Psychological and physiological computing based on multi-dimensional foot information

As the population ages, utilizing foot information to continuously monitor the physiological and psychological health status of the elderly is emerging as a pivotal tool for meeting this crucial societal demand. However, few reviews explored how multi-dimensional foot data has been integrated into physiological and psychological computing. This review is essential as it fills a critical knowledge gap in understanding the connections between physiological and psychological disorders and various components of foot information. To identify relevant literature, a thorough search was conducted across IEEE, DBLP, Elsevier, Springer, Google Scholar, and PubMed, initially yielding 2386 publications. After multiple rounds of systematic filtering, 404 publications were selected for in-depth analysis. This review examines (1) the mechanisms linking foot information to human physiological and psychological conditions, (2) the monitoring devices that collect diverse foot-based data, (3) the datasets correlating diseases with multiple foot data, (4) the prevalent feature engineering of different foot data, and (5) the cutting-edge machine and deep learning algorithms for diseases analysis. It also provides insights into future developments in foot information health monitoring for psychological and physiological computing.

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Publication Details

Journal
Artificial Intelligence Review
Published
2025-02-15
DOI
https://doi.org/10.1007/s10462-024-11087-5
Citations
1
Primary Topic
Gait Recognition and Analysis
Type
article
Field-Weighted Citation Impact
0.67
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article

Psychological and physiological computing based on multi-dimensional foot information

Zhiyao Zhao, Siyuan Chen, Shibin Wu, Huilin Yao et al.
1 citations
Artificial Intelligence Review
Gait Recognition and Analysis
0.67
article

Psychological and physiological computing based on multi-dimensional foot information

Zhiyao Zhao, Siyuan Chen, Shibin Wu, Huilin Yao, Bowen Zhang, Jincheng Zhang, Yuanjun Ma, Shengyang Li, Ruotian Peng, Lin Shu
article en
1 citations

Abstract

As the population ages, utilizing foot information to continuously monitor the physiological and psychological health status of the elderly is emerging as a pivotal tool for meeting this crucial societal demand. However, few reviews explored how multi-dimensional foot data has been integrated into physiological and psychological computing. This review is essential as it fills a critical knowledge gap in understanding the connections between physiological and psychological disorders and various components of foot information. To identify relevant literature, a thorough search was conducted across IEEE, DBLP, Elsevier, Springer, Google Scholar, and PubMed, initially yielding 2386 publications. After multiple rounds of systematic filtering, 404 publications were selected for in-depth analysis. This review examines (1) the mechanisms linking foot information to human physiological and psychological conditions, (2) the monitoring devices that collect diverse foot-based data, (3) the datasets correlating diseases with multiple foot data, (4) the prevalent feature engineering of different foot data, and (5) the cutting-edge machine and deep learning algorithms for diseases analysis. It also provides insights into future developments in foot information health monitoring for psychological and physiological computing.

Artificial Intelligence ReviewVol. 58(5)
City University of Hong Kong (HK), South China University of Technology (CN)
Openalex Percentile: Top 35%
Gait Recognition and Analysis
0.67
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Psychological and physiological computing based on multi-dimensional foot information — Zhiyao Zhao, Siyuan Chen, et al. · Artificial Intelligence Review (2025) | TGRS Research Map | TGRS