Furui Lab LogoIntelligent BiosignalInformatics Lab
Research Projects

Infant Motion Analysis Using Video Images

Medical Application Systems and Interface Development

Infant Motion Analysis Using Video Images

Research Overview

Construction of AI image analysis systems supporting developmental assessment

We are developing automatic evaluation systems using video image analysis technology to objectively evaluate infant motor development. This system aims to support specialist diagnosis and provide opportunities for early intervention. Research approach: - Markerless measurement using RGB cameras - Automation of General Movements assessment - Quantification of developmental indicators according to age We are advancing this in collaboration with Prefectural University of Hiroshima and Nagaoka University of Technology.

Keywords

Motion AnalysisPediatricsComputer Vision

Quick Links

All PublicationsContact Us

Related Publications

View All →
2025Int'l Conf.

Discriminative analysis of autistic tendencies at 18 months of age using eye gaze characteristics in 4-, 10-, and 18-month-old infants

Rena Ueda, Hirokazu Doi, Akira Furui et al.

Proceedings of 2025 IEEE/SICE international symposium on system integration (SII)

InfantsMedical Imaging
2025Int'l Conf.

Non-negative tensor factorization of infant spontaneous movements: a pilot study for ASD risk evaluation of newborn infants

Rikuya Yonei, Akira Furui, Hirokazu Doi et al.

Proceedings of 2025 IEEE/SICE international symposium on system integration (SII)

InfantsMedical Imaging+1
2024Journal

Risk of autism spectrum disorder at 18 months of age is associated with prenatal level of polychlorinated biphenyls exposure in a Japanese birth cohort

Hirokazu Doi, Akira Furui, Rena Ueda et al.

Scientific Reports

DOI
2023Journal

Spatiotemporal patterns of spontaneous movement in neonates are significantly linked to risk of autism spectrum disorders at 18 months old

Hirokazu Doi, Akira Furui, Rena Ueda et al.

Scientific Reports

DOI
2022Journal

Prediction of autistic tendencies at 18 months of age via markerless video analysis of spontaneous body movements in 4-month-old infants

Hirokazu Doi, Naoya Iijima, Akira Furui et al.

Scientific Reports

DOI
2022Int'l Conf.

Automated classification of general movements in infants using two-stream spatiotemporal fusion network

Yuki Hashimoto, Akira Furui, Koji Shimatani et al.

Proceedings of 25th international conference on medical image computing and computer assisted intervention (MICCAI2022)

InfantsMotion Analysis+1
PDFCodeDOI
2020Journal

Longitudinal assessment of U-shaped and inverted U-shaped developmental changes in the spontaneous movements of infants via markerless video analysis

Naoki Kinoshita, Akira Furui, Zu Soh et al.

Scientific Reports

DOI
2020Journal

Video-based evaluation of infant crawling toward quantitative assessment of motor development

Katsuaki Kawashima, Yasuko Funabiki, Shino Ogawa et al.

Scientific Reports

DOI
2020Journal

Markerless measurement and evaluation of general movements in infants

Toshio Tsuji, Shota Nakashima, Hideaki Hayashi et al.

Scientific Reports

DOI
2026Int'l Conf.

Movement-specific analysis for FIM score classification using spatio-temporal deep learning

Jun Masaki, Ariaki Higashi, Naoko Shinagawa et al.

2026 IEEE/SICE international symposium on system integration (SII)

FIMMotion Analysis+1
2025Domestic Conf.

VAEによる油圧ショベル操作パターンの階層的解析と操作者の潜在状態評価への応用

塚本修平, 沖本翔, 正木淳 et al.

第26回計測自動制御学会システムインテグレーション部門講演会（SI2025）

Hydraulic ExcavatorVAE+1
2025Domestic Conf.

深層学習を用いた簡易動作群の総合解析に基づくFIM運動項目スコア推定

正木淳, 東有明, 品川直子 et al.

第26回計測自動制御学会システムインテグレーション部門講演会（SI2025）

FIMMotion Analysis+1
2025Domestic Conf.

骨格推定と時空間深層学習によるFIM運動項目スコア評価の基礎検討

正木淳, 廣池友哉, 東有明 et al.

ロボティクス・メカトロニクス講演会2025 (ROBOMECH2025)

FIMMotion Analysis+1