Atypical Head Movement during Face-to-Face Interaction in Children with Autism Spectrum Disorder / Zhongbo ZHAO in Autism Research, 14-6 (June 2021)  

Public ISBD [article]  inAutism Research > 14-6 (June 2021) . - p.1197-1208 Titre : Atypical Head Movement during Face-to-Face Interaction in Children with Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Zhongbo ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xudong ZHANG, Auteur ; Haiming TANG, Auteur ; J. XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Qiongling PENG, Auteur ; Xingda QU, Auteur Année de publication : 2021 Article en page(s) : p.1197-1208 Langues : Anglais (eng) Mots-clés : Autism Spectrum Disorder  Autistic Disorder  Child  Fixation, Ocular  Head Movements  Humans  Stereotyped Behavior  autism  biomarker  eye tracking  head movement  stereotypy Index. décimale : PER Périodiques Résumé : The present study implemented an objective head pose tracking technique-OpenFace 2.0 to quantify the three dimensional head movement. Children with autism spectrum disorder (ASD) and typical development (TD) were engaged in a structured conversation with an interlocutress while wearing an eye tracker. We computed the head movement stereotypy with multiscale entropy analysis. In addition, the head rotation range (RR) and the amount of rotation per minute (ARPM) were calculated to quantify the extent of head movement. Results demonstrated that the ASD group had significantly higher level of movement stereotypy, RR and ARPM in all the three directions of head movement. Further analyses revealed that the extent of head movement could be significantly explained by movement stereotypy, but not by the amount of visual fixation to the interlocutress. These results demonstrated the atypical head movement dynamics in children with ASD during live interaction. It is proposed that head movement might potentially provide novel objective biomarkers of ASD. LAY SUMMARY: Our study used an objective tool to quantify head movement in children with autism. Results showed that children with autism had more stereotyped and greater head movement. We suggest that head movement tracking technique be widely used in autism research. En ligne : http://dx.doi.org/10.1002/aur.2478 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=449 [article] Atypical Head Movement during Face-to-Face Interaction in Children with Autism Spectrum Disorder [texte imprimé] / Zhongbo ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xudong ZHANG, Auteur ; Haiming TANG, Auteur ; J. XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Qiongling PENG, Auteur ; Xingda QU, Auteur . - 2021 . - p.1197-1208. Langues : Anglais (eng) in Autism Research > 14-6 (June 2021) . - p.1197-1208 Mots-clés : Autism Spectrum Disorder  Autistic Disorder  Child  Fixation, Ocular  Head Movements  Humans  Stereotyped Behavior  autism  biomarker  eye tracking  head movement  stereotypy Index. décimale : PER Périodiques Résumé : The present study implemented an objective head pose tracking technique-OpenFace 2.0 to quantify the three dimensional head movement. Children with autism spectrum disorder (ASD) and typical development (TD) were engaged in a structured conversation with an interlocutress while wearing an eye tracker. We computed the head movement stereotypy with multiscale entropy analysis. In addition, the head rotation range (RR) and the amount of rotation per minute (ARPM) were calculated to quantify the extent of head movement. Results demonstrated that the ASD group had significantly higher level of movement stereotypy, RR and ARPM in all the three directions of head movement. Further analyses revealed that the extent of head movement could be significantly explained by movement stereotypy, but not by the amount of visual fixation to the interlocutress. These results demonstrated the atypical head movement dynamics in children with ASD during live interaction. It is proposed that head movement might potentially provide novel objective biomarkers of ASD. LAY SUMMARY: Our study used an objective tool to quantify head movement in children with autism. Results showed that children with autism had more stereotyped and greater head movement. We suggest that head movement tracking technique be widely used in autism research. En ligne : http://dx.doi.org/10.1002/aur.2478 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=449

Correction to: Random and ShortTerm Excessive Eye Movement in Children with Autism During FacetoFace Conversation / Zhong ZHAO in Journal of Autism and Developmental Disorders, 52-8 (August 2022)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 52-8 (August 2022) . - p.3711 Titre : Correction to: Random and ShortTerm Excessive Eye Movement in Children with Autism During FacetoFace Conversation Type de document : texte imprimé Auteurs : Zhong ZHAO, Auteur ; Jiayi XING, Auteur ; Xiaobin ZHANG, Auteur ; Xingda QU, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur Article en page(s) : p.3711 Langues : Anglais (eng) Index. décimale : PER Périodiques En ligne : http://dx.doi.org/10.1007/s10803-021-05294-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=485 [article] Correction to: Random and ShortTerm Excessive Eye Movement in Children with Autism During FacetoFace Conversation [texte imprimé] / Zhong ZHAO, Auteur ; Jiayi XING, Auteur ; Xiaobin ZHANG, Auteur ; Xingda QU, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur . - p.3711. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 52-8 (August 2022) . - p.3711 Index. décimale : PER Périodiques En ligne : http://dx.doi.org/10.1007/s10803-021-05294-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=485

Excessive and less complex body movement in children with autism during face-to-face conversation: An objective approach to behavioral quantification / Zhongbo ZHAO in Autism Research, 15-2 (February 2022)  

Public ISBD [article]  inAutism Research > 15-2 (February 2022) . - p.305-316 Titre : Excessive and less complex body movement in children with autism during face-to-face conversation: An objective approach to behavioral quantification Type de document : texte imprimé Auteurs : Zhongbo ZHAO, Auteur ; Haiming TANG, Auteur ; Camila ALVIAR, Auteur ; Christopher T. KELLO, Auteur ; Xudong ZHANG, Auteur ; Xinyao HU, Auteur ; Xingda QU, Auteur ; Jianping LU, Auteur Année de publication : 2022 Article en page(s) : p.305-316 Langues : Anglais (eng) Mots-clés : autism  complexity matching  face-to-face  movement dynamics  social interaction  spectral analysis Index. décimale : PER Périodiques Résumé : The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty-three children with typical development (TD) were videotaped while engaged in a face-to-face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions. LAY SUMMARY: By implementing an objective behavioral quantifying technique, our study demonstrated that children with autism had more body movement during face-to-face conversation, and they moved in a less complex way. The current diagnosis of autism heavily relies on doctor's experiences. These findings suggest a potential that autism might be automatically screened during daily social interactions. En ligne : http://dx.doi.org/10.1002/aur.2646 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=450 [article] Excessive and less complex body movement in children with autism during face-to-face conversation: An objective approach to behavioral quantification [texte imprimé] / Zhongbo ZHAO, Auteur ; Haiming TANG, Auteur ; Camila ALVIAR, Auteur ; Christopher T. KELLO, Auteur ; Xudong ZHANG, Auteur ; Xinyao HU, Auteur ; Xingda QU, Auteur ; Jianping LU, Auteur . - 2022 . - p.305-316. Langues : Anglais (eng) in Autism Research > 15-2 (February 2022) . - p.305-316 Mots-clés : autism  complexity matching  face-to-face  movement dynamics  social interaction  spectral analysis Index. décimale : PER Périodiques Résumé : The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty-three children with typical development (TD) were videotaped while engaged in a face-to-face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions. LAY SUMMARY: By implementing an objective behavioral quantifying technique, our study demonstrated that children with autism had more body movement during face-to-face conversation, and they moved in a less complex way. The current diagnosis of autism heavily relies on doctor's experiences. These findings suggest a potential that autism might be automatically screened during daily social interactions. En ligne : http://dx.doi.org/10.1002/aur.2646 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=450

Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms / Zhong ZHAO in Journal of Autism and Developmental Disorders, 52-7 (July 2022)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 52-7 (July 2022) . - p.3038-3049 Titre : Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms Type de document : texte imprimé Auteurs : Zhong ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xiaobin ZHANG, Auteur ; Haiming TANG, Auteur ; Jiayi XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Xingda QU, Auteur Article en page(s) : p.3038-3049 Langues : Anglais (eng) Mots-clés : Algorithms  Autism Spectrum Disorder/diagnosis  Autistic Disorder  Child  Head Movements  Humans  Machine Learning  Autism  Biomarkers  Diagnosis  Head movement Index. décimale : PER Périodiques Résumé : Our study investigated the feasibility of using head movement features to identify individuals with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were required to answer ten yes-no questions, and they were encouraged to nod/shake head while doing so. The head rotation range (RR) and the amount of rotation per minute (ARPM) in the pitch (head nodding direction), yaw (head shaking direction) and roll (lateral head inclination) directions were computed, and further fed into machine learning classifiers as the input features. The maximum classification accuracy of 92.11% was achieved with the decision tree classifier with two features (i.e., RR_Pitch and ARPM_Yaw). Our study suggests that head movement dynamics contain objective biomarkers that could identify ASD. En ligne : http://dx.doi.org/10.1007/s10803-021-05179-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=477 [article] Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms [texte imprimé] / Zhong ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xiaobin ZHANG, Auteur ; Haiming TANG, Auteur ; Jiayi XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Xingda QU, Auteur . - p.3038-3049. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 52-7 (July 2022) . - p.3038-3049 Mots-clés : Algorithms  Autism Spectrum Disorder/diagnosis  Autistic Disorder  Child  Head Movements  Humans  Machine Learning  Autism  Biomarkers  Diagnosis  Head movement Index. décimale : PER Périodiques Résumé : Our study investigated the feasibility of using head movement features to identify individuals with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were required to answer ten yes-no questions, and they were encouraged to nod/shake head while doing so. The head rotation range (RR) and the amount of rotation per minute (ARPM) in the pitch (head nodding direction), yaw (head shaking direction) and roll (lateral head inclination) directions were computed, and further fed into machine learning classifiers as the input features. The maximum classification accuracy of 92.11% was achieved with the decision tree classifier with two features (i.e., RR_Pitch and ARPM_Yaw). Our study suggests that head movement dynamics contain objective biomarkers that could identify ASD. En ligne : http://dx.doi.org/10.1007/s10803-021-05179-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=477

Random and Short-Term Excessive Eye Movement in Children with Autism During Face-to-Face Conversation / Zhong ZHAO in Journal of Autism and Developmental Disorders, 52-8 (August 2022)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 52-8 (August 2022) . - p.3699-3710 Titre : Random and Short-Term Excessive Eye Movement in Children with Autism During Face-to-Face Conversation Type de document : texte imprimé Auteurs : Zhong ZHAO, Auteur ; Jiayi XING, Auteur ; Xiaobin ZHANG, Auteur ; Xingda QU, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur Article en page(s) : p.3699-3710 Langues : Anglais (eng) Mots-clés : Autism Spectrum Disorder  Autistic Disorder  Child  Communication  Eye Movements  Humans  Autism  Entropy  Eye movement quantity  Eye tracking  Face-to-face interaction  Oculomotor Index. décimale : PER Périodiques Résumé : This study investigated the oculomotor performance in children with autism spectrum disorder (ASD) during a face-to-face conversation. A head mounted eye tracker recorded the eye movements in 20 children with ASD and 23 children with typical development (TD). Group comparisons were conducted on the randomness and the quantity of eye movement. The amount of time needed to reveal group difference was also examined. Results showed that the randomness of eye movement was significantly higher at all examined time durations, and the amount of eye movement was significantly greater within 3 s in the ASD group. These findings demonstrated an atypical pattern of oculomotor dynamics in children ASD, which might facilitate the objective identification of ASD during daily social interaction. En ligne : http://dx.doi.org/10.1007/s10803-021-05255-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=485 [article] Random and Short-Term Excessive Eye Movement in Children with Autism During Face-to-Face Conversation [texte imprimé] / Zhong ZHAO, Auteur ; Jiayi XING, Auteur ; Xiaobin ZHANG, Auteur ; Xingda QU, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur . - p.3699-3710. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 52-8 (August 2022) . - p.3699-3710 Mots-clés : Autism Spectrum Disorder  Autistic Disorder  Child  Communication  Eye Movements  Humans  Autism  Entropy  Eye movement quantity  Eye tracking  Face-to-face interaction  Oculomotor Index. décimale : PER Périodiques Résumé : This study investigated the oculomotor performance in children with autism spectrum disorder (ASD) during a face-to-face conversation. A head mounted eye tracker recorded the eye movements in 20 children with ASD and 23 children with typical development (TD). Group comparisons were conducted on the randomness and the quantity of eye movement. The amount of time needed to reveal group difference was also examined. Results showed that the randomness of eye movement was significantly higher at all examined time durations, and the amount of eye movement was significantly greater within 3 s in the ASD group. These findings demonstrated an atypical pattern of oculomotor dynamics in children ASD, which might facilitate the objective identification of ASD during daily social interaction. En ligne : http://dx.doi.org/10.1007/s10803-021-05255-7 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=485

Use of Oculomotor Behavior to Classify Children with Autism and Typical Development: A Novel Implementation of the Machine Learning Approach / Zhong ZHAO in Journal of Autism and Developmental Disorders, 53-3 (March 2023)  

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