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Early screening of autism spectrum disorder using cry features.

ABSTRACT: The increase in the number of children with autism and the importance of early autism intervention has prompted researchers to perform automatic and early autism screening. Consequently, in the present paper, a cry-based screening approach for children with Autism Spectrum Disorder (ASD) is introduced which would provide both early and automatic screening. During the study, we realized that ASD specific features are not necessarily observable in all children with ASD and in all instances collected from each child. Therefore, we proposed a new classification approach to be able to determine such features and their corresponding instances. To test the proposed approach a set of data relating to children between 18 to 53 months which had been recorded using high-quality voice recording devices and typical smartphones at various locations such as homes and daycares was studied. Then, after preprocessing, the approach was used to train a classifier, using data for 10 boys with ASD and 10 Typically Developed (TD) boys. The trained classifier was tested on the data of 14 boys and 7 girls with ASD and 14 TD boys and 7 TD girls. The sensitivity, specificity, and precision of the proposed approach for boys were 85.71%, 100%, and 92.85%, respectively. These measures were 71.42%, 100%, and 85.71% for girls, respectively. It was shown that the proposed approach outperforms the common classification methods. Furthermore, it demonstrated better results than the studies which used voice features for screening ASD. To pilot the practicality of the proposed approach for early autism screening, the trained classifier was tested on 57 participants between 10 to 18 months. These 57 participants consisted of 28 boys and 29 girls and the results were very encouraging for the use of the approach in early ASD screening.

SUBMITTER: Khozaei A

PROVIDER: S-EPMC7728261 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Early screening of autism spectrum disorder using cry features.

Khozaei Aida A Moradi Hadi H Hosseini Reshad R Pouretemad Hamidreza H Eskandari Bahareh B

PloS one 20201210 12

The increase in the number of children with autism and the importance of early autism intervention has prompted researchers to perform automatic and early autism screening. Consequently, in the present paper, a cry-based screening approach for children with Autism Spectrum Disorder (ASD) is introduced which would provide both early and automatic screening. During the study, we realized that ASD specific features are not necessarily observable in all children with ASD and in all instances collect ...[more]

PMID: 33301502

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Project description:The need for early treatment of autism spectrum disorders (ASD) necessitates early screening. Very few tools have been prospectively tested with infants of less than 12 months of age. The PREAUT grid is based on dyadic assessment through interaction and shared emotion and showed good metrics for predicting ASD in very-high-risk infants with West syndrome.We assessed the ability of the PREAUT grid to predict ASD in low-risk individuals by prospectively following and screening 12,179 infants with the PREAUT grid at four (PREAUT-4) and nine (PREAUT-9) months of age. A sample of 4,835 toddlers completed the Checklist for Autism in Toddlers (CHAT) at 24 months (CHAT-24) of age. Children who were positive at one screening (N = 100) were proposed a clinical assessment (including the Children Autism Rating Scale, a Developmental Quotient, and an ICD-10-based clinical diagnosis if appropriate) in the third year of life. A randomly selected sample of 1,100 individuals who were negative at all screenings was followed by the PMI team from three to five years of age to identify prospective false negative cases. The clinical outcome was available for 45% (N = 45) of positive children and 52.6% (N = 579) of negative children.Of the 100 children who screened positive, 45 received a diagnosis at follow-up. Among those receiving a diagnosis, 22 were healthy, 10 were diagnosed with ASD, seven with intellectual disability (ID), and six had another developmental disorder. Thus, 50% of infants positive at one screening subsequently received a neurodevelopmental diagnosis. The PREAUT grid scores were significantly associated with medium and high ASD risk status on the CHAT at 24 months (odds ratio of 12.1 (95%CI: 3.0-36.8), p < 0.001, at four months and 38.1 (95%CI: 3.65-220.3), p < 0.001, at nine months). Sensitivity (Se), specificity, negative predictive values, and positive predictive values (PPVs) for PREAUT at four or nine months, and CHAT at 24 months, were similar [PREAUT-4: Se = 16.0 to 20.6%, PPV = 25.4 to 26.3%; PREAUT-9: Se = 30.5 to 41.2%, PPV = 20.2 to 36.4%; and CHAT-24: Se = 33.9 to 41.5%, PPV = 27.3 to 25.9%]. The repeated use of the screening instruments increased the Se but not PPV estimates [PREAUT and CHAT combined: Se = 67.9 to 77.7%, PPV = 19.0 to 28.0%].The PREAUT grid can contribute to very early detection of ASD and its combination with the CHAT may improve the early diagnosis of ASD and other neurodevelopmental disorders.

Dataset Information

Early screening of autism spectrum disorder using cry features.

Publications

Early screening of autism spectrum disorder using cry features.

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