Scholarlink

<p>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,&#xa0;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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Psychological and physiological computing based on multi-dimensional foot information

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月15日

查看全文
  • Shengyang Li,
  • Huilin Yao,
  • Ruotian Peng,
  • Yuanjun Ma,
  • Bowen Zhang,
  • Zhiyao Zhao,
  • Jincheng Zhang,
  • Siyuan Chen,
  • Shibin Wu,
  • Lin Shu

摘要

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.