Suppr超能文献

利用可穿戴传感器识别和预测防御性悲观人格特质

Leveraging Wearable Sensors for the Identification and Prediction of Defensive Pessimism Personality Traits.

作者信息

Zhou You, Li Dongfen, Deng Bowen, Liang Weiqian

机构信息

College of Computer and Network Security, Chengdu University of Technology, 1#, Dongsanlu, Erxianqiao, Chengdu 610059, China.

出版信息

Micromachines (Basel). 2025 Aug 2;16(8):906. doi: 10.3390/mi16080906.

Abstract

Defensive pessimism, an important emotion regulation and motivation strategy, has increasingly attracted scholarly attention in psychology. Recently, sensor-based methods have begun to supplement or replace traditional questionnaire surveys in personality research. However, current approaches for collecting vital signs data face several challenges, including limited monitoring durations, significant data deviations, and susceptibility to external interference. This paper proposes a novel approach using a NiCr/NiSi alloy film temperature sensor, which has a K-type structure and flexible piezoelectric pressure sensor to identify and predict defensive pessimism personality traits. Experimental results indicate that the Seebeck coefficients for K-, T-, and E-type thermocouples are approximately 41 μV/°C, 39 μV/°C, and 57 μV/°C, respectively, which align closely with national standards and exhibit good consistency across multiple experimental groups. Moreover, radial artery frequency experiments demonstrate a strong linear relationship between pulse rate and the intensity of external stimuli, where stronger stimuli correspond to faster pulse rates. Simulation experiments further reveal a high correlation between radial artery pulse frequency and skin temperature, and a regression model based on the physiological sensor data shows a good fit ( < 0.05). These findings verify the feasibility of using temperature and flexible piezoelectric pressure sensors to identify and predict defensive pessimism personality characteristics.

摘要

防御性悲观是一种重要的情绪调节和动机策略,在心理学领域越来越受到学术关注。最近,基于传感器的方法已开始在人格研究中补充或取代传统的问卷调查。然而,目前收集生命体征数据的方法面临着几个挑战,包括监测持续时间有限、数据偏差大以及易受外部干扰。本文提出了一种使用具有K型结构的NiCr/NiSi合金薄膜温度传感器和柔性压电压力传感器来识别和预测防御性悲情人格特质的新方法。实验结果表明,K型、T型和E型热电偶的塞贝克系数分别约为41 μV/°C、39 μV/°C和57 μV/°C,与国家标准密切吻合,并且在多个实验组中表现出良好的一致性。此外,桡动脉频率实验表明脉搏率与外部刺激强度之间存在很强的线性关系,刺激越强,脉搏率越快。模拟实验进一步揭示了桡动脉脉搏频率与皮肤温度之间的高度相关性,并且基于生理传感器数据的回归模型显示出良好的拟合度(<0.05)。这些发现验证了使用温度和柔性压电压力传感器来识别和预测防御性悲情人格特征的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/399e/12388590/79faf2a38afb/micromachines-16-00906-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验