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