Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China.

Journal: BMC geriatrics
Published Date: Jul 2, 2025

Abstract

OBJECTIVE: Depression in older adults is a growing public health concern, yet there is still a lack of convenient and real-time methods for depressive symptoms identification. This study aims to develop a gait-based depression recognition method for Chinese community-dwelling older adults.

Authors

  • Shaowu Lin
    School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China.
  • Sicheng Li
    Department of Oral and Maxillofacial Surgery, Key Laboratory of Oral Diseases of Traditional Chinese Medicine, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, 445 Bayi Dadao, Nanchang, 360000, Jiangxi, China.
  • Ya Fang
    The State Key Laboratory of Molecular Vaccine and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361102, China.

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