Handedness in Children With Autism Spectrum Disorder

Knaus, Tracey A.; Kamps, Jodi L.; Foundas, Anne L.

doi:10.1177/0031512516637021

Cited by 21 publications

(13 citation statements)

References 64 publications

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Section: Methodsmentioning

confidence: 99%

“…Following intellectual testing, handedness was assessed using the Almli Handedness Assessment [Almli, Rivkin, & McKinstry, 2007; Knaus, Kamps, & Foundas, 2016]. This handedness assessment has previously been used on children with ASD between the ages of 3–17 [Knaus et al, 2016]. The participant was seated in front of the experimenter and asked to complete 10 tasks using their hands with items presented at midline.…”

Section: Methodsmentioning

confidence: 99%

“…The participant was seated in front of the experimenter and asked to complete 10 tasks using their hands with items presented at midline. Handedness was scored from −3.16 (complete left handedness) to +3.16 (complete right‐handedness) [Almli et al, 2007; Knaus et al, 2016]. If handedness was scored between −1 and +1, indicating no hand preference, the hand used for the writing task was selected as the dominant‐hand.…”

Section: Methodsmentioning

confidence: 99%

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Children with Autism Spectrum Disorder Show Impairments During Dynamic Versus Static Grip‐force Tracking

et al. 2020

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Impairments in visuomotor integration (VMI) may contribute to anomalous development of motor, as well as socialcommunicative, skills in children with autism spectrum disorder (ASD). However, it is relatively unknown whether VMI impairments are specific to children with ASD versus children with other neurodevelopmental disorders. As such, this study addressed the hypothesis that children with ASD, but not those in other clinical control groups, would show greater deficits in high-VMI dynamic grip-force tracking versus low-VMI static presentation. Seventy-nine children, aged 7-17 years, participated: 22 children with ASD, 17 children with fetal alcohol spectrum disorder (FASD), 18 children with Attention-Deficit Hyperactivity Disorder (ADHD), and 22 typically developing (TD) children. Two grip-force tracking conditions were examined: (1) a low-VMI condition (static visual target) and (2) a high-VMI condition (dynamic visual target). Low-frequency force oscillations <0.5 Hz during the visuomotor task were also examined. Twoway ANCOVAs were used to examine group x VMI and group x frequency effects (α = 0.05). Children with ASD showed a difficulty, above that seen in the ADHD/FASD groups, tracking dynamic, but not static, visual stimuli as compared to TD children. Low-frequency force oscillations <0.25 Hz were also significantly greater in the ASD versus the TD group. This study is the first to report VMI deficits during dynamic versus static grip-force tracking and increased proportion of force oscillations <0.25 Hz during visuomotor tracking in the ASD versus TD group. Dynamic VMI impairments may be a core psychophysiologic feature that could contribute to impaired development of motor and socialcommunicative skills in ASD.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Children with Autism Spectrum Disorder Show Impairments During Dynamic Versus Static Grip‐force Tracking

et al. 2020

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“…In terms of participant demographics, we considered whether studies included a clinically defined population, because adextrality (sometimes termed ‘pathological sinistrality’) has historically been associated with higher susceptibility to both congenital and acquired diseases (Coren & Halpern, ) and psychological disorders (Bradshaw‐McAnulty, Hicks, & Kinsbourne, ; Crow, Crow, Done, & Leask, ; Knaus, Kamps, & Foundas, ; Lindell & Hudry, ; Rodriguez et al., ; Satz, ). If this is true, we might observe either a greater proportion of adextrals amongst clinically defined samples, if these studies eschew handedness as an inclusion/exclusion criterion in order to facilitate recruitment; or alternatively a disproportionately low representation of adextrals if studies recognise the likelihood of adextrality and are therefore more likely to exclude adextrals.…”

Section: Introductionmentioning

confidence: 99%

A sinister subject: Quantifying handedness‐based recruitment biases in current neuroimaging research

Bailey

McMillan

Newman

2019

Eur J of Neuroscience

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Approximately ten per cent of humans are left‐handed or ambidextrous (adextral). It has been suggested that, despite their sizable representation at the whole‐population level, this demographic is largely avoided by researchers within the neuroimaging community. To date, however, no formal effort has been made to quantify the extent to which adextrals are excluded from neuroimaging‐based research. Here, we aimed to address this question in a review of over 1,000 recent articles published in high‐impact, peer‐reviewed, neuroimaging‐focused journals. Specifically, we sought to ascertain whether, and the extent to which adextrals are underrepresented in neuroimaging study samples, and to delineate potential trends in this bias. Handedness data were available for over 30,000 research subjects; only around 3%–4% of these individuals were adextral—considerably less than the 10% benchmark one would expect if neuroimaging samples were truly representative of the general population. This observation was generally consistent across different areas of research, but was modulated by the demographic characteristics of neuroimaging participants. The epistemological and ethical implications of these findings are discussed.

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“…Another field that can benefit from this independent understanding is neuroscience, where handdominance is commonly associated with several neurological factors [19]. For example, the authors of [20,21] found significant differences in the hand-dominance level of children with Autism Spectrum Disorder (ASD). A wearable camera that is able to differentiate between left and right hand is not only in line with biological and neurosciences perspective, but it also opens the doors to understanding hands as two interacting entities, centrally coordinated to achieve a particular goal.…”

Section: Introductionmentioning

confidence: 99%

Left/right hand segmentation in egocentric videos

Betancourt

Morerio

Barakova

et al. 2017

Computer Vision and Image Understanding

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Wearable cameras allow people to record their daily activities from a user-centered (First Person Vision) perspective. Due to their favorable location, wearable cameras frequently capture the hands of the user, and may thus represent a promising usermachine interaction tool for different applications. Existent First Person Vision methods handle hand segmentation as a backgroundforeground problem, ignoring two important facts: i) hands are not a single "skin-like" moving element, but a pair of interacting cooperative entities, ii) close hand interactions may lead to hand-to-hand occlusions and, as a consequence, create a single hand-like segment. These facts complicate a proper understanding of hand movements and interactions. Our approach extends traditional background-foreground strategies, by including a hand-identification step (left-right) based on a Maxwell distribution of angle and position. Hand-to-hand occlusions are addressed by exploiting temporal superpixels. The experimental results show that, in addition to a reliable left/right hand-segmentation, our approach considerably improves the traditional background-foreground hand-segmentation.

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Handedness in Children With Autism Spectrum Disorder

Cited by 21 publications

References 64 publications

Children with Autism Spectrum Disorder Show Impairments During Dynamic Versus Static Grip‐force Tracking

Children with Autism Spectrum Disorder Show Impairments During Dynamic Versus Static Grip‐force Tracking

A sinister subject: Quantifying handedness‐based recruitment biases in current neuroimaging research

Left/right hand segmentation in egocentric videos

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