Affiliation:
1. Ashikaga University, Ashikaga, Tochigi, Japan
Abstract
This article describes a qualitative cognitive analysis and modeling tool (QCAM) for biological data collected using sensors such as a simple brain-wave sensor, while executing an actual task. However, these types of sensors are generally less accurate than devices designed for medical use. Sensors may be influenced by noise or personal differences between subjects. A qualitative approach is very effective for analyzing such data, because the authors can understand their essential features by focusing on qualitative changes, such as increasing, decreasing, and steady changes in the data, without quantifying it. Therefore, in addition to statistical analysis, QCAM provides qualitative analysis and modeling of data and allows us to verify the model by using qualitative reasoning. This article explains QCAM and describes experimental results obtained by using real driving data, a combination of movie data from a camera, acceleration data from a smart phone, and brain-wave data from a simple brain-wave sensor, that was obtained while a person drove a vehicle.
Subject
Artificial Intelligence,Human-Computer Interaction,Software
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Reproduction of mental states in driving using a visual filter;2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC);2022-12-08
2. Cognitive Driving Data Visualization and Driving Style Transfer;2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC);2021-10-29
3. IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive Computing (Plenary Panel Report-II);2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC);2021-10-29
4. Hybrid Approach for Enhancing Performance of Genomic Data for Stream Matching;International Journal of Cognitive Informatics and Natural Intelligence;2021-10
5. Experience-Based Approach for Cognitive Vehicle Research;International Journal of Software Science and Computational Intelligence;2020-10