SPIDERS: Low-Cost Wireless Glasses for Continuous In-Situ Bio-Signal Acquisition and Emotion Recognition
SPIDERS: Low-Cost Wireless Glasses for Continuous In-Situ Bio-Signal Acquisition and Emotion Recognition
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DOI：
10.1109/iotdi49375.2020.00011
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发表时间：
2020-04
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通讯作者：
Jingping Nie;Yigong Hu;Yuanyuting Wang;S. Xia;Xiaofan Jiang
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作者：
Jingping Nie;Yigong Hu;Yuanyuting Wang;S. Xia;Xiaofan Jiang
我们提出了一种用于处理情绪识别和传感的原位生物信号数据的系统（SPIDERS）-一种低成本的、无线的、基于眼镜的平台，用于连续地原位监测用户的面部表情（明显的情绪）和真实的情绪。我们提出了算法，以提供四个核心功能（眼睛形状和眉毛运动，瞳孔测量，眼肌肌肉运动，头部运动），使用从三个非接触式传感器（红外摄像头，接近传感器，IMU）获取的生物信号。SPIDERS根据上述四种生物信号区分不同类别的明显和真实的情绪状态。我们的原型先进的功能，包括面部表情检测和真实的情感分类与地标和光流的面部表情检测器，利用用户的眉毛和眼睛形状的变化，以实现高达83.87%的准确性，以及基于瞳孔测量的真实的情感分类器具有更高的准确性比其他低成本的可穿戴平台，使用传感器需要皮肤接触。SPIDERS的组装成本不到20美元，在充电前可以连续运行长达9小时。我们证明，蜘蛛是一个真正的无线和便携式平台，有能力影响广泛的应用程序，用户的情绪状态的知识是至关重要的。
We present a System for Processing In-situ Bio-signal Data for Emotion Recognition and Sensing (SPIDERS)– a low-cost, wireless, glasses-based platform for continuous in-situ monitoring of user's facial expressions (apparent emotions) and real emotions. We present algorithms to provide four core functions (eye shape and eyebrow movements, pupillometry, zygomaticus muscle movements, and head movements), using the bio-signals acquired from three non-contact sensors (IR camera, proximity sensor, IMU). SPIDERS distinguishes between different classes of apparent and real emotion states based on the aforementioned four bio-signals. We prototype advanced functionalities including facial expression detection and real emotion classification with a landmarks and optical flow based facial expression detector that leverages changes in a user's eyebrows and eye shapes to achieve up to 83.87% accuracy, as well as a pupillometry-based real emotion classifier with higher accuracy than other low-cost wearable platforms that use sensors requiring skin contact. SPIDERS costs less than $20 to assemble and can continuously run for up to 9 hours before recharging. We demonstrate that SPIDERS is a truly wireless and portable platform that has the capability to impact a wide range of applications, where knowledge of the user's emotional state is critical.