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Auteur Guillermo SAPIRO |
Documents disponibles écrits par cet auteur (5)
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Complexity analysis of head movements in autistic toddlers / Pradeep Raj KRISHNAPPA BABU in Journal of Child Psychology and Psychiatry, 64-1 (January 2023)
[article]
Titre : Complexity analysis of head movements in autistic toddlers Type de document : Texte imprimé et/ou numérique Auteurs : Pradeep Raj KRISHNAPPA BABU, Auteur ; J. Matias DI MARTINO, Auteur ; Zhuoqing CHANG, Auteur ; Sam PEROCHON, Auteur ; Rachel AIELLO, Auteur ; Kimberly L.H. CARPENTER, Auteur ; Scott COMPTON, Auteur ; Naomi DAVIS, Auteur ; Lauren FRANZ, Auteur ; Steven ESPINOSA, Auteur ; Jacqueline FLOWERS, Auteur ; Geraldine DAWSON, Auteur ; Guillermo SAPIRO, Auteur Article en page(s) : p.156-166 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Background Early differences in sensorimotor functioning have been documented in young autistic children and infants who are later diagnosed with autism. Previous research has demonstrated that autistic toddlers exhibit more frequent head movement when viewing dynamic audiovisual stimuli, compared to neurotypical toddlers. To further explore this behavioral characteristic, in this study, computer vision (CV) analysis was used to measure several aspects of head movement dynamics of autistic and neurotypical toddlers while they watched a set of brief movies with social and nonsocial content presented on a tablet. Methods Data were collected from 457 toddlers, 17-36 months old, during their well-child visit to four pediatric primary care clinics. Forty-one toddlers were subsequently diagnosed with autism. An application (app) displayed several brief movies on a tablet, and the toddlers watched these movies while sitting on their caregiver's lap. The front-facing camera in the tablet recorded the toddlers' behavioral responses. CV was used to measure the participants' head movement rate, movement acceleration, and complexity using multiscale entropy. Results Autistic toddlers exhibited significantly higher rate, acceleration, and complexity in their head movements while watching the movies compared to neurotypical toddlers, regardless of the type of movie content (social vs. nonsocial). The combined features of head movement acceleration and complexity reliably distinguished the autistic and neurotypical toddlers. Conclusions Autistic toddlers exhibit differences in their head movement dynamics when viewing audiovisual stimuli. Higher complexity of their head movements suggests that their movements were less predictable and less stable compared to neurotypical toddlers. CV offers a scalable means of detecting subtle differences in head movement dynamics, which may be helpful in identifying early behaviors associated with autism and providing insight into the nature of sensorimotor differences associated with autism. En ligne : https://doi.org/10.1111/jcpp.13681 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=490
in Journal of Child Psychology and Psychiatry > 64-1 (January 2023) . - p.156-166[article] Complexity analysis of head movements in autistic toddlers [Texte imprimé et/ou numérique] / Pradeep Raj KRISHNAPPA BABU, Auteur ; J. Matias DI MARTINO, Auteur ; Zhuoqing CHANG, Auteur ; Sam PEROCHON, Auteur ; Rachel AIELLO, Auteur ; Kimberly L.H. CARPENTER, Auteur ; Scott COMPTON, Auteur ; Naomi DAVIS, Auteur ; Lauren FRANZ, Auteur ; Steven ESPINOSA, Auteur ; Jacqueline FLOWERS, Auteur ; Geraldine DAWSON, Auteur ; Guillermo SAPIRO, Auteur . - p.156-166.
Langues : Anglais (eng)
in Journal of Child Psychology and Psychiatry > 64-1 (January 2023) . - p.156-166
Index. décimale : PER Périodiques Résumé : Background Early differences in sensorimotor functioning have been documented in young autistic children and infants who are later diagnosed with autism. Previous research has demonstrated that autistic toddlers exhibit more frequent head movement when viewing dynamic audiovisual stimuli, compared to neurotypical toddlers. To further explore this behavioral characteristic, in this study, computer vision (CV) analysis was used to measure several aspects of head movement dynamics of autistic and neurotypical toddlers while they watched a set of brief movies with social and nonsocial content presented on a tablet. Methods Data were collected from 457 toddlers, 17-36 months old, during their well-child visit to four pediatric primary care clinics. Forty-one toddlers were subsequently diagnosed with autism. An application (app) displayed several brief movies on a tablet, and the toddlers watched these movies while sitting on their caregiver's lap. The front-facing camera in the tablet recorded the toddlers' behavioral responses. CV was used to measure the participants' head movement rate, movement acceleration, and complexity using multiscale entropy. Results Autistic toddlers exhibited significantly higher rate, acceleration, and complexity in their head movements while watching the movies compared to neurotypical toddlers, regardless of the type of movie content (social vs. nonsocial). The combined features of head movement acceleration and complexity reliably distinguished the autistic and neurotypical toddlers. Conclusions Autistic toddlers exhibit differences in their head movement dynamics when viewing audiovisual stimuli. Higher complexity of their head movements suggests that their movements were less predictable and less stable compared to neurotypical toddlers. CV offers a scalable means of detecting subtle differences in head movement dynamics, which may be helpful in identifying early behaviors associated with autism and providing insight into the nature of sensorimotor differences associated with autism. En ligne : https://doi.org/10.1111/jcpp.13681 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=490 Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism / Kimberly L. H. CARPENTER in Autism Research, 14-3 (March 2021)
[article]
Titre : Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism Type de document : Texte imprimé et/ou numérique Auteurs : Kimberly L. H. CARPENTER, Auteur ; Jordan HAHEMI, Auteur ; Kathleen CAMPBELL, Auteur ; Steven J. LIPPMANN, Auteur ; Jeffrey P. BAKER, Auteur ; Helen L. EGGER, Auteur ; Steven ESPINOSA, Auteur ; Saritha VERMEER, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur Article en page(s) : p.488-499 Langues : Anglais (eng) Mots-clés : autism computer vision early detection facial expressions risk behaviors Amazon, Google, Cisco, and Microsoft and is a consultant for Apple and Volvo. Geraldine Dawson is on the Scientific Advisory Boards of Janssen Research and Development, Akili, Inc., LabCorp, Inc., Tris Pharma, and Roche Pharmaceutical Company, a consultant for Apple, Inc, Gerson Lehrman Group, Guidepoint, Inc., Teva Pharmaceuticals, and Axial Ventures, has received grant funding from Janssen Research and Development, and is CEO of DASIO, LLC (with Guillermo Sapiro). Dawson receives royalties from Guilford Press, Springer, and Oxford University Press. Dawson, Sapiro, Carpenter, Hashemi, Campbell, Espinosa, Baker, and Egger helped develop aspects of the technology that is being used in the study. The technology has been licensed and Dawson, Sapiro, Carpenter, Hashemi, Espinosa, Baker, Egger, and Duke University have benefited financially. Index. décimale : PER Périodiques Résumé : Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time-consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors. This study assessed the utility of a tablet-based behavioral assessment for eliciting and detecting one type of risk behavior, namely, patterns of facial expression, in 104 toddlers (ASD N =?22) and evaluated whether such patterns differentiated toddlers with and without ASD. The assessment consisted of the child sitting on his/her caregiver's lap and watching brief movies shown on a smart tablet while the embedded camera recorded the child's facial expressions. Computer vision analysis (CVA) automatically detected and tracked facial landmarks, which were used to estimate head position and facial expressions (Positive, Neutral, All Other). Using CVA, specific points throughout the movies were identified that reliably differentiate between children with and without ASD based on their patterns of facial movement and expressions (area under the curves for individual movies ranging from 0.62 to 0.73). During these instances, children with ASD more frequently displayed Neutral expressions compared to children without ASD, who had more All Other expressions. The frequency of All Other expressions was driven by non-ASD children more often displaying raised eyebrows and an open mouth, characteristic of engagement/interest. Preliminary results suggest computational coding of facial movements and expressions via a tablet-based assessment can detect differences in affective expression, one of the early, core features of ASD. LAY SUMMARY: This study tested the use of a tablet in the behavioral assessment of young children with autism. Children watched a series of developmentally appropriate movies and their facial expressions were recorded using the camera embedded in the tablet. Results suggest that computational assessments of facial expressions may be useful in early detection of symptoms of autism. En ligne : http://dx.doi.org/10.1002/aur.2391 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443
in Autism Research > 14-3 (March 2021) . - p.488-499[article] Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism [Texte imprimé et/ou numérique] / Kimberly L. H. CARPENTER, Auteur ; Jordan HAHEMI, Auteur ; Kathleen CAMPBELL, Auteur ; Steven J. LIPPMANN, Auteur ; Jeffrey P. BAKER, Auteur ; Helen L. EGGER, Auteur ; Steven ESPINOSA, Auteur ; Saritha VERMEER, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur . - p.488-499.
Langues : Anglais (eng)
in Autism Research > 14-3 (March 2021) . - p.488-499
Mots-clés : autism computer vision early detection facial expressions risk behaviors Amazon, Google, Cisco, and Microsoft and is a consultant for Apple and Volvo. Geraldine Dawson is on the Scientific Advisory Boards of Janssen Research and Development, Akili, Inc., LabCorp, Inc., Tris Pharma, and Roche Pharmaceutical Company, a consultant for Apple, Inc, Gerson Lehrman Group, Guidepoint, Inc., Teva Pharmaceuticals, and Axial Ventures, has received grant funding from Janssen Research and Development, and is CEO of DASIO, LLC (with Guillermo Sapiro). Dawson receives royalties from Guilford Press, Springer, and Oxford University Press. Dawson, Sapiro, Carpenter, Hashemi, Campbell, Espinosa, Baker, and Egger helped develop aspects of the technology that is being used in the study. The technology has been licensed and Dawson, Sapiro, Carpenter, Hashemi, Espinosa, Baker, Egger, and Duke University have benefited financially. Index. décimale : PER Périodiques Résumé : Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time-consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors. This study assessed the utility of a tablet-based behavioral assessment for eliciting and detecting one type of risk behavior, namely, patterns of facial expression, in 104 toddlers (ASD N =?22) and evaluated whether such patterns differentiated toddlers with and without ASD. The assessment consisted of the child sitting on his/her caregiver's lap and watching brief movies shown on a smart tablet while the embedded camera recorded the child's facial expressions. Computer vision analysis (CVA) automatically detected and tracked facial landmarks, which were used to estimate head position and facial expressions (Positive, Neutral, All Other). Using CVA, specific points throughout the movies were identified that reliably differentiate between children with and without ASD based on their patterns of facial movement and expressions (area under the curves for individual movies ranging from 0.62 to 0.73). During these instances, children with ASD more frequently displayed Neutral expressions compared to children without ASD, who had more All Other expressions. The frequency of All Other expressions was driven by non-ASD children more often displaying raised eyebrows and an open mouth, characteristic of engagement/interest. Preliminary results suggest computational coding of facial movements and expressions via a tablet-based assessment can detect differences in affective expression, one of the early, core features of ASD. LAY SUMMARY: This study tested the use of a tablet in the behavioral assessment of young children with autism. Children watched a series of developmentally appropriate movies and their facial expressions were recorded using the camera embedded in the tablet. Results suggest that computational assessments of facial expressions may be useful in early detection of symptoms of autism. En ligne : http://dx.doi.org/10.1002/aur.2391 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443 Impact of a digital Modified Checklist for Autism in Toddlers-Revised on likelihood and age of autism diagnosis and referral for developmental evaluation / Samantha MAJOR in Autism, 24-7 (October 2020)
[article]
Titre : Impact of a digital Modified Checklist for Autism in Toddlers-Revised on likelihood and age of autism diagnosis and referral for developmental evaluation Type de document : Texte imprimé et/ou numérique Auteurs : Samantha MAJOR, Auteur ; Kathleen CAMPBELL, Auteur ; Steven ESPINOSA, Auteur ; Jeffrey P. BAKER, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Guillermo SAPIRO, Auteur ; Saritha VERMEER, Auteur ; Geraldine DAWSON, Auteur Article en page(s) : p.1629-1638 Langues : Anglais (eng) Mots-clés : *asd *developmental evaluation *quality improvement *screening Inc, LabCorp, Inc, Roche Pharmaceutical Company, and Tris Pharma, and is a consultant to Apple, Gerson Lehrman Group, Guidepoint, Inc, Axial Ventures, and Teva Pharmaceutical. GD and GS are associated with DASIO, LLC. GD has received book royalties from Guilford Press, Oxford University Press, Springer Nature Press. GD has the following patent applications: 1802952, 1802942, 15141391, and 16493754. SE, KC, GD, and GS have developed technology that has been licensed and they and Duke University have benefited financially. Index. décimale : PER Périodiques Résumé : This was a project in primary care for young children (1-2?years old). We tested a parent questionnaire on a tablet. This tablet questionnaire asked questions to see whether the child may have autism. We compared the paper and pencil version of the questionnaire to the tablet questionnaire. We read the medical charts for the children until they were 4?years old to see whether they ended up having autism. We found that doctors were more likely to recommend an autism evaluation when a parent used the tablet questionnaire. We think that the tablet's automatic scoring feature helped the doctors. We also think that the doctors benefited from the advice the tablet gave them. En ligne : http://dx.doi.org/10.1177/1362361320916656 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=431
in Autism > 24-7 (October 2020) . - p.1629-1638[article] Impact of a digital Modified Checklist for Autism in Toddlers-Revised on likelihood and age of autism diagnosis and referral for developmental evaluation [Texte imprimé et/ou numérique] / Samantha MAJOR, Auteur ; Kathleen CAMPBELL, Auteur ; Steven ESPINOSA, Auteur ; Jeffrey P. BAKER, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Guillermo SAPIRO, Auteur ; Saritha VERMEER, Auteur ; Geraldine DAWSON, Auteur . - p.1629-1638.
Langues : Anglais (eng)
in Autism > 24-7 (October 2020) . - p.1629-1638
Mots-clés : *asd *developmental evaluation *quality improvement *screening Inc, LabCorp, Inc, Roche Pharmaceutical Company, and Tris Pharma, and is a consultant to Apple, Gerson Lehrman Group, Guidepoint, Inc, Axial Ventures, and Teva Pharmaceutical. GD and GS are associated with DASIO, LLC. GD has received book royalties from Guilford Press, Oxford University Press, Springer Nature Press. GD has the following patent applications: 1802952, 1802942, 15141391, and 16493754. SE, KC, GD, and GS have developed technology that has been licensed and they and Duke University have benefited financially. Index. décimale : PER Périodiques Résumé : This was a project in primary care for young children (1-2?years old). We tested a parent questionnaire on a tablet. This tablet questionnaire asked questions to see whether the child may have autism. We compared the paper and pencil version of the questionnaire to the tablet questionnaire. We read the medical charts for the children until they were 4?years old to see whether they ended up having autism. We found that doctors were more likely to recommend an autism evaluation when a parent used the tablet questionnaire. We think that the tablet's automatic scoring feature helped the doctors. We also think that the doctors benefited from the advice the tablet gave them. En ligne : http://dx.doi.org/10.1177/1362361320916656 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=431 Relationship between quantitative digital behavioral features and clinical profiles in young autistic children / Marika COFFMAN in Autism Research, 16-7 (July 2023)
[article]
Titre : Relationship between quantitative digital behavioral features and clinical profiles in young autistic children Type de document : Texte imprimé et/ou numérique Auteurs : Marika COFFMAN, Auteur ; J. Matias DI MARTINO, Auteur ; Rachel AIELLO, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Zhuoqing CHANG, Auteur ; Scott COMPTON, Auteur ; Brian EICHNER, Auteur ; Steve ESPINOSA, Auteur ; Jacqueline FLOWERS, Auteur ; Lauren FRANZ, Auteur ; Sam PEROCHON, Auteur ; Pradeep Raj KRISHNAPPA BABU, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur Article en page(s) : p.1360-1374 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Abstract Early behavioral markers for autism include differences in social attention and orienting in response to one's name when called, and differences in body movements and motor abilities. More efficient, scalable, objective, and reliable measures of these behaviors could improve early screening for autism. This study evaluated whether objective and quantitative measures of autism-related behaviors elicited from an app (SenseToKnow) administered on a smartphone or tablet and measured via computer vision analysis (CVA) are correlated with standardized caregiver-report and clinician administered measures of autism-related behaviors and cognitive, language, and motor abilities. This is an essential step in establishing the concurrent validity of a digital phenotyping approach. In a sample of 485 toddlers, 43 of whom were diagnosed with autism, we found that CVA-based gaze variables related to social attention were associated with the level of autism-related behaviors. Two language-related behaviors measured via the app, attention to people during a conversation and responding to one's name being called, were associated with children's language skills. Finally, performance during a bubble popping game was associated with fine motor skills. These findings provide initial support for the concurrent validity of the SenseToKnow app and its potential utility in identifying clinical profiles associated with autism. Future research is needed to determine whether the app can be used as an autism screening tool, can reliably stratify autism-related behaviors, and measure changes in autism-related behaviors over time. En ligne : https://doi.org/10.1002/aur.2955 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=510
in Autism Research > 16-7 (July 2023) . - p.1360-1374[article] Relationship between quantitative digital behavioral features and clinical profiles in young autistic children [Texte imprimé et/ou numérique] / Marika COFFMAN, Auteur ; J. Matias DI MARTINO, Auteur ; Rachel AIELLO, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Zhuoqing CHANG, Auteur ; Scott COMPTON, Auteur ; Brian EICHNER, Auteur ; Steve ESPINOSA, Auteur ; Jacqueline FLOWERS, Auteur ; Lauren FRANZ, Auteur ; Sam PEROCHON, Auteur ; Pradeep Raj KRISHNAPPA BABU, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur . - p.1360-1374.
Langues : Anglais (eng)
in Autism Research > 16-7 (July 2023) . - p.1360-1374
Index. décimale : PER Périodiques Résumé : Abstract Early behavioral markers for autism include differences in social attention and orienting in response to one's name when called, and differences in body movements and motor abilities. More efficient, scalable, objective, and reliable measures of these behaviors could improve early screening for autism. This study evaluated whether objective and quantitative measures of autism-related behaviors elicited from an app (SenseToKnow) administered on a smartphone or tablet and measured via computer vision analysis (CVA) are correlated with standardized caregiver-report and clinician administered measures of autism-related behaviors and cognitive, language, and motor abilities. This is an essential step in establishing the concurrent validity of a digital phenotyping approach. In a sample of 485 toddlers, 43 of whom were diagnosed with autism, we found that CVA-based gaze variables related to social attention were associated with the level of autism-related behaviors. Two language-related behaviors measured via the app, attention to people during a conversation and responding to one's name being called, were associated with children's language skills. Finally, performance during a bubble popping game was associated with fine motor skills. These findings provide initial support for the concurrent validity of the SenseToKnow app and its potential utility in identifying clinical profiles associated with autism. Future research is needed to determine whether the app can be used as an autism screening tool, can reliably stratify autism-related behaviors, and measure changes in autism-related behaviors over time. En ligne : https://doi.org/10.1002/aur.2955 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=510 A Six-Minute Measure of Vocalizations in Toddlers with Autism Spectrum Disorder / Elena J. TENENBAUM in Autism Research, 13-8 (August 2020)
[article]
Titre : A Six-Minute Measure of Vocalizations in Toddlers with Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Elena J. TENENBAUM, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Maura SABATOS-DEVITO, Auteur ; Jordan HASHEMI, Auteur ; Saritha VERMEER, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur Article en page(s) : p.1373-1382 Langues : Anglais (eng) Mots-clés : developmental psychology early detection early signs infants language Index. décimale : PER Périodiques Résumé : To improve early identification of autism spectrum disorder (ASD), we need objective, reliable, and accessible measures. To that end, a previous study demonstrated that a tablet-based application (app) that assessed several autism risk behaviors distinguished between toddlers with ASD and non-ASD toddlers. Using vocal data collected during this study, we investigated whether vocalizations uttered during administration of this app can distinguish among toddlers aged 16-31?months with typical development (TD), language or developmental delay (DLD), and ASD. Participant's visual and vocal responses were recorded using the camera and microphone in a tablet while toddlers watched movies designed to elicit behaviors associated with risk for ASD. Vocalizations were then coded offline. Results showed that (a) children with ASD and DLD were less likely to produce words during app administration than TD participants; (b) the ratio of syllabic vocalizations to all vocalizations was higher among TD than ASD or DLD participants; and (c) the rates of nonsyllabic vocalizations were higher in the ASD group than in either the TD or DLD groups. Those producing more nonsyllabic vocalizations were 24 times more likely to be diagnosed with ASD. These results lend support to previous findings that early vocalizations might be useful in identifying risk for ASD in toddlers and demonstrate the feasibility of using a scalable tablet-based app for assessing vocalizations in the context of a routine pediatric visit. LAY SUMMARY: Although parents often report symptoms of autism spectrum disorder (ASD) in infancy, we are not yet reliably diagnosing ASD until much later in development. A previous study tested a tablet-based application (app) that recorded behaviors we know are associated with ASD to help identify children at risk for the disorder. Here we measured how children vocalize while they watched the movies presented on the tablet. Children with ASD were less likely to produce words, less likely to produce speechlike sounds, and more likely to produce atypical sounds while watching these movies. These measures, combined with other behaviors measured by the app, might help identify which children should be evaluated for ASD. Autism Res 2020, 13: 1373-1382. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. En ligne : http://dx.doi.org/10.1002/aur.2293 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=430
in Autism Research > 13-8 (August 2020) . - p.1373-1382[article] A Six-Minute Measure of Vocalizations in Toddlers with Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Elena J. TENENBAUM, Auteur ; Kimberly L. H. CARPENTER, Auteur ; Maura SABATOS-DEVITO, Auteur ; Jordan HASHEMI, Auteur ; Saritha VERMEER, Auteur ; Guillermo SAPIRO, Auteur ; Geraldine DAWSON, Auteur . - p.1373-1382.
Langues : Anglais (eng)
in Autism Research > 13-8 (August 2020) . - p.1373-1382
Mots-clés : developmental psychology early detection early signs infants language Index. décimale : PER Périodiques Résumé : To improve early identification of autism spectrum disorder (ASD), we need objective, reliable, and accessible measures. To that end, a previous study demonstrated that a tablet-based application (app) that assessed several autism risk behaviors distinguished between toddlers with ASD and non-ASD toddlers. Using vocal data collected during this study, we investigated whether vocalizations uttered during administration of this app can distinguish among toddlers aged 16-31?months with typical development (TD), language or developmental delay (DLD), and ASD. Participant's visual and vocal responses were recorded using the camera and microphone in a tablet while toddlers watched movies designed to elicit behaviors associated with risk for ASD. Vocalizations were then coded offline. Results showed that (a) children with ASD and DLD were less likely to produce words during app administration than TD participants; (b) the ratio of syllabic vocalizations to all vocalizations was higher among TD than ASD or DLD participants; and (c) the rates of nonsyllabic vocalizations were higher in the ASD group than in either the TD or DLD groups. Those producing more nonsyllabic vocalizations were 24 times more likely to be diagnosed with ASD. These results lend support to previous findings that early vocalizations might be useful in identifying risk for ASD in toddlers and demonstrate the feasibility of using a scalable tablet-based app for assessing vocalizations in the context of a routine pediatric visit. LAY SUMMARY: Although parents often report symptoms of autism spectrum disorder (ASD) in infancy, we are not yet reliably diagnosing ASD until much later in development. A previous study tested a tablet-based application (app) that recorded behaviors we know are associated with ASD to help identify children at risk for the disorder. Here we measured how children vocalize while they watched the movies presented on the tablet. Children with ASD were less likely to produce words, less likely to produce speechlike sounds, and more likely to produce atypical sounds while watching these movies. These measures, combined with other behaviors measured by the app, might help identify which children should be evaluated for ASD. Autism Res 2020, 13: 1373-1382. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. En ligne : http://dx.doi.org/10.1002/aur.2293 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=430