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Incorporating Measures of Intermodal Coordination in Automated Analysis of Infant-Mother Interaction

Published: 22 October 2020 Publication History

Abstract

Interactions between infants and their mothers can provide meaningful insight into the dyad's health and well-being. Previous work has shown that infant-mother coordination, within a single modality, varies significantly with age and interaction quality. However, as infants are still developing their motor, language, and social skills, they may differ from their mothers in the modes they use to communicate. This work examines how infant-mother coordination across modalities can expand researchers' abilities to observe meaningful trends in infant-mother interactions. Using automated feature extraction tools, we analyzed the head position, arm position, and vocal fundamental frequency of mothers and their infants during the Face-to-Face Still-Face (FFSF) procedure. A de-identified dataset including these features was made available online as a contribution of this work. Analysis of infant behavior over the course of the FFSF indicated that the amount and modality of infant behavior change evolves with age. Evaluating the interaction dynamics, we found that infant and mother behavioral signals are coordinated both within and across modalities, and that levels of both intramodal and intermodal coordination vary significantly with age and across stages of the FFSF. These results support the significance of intermodal coordination when assessing changes in infant-mother interaction across conditions.

Supplementary Material

MP4 File (3382507.3418870.mp4)
Infant-mother interactions can provide meaningful insight into the dyad?s well-being. Previous work has shown that infant-mother coordination, within a single modality, varies significantly with age and interaction quality. However, as infants are still developing motor and social skills, they may differ from their mothers in the modes they use to communicate. This work examines how coordination across modalities can be used to identify meaningful trends in infant-mother interactions. Using automated feature extraction, we analyzed the head position, arm position, and vocal fundamental frequency of mothers and their infants during the Face-to-Face Still-Face (FFSF) procedure. Results indicated that infant and mother behavioral signals were coordinated both within and across modalities, and that levels of coordination varied significantly across age and stages of the FFSF, supporting the significance of intermodal coordination when assessing changes in infant-mother interaction across conditions.

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Cited By

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  • (2024)Survey of Automated Methods for Nonverbal Behavior Analysis in Parent-Child Interactions2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)10.1109/FG59268.2024.10582009(1-11)Online publication date: 27-May-2024
  • (2023)Quantifying the Quality of Parent-Child Interaction Through Machine-Learning Based Audio and Video Analysis: Towards a Vision of AI-assisted Coaching Support for Social WorkersACM Journal on Computing and Sustainable Societies10.1145/36176932:1(1-21)Online publication date: 1-Sep-2023
  • (2022)Evaluating Temporal Patterns in Applied Infant Affect Recognition2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII)10.1109/ACII55700.2022.9953842(1-8)Online publication date: 18-Oct-2022
  • Show More Cited By

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  1. Incorporating Measures of Intermodal Coordination in Automated Analysis of Infant-Mother Interaction

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      cover image ACM Conferences
      ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction
      October 2020
      920 pages
      ISBN:9781450375818
      DOI:10.1145/3382507
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      Published: 22 October 2020

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      Author Tags

      1. behavioral signal processing
      2. infant-mother interaction
      3. intermodal correlation

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      • JPB Foundation
      • National Science Foundation

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      ICMI '20
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      ICMI '20: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
      October 25 - 29, 2020
      Virtual Event, Netherlands

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      Overall Acceptance Rate 453 of 1,080 submissions, 42%

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      Cited By

      View all
      • (2024)Survey of Automated Methods for Nonverbal Behavior Analysis in Parent-Child Interactions2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG)10.1109/FG59268.2024.10582009(1-11)Online publication date: 27-May-2024
      • (2023)Quantifying the Quality of Parent-Child Interaction Through Machine-Learning Based Audio and Video Analysis: Towards a Vision of AI-assisted Coaching Support for Social WorkersACM Journal on Computing and Sustainable Societies10.1145/36176932:1(1-21)Online publication date: 1-Sep-2023
      • (2022)Evaluating Temporal Patterns in Applied Infant Affect Recognition2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII)10.1109/ACII55700.2022.9953842(1-8)Online publication date: 18-Oct-2022
      • (2021)Dynamic Mode Decomposition with Control as a Model of Multimodal Behavioral CoordinationProceedings of the 2021 International Conference on Multimodal Interaction10.1145/3462244.3479916(25-33)Online publication date: 18-Oct-2021
      • (2021)BabyNet: A Lightweight Network for Infant Reaching Action Recognition in Unconstrained Environments to Support Future Pediatric Rehabilitation Applications2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN)10.1109/RO-MAN50785.2021.9515507(461-467)Online publication date: 8-Aug-2021

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