We present and discuss options based on a societal perspective (awareness and understanding), parental perspective (access to services and resources), and child perspective (participation). SUMMARY: In order to improve mental health, interventions must take into account multiple levels in a complex framework that includes community, family, and the individual. While more research on intervention effectiveness is necessary, researchers, practitioners, and community advocates can use existing initiatives as a starting point to address the urgent need for improving mental health in DCD.

Shared Features or Co-occurrence? Evaluating Symptoms of Developmental Coordination Disorder in Children and Adolescents with Autism Spectrum Disorder.

Motor differences are common in Autism Spectrum Disorder (ASD), but rarely evaluated against diagnostic criteria for Developmental Coordination Disorder (DCD). We aimed to determine whether motor problems in ASD represent the possible co-occurrence of DCD. We retrospectively reviewed standardized assessments and parent-reports to evaluate motor ability in 43 individuals with ASD against diagnostic criteria for DCD, and compared to 18 individuals with DCD. Over 97% of cases in the ASD group scored below the 16th percentile in motor ability, with most below the 5th percentile. Over 90% of cases in the ASD group met criteria for co-occurring DCD. Motor challenges are a clinically-significant problem in ASD; systematically assessing the prevalence of co-occurring ASD + DCD is necessary to optimize assessment and intervention.

Preliminary Improvements in Dynamic Postural Control after A Group-based Intervention Program for Children with Developmental Coordination Disorder: A Brief Report.

OBJECTIVE: To determine the value of a traditional (easy to implement) group-based intervention program on both static and dynamic postural control in children with Developmental Coordination Disorder (DCD). METHODS: Sway and stability indices were measured with the Clinical Test of Sensory Integration in Balance (CTSIB) and efficiency of goal-directed movement was measured during a Limits-of-Stability (LoS) task, before and after the intervention program. The intervention involved a total of 10 one-hour group sessions, administered once per week for 10 weeks. RESULTS: Results indicated significant group increases in dynamic postural control (p <.05). These results suggest it is possible to improve dynamic postural control in this population. This type of intervention does not require any expensive materials, it is feasible, and easy-to-implement to a group of children. CONCLUSION: We conclude that this simple form of intervention involving fun group activities can significantly improve dynamic postural control in children with DCD.

Plasma trimethylamine N-oxide, a gut microbe-generated phosphatidylcholine metabolite, is associated with autism spectrum disorders.

OBJECTIVE: The compositions of the gut microbiota and its metabolites were altered in individuals with Autism Spectrum Disorder (ASD). The aim of this study was to assess whether plasma levels of gut-derived metabolite trimethylamine N-oxide (TMAO) were associated with ASD and the degree of symptom severity. METHODS: From September 2017 to January 2019, a total of three hundred and twenty-eight Chinese children (164 with ASD and 164 their age-sex matched control subjects) aged 3-8 years were included. TMAO levels in plasma were determined using high-performance liquid chromatography tandem mass spectrometry (LC/MS/MS). Logistic regression analysis was used to examine the TMAO-ASD association. RESULTS: In the study, the median age of the ASD group was 5 years (interquartile range [IQR], 4-6 years) and 129 (78.7%) were boys. The median plasma levels of TMAO in children with ASD and typically-developing (TD) children at admission were 4.2 (IQR, 3.0-5.6) µmol/l and 3.0 (2.0-4.4) µmol/l, respectively (P < 0.001). For each 1 µmol/l increase of plasma TMAO, the unadjusted and adjusted risk of ASD would be increased by 54% (with the odds ratios [OR] of 1.54; 95% confidence intervals [CI]: 1.32-1.78; P < 0.001) and 27% (1.27 [1.10-1.45], P < 0.001), respectively. Symptom severity was classified as mild-to-moderate (CARS < 37) for 66 children with ASD (40.2%). In these children, the plasma levels of TMAO were lower than in the 98 children with ASD (59.8%) whose symptoms were classified as severe (CARS > 36) (3.5[2.5-4.9] µmol/l vs. 4.5(3.7-6.0) µmol/l; P < 0.001). For each 1 µmol/l increase of plasma TMAO, the unadjusted and adjusted risk of severe autism would be increased by 61% (with the OR of 1.61 [95% CI 1.28-2.01], P < 0.001) and 31% (1.31 [1.08-1.49], P < 0.001), respectively. CONCLUSIONS: Elevated plasma levels of TMAO were associated with ASD and symptom severity.