基于MEMS磁强计和神经网络的驾驶员头部姿态监测与疲劳分析

Hobeom Han, Hyeongkyu Jang, S. Yoon
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引用次数: 8

摘要

提出了一种用于远距离驾驶员头部不平衡姿态监测的便携式传感器系统。头部姿势监测使驾驶员疲劳分析(避免潜在的车祸),防止慢性疲劳和可能的颈部相关疾病。一个三轴MEMS磁强计和微型磁体附着在用户的脖子上。用户进行由五种常见驾驶动作和一种不方便姿势组成的驾驶场景。采集到的磁强计数据通过神经网络算法进行处理。部分数据用于建立学习模型,其余数据用于校准模型。实验结果令人满意,模型精度高达93.0%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Driver Head Posture Monitoring using MEMS Magnetometer and Neural Network for Long-distance Driving Fatigue Analysis
This paper presents a portable sensor system to monitor unbalanced head postures of long-distance drivers. The head posture monitoring enables driver fatigue analysis (avoiding potential car accidents) and prevents chronic fatigue and possible neck related diseases. A three-axis MEMS magnetometer and miniature magnet are attached on a user’s neck. The user conducts driving scenarios consisting of five common driving actives and one inconvenient posture. Collected magnetometer data are proceeded by neural network algorithms. Part of the data are used to develop a learned model and rest of them are used to calibrate the model. Experiment results are very promising and exhibit superior model accuracy as high as 93.0%.
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