Suppr超能文献

MsWH:一种用于捕获和分析生理情绪信号的多感官硬件平台。

MsWH: A Multi-Sensory Hardware Platform for Capturing and Analyzing Physiological Emotional Signals.

机构信息

Department of Electronics, Escuela Universitaria Politécnica de La Almunia, La Almunia de Doña Godina, 50100 Zaragoza, Spain.

Department of Electronics Engineering and Communications, Escuela de Ingeniería y Arquitectura, I3A, Universidad de Zaragoza, 50018 Zaragoza, Spain.

出版信息

Sensors (Basel). 2022 Aug 2;22(15):5775. doi: 10.3390/s22155775.

Abstract

This paper presents a new physiological signal acquisition multi-sensory platform for emotion detection: Multi-sensor Wearable Headband (MsWH). The system is capable of recording and analyzing five different physiological signals: skin temperature, blood oxygen saturation, heart rate (and its variation), movement/position of the user (more specifically of his/her head) and electrodermal activity/bioimpedance. The measurement system is complemented by a porthole camera positioned in such a way that the viewing area remains constant. Thus, the user's face will remain centered regardless of its position and movement, increasing the accuracy of facial expression recognition algorithms. This work specifies the technical characteristics of the developed device, paying special attention to both the hardware used (sensors, conditioning, microprocessors, connections) and the software, which is optimized for accurate and massive data acquisition. Although the information can be partially processed inside the device itself, the system is capable of sending information via Wi-Fi, with a very high data transfer rate, in case external processing is required. The most important features of the developed platform have been compared with those of a proven wearable device, namely the Empatica E4 wristband, in those measurements in which this is possible.

摘要

本文提出了一种用于情绪检测的新的生理信号采集多传感器平台

多传感器可穿戴头带(MsWH)。该系统能够记录和分析五种不同的生理信号:皮肤温度、血氧饱和度、心率(及其变化)、用户的运动/位置(更具体地说是他/她的头部)和皮肤电活动/生物阻抗。测量系统配有一个舷窗摄像头,其位置设置为使观察区域保持不变。因此,无论用户的位置和运动如何,他/她的面部将始终保持在中心位置,从而提高面部表情识别算法的准确性。这项工作详细说明了所开发设备的技术特点,特别关注所使用的硬件(传感器、调理、微处理器、连接)和软件,该软件经过优化,可实现准确和大量的数据采集。尽管设备本身可以部分处理信息,但该系统能够通过 Wi-Fi 以非常高的数据传输速率发送信息,如果需要外部处理的话。已将所开发平台的最重要功能与经过验证的可穿戴设备(即 Empatica E4 腕带)进行了比较,在可行的情况下进行了这些测量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/651b/9371105/62b3a9b0eb39/sensors-22-05775-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