Wearable sensor-based evaluation of psychosocial stress in patients with metabolic syndrome

作者：

Highlights：

• A wearable device powered with an e-health solution has been developed to assess anxiety and stress levels.

• A multivariate methodology for the modeling of stress via proposed neural-network-based affective state detection algorithm.

• With the unique clinical dataset, prediction accuracy of 92% for MES patients’ stress level.

摘要

•A wearable device powered with an e-health solution has been developed to assess anxiety and stress levels.•A multivariate methodology for the modeling of stress via proposed neural-network-based affective state detection algorithm.•With the unique clinical dataset, prediction accuracy of 92% for MES patients’ stress level.

论文关键词：Wearable System,e-Health,HRV,Affective Computing,Neural Networks,Metabolic Syndrome

论文评审过程：Received 4 November 2019, Revised 14 January 2020, Accepted 17 February 2020, Available online 20 February 2020, Version of Record 26 February 2020.

论文官网地址：https://doi.org/10.1016/j.artmed.2020.101824