Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions

This study proposes a capacitance-based fatigue driving recognition method. The proposed method encompasses four principal phases: signal acquisition, pre-processing, blink detection, and fatigue driving recognition. A measurement circuit based on the FDC2214 is designed for the purpose of signal ac...

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Main Authors: Cheng Zeng, Haipeng Wang
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/24/23/7633
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author Cheng Zeng
Haipeng Wang
author_facet Cheng Zeng
Haipeng Wang
author_sort Cheng Zeng
collection DOAJ
description This study proposes a capacitance-based fatigue driving recognition method. The proposed method encompasses four principal phases: signal acquisition, pre-processing, blink detection, and fatigue driving recognition. A measurement circuit based on the FDC2214 is designed for the purpose of signal acquisition. The acquired signal is initially subjected to pre-processing, whereby noise waves are filtered out. Subsequently, the blink detection algorithm is employed to recognize the characteristics of human blinks. The characteristics of human blink include eye closing time, eye opening time, and idle time. Lastly, the BP neural network is employed to calculate the fatigue driving scale in the fatigue driving recognition stage. Experiments under various working and light conditions are conducted to verify the effectiveness of the proposed method. The results show that high fatigue driving recognition accuracy (92%) can be obtained by the proposed method under various light conditions.
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institution Kabale University
issn 1424-8220
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publishDate 2024-11-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-f844da99a05f4e7d9f814a07d2cf77b82024-12-13T16:32:14ZengMDPI AGSensors1424-82202024-11-012423763310.3390/s24237633Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light ConditionsCheng Zeng0Haipeng Wang1School of Advanced Manufacturing, Nanchang University, Nanchang 330031, ChinaSchool of Intelligent Manufacturing, Jiangsu College of Engineering and Technology, Nantong 226006, ChinaThis study proposes a capacitance-based fatigue driving recognition method. The proposed method encompasses four principal phases: signal acquisition, pre-processing, blink detection, and fatigue driving recognition. A measurement circuit based on the FDC2214 is designed for the purpose of signal acquisition. The acquired signal is initially subjected to pre-processing, whereby noise waves are filtered out. Subsequently, the blink detection algorithm is employed to recognize the characteristics of human blinks. The characteristics of human blink include eye closing time, eye opening time, and idle time. Lastly, the BP neural network is employed to calculate the fatigue driving scale in the fatigue driving recognition stage. Experiments under various working and light conditions are conducted to verify the effectiveness of the proposed method. The results show that high fatigue driving recognition accuracy (92%) can be obtained by the proposed method under various light conditions.https://www.mdpi.com/1424-8220/24/23/7633capacitanceblink detectionfatigue driving recognitionneural network
spellingShingle Cheng Zeng
Haipeng Wang
Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
Sensors
capacitance
blink detection
fatigue driving recognition
neural network
title Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
title_full Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
title_fullStr Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
title_full_unstemmed Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
title_short Capacitance-Based Untethered Fatigue Driving Recognition Under Various Light Conditions
title_sort capacitance based untethered fatigue driving recognition under various light conditions
topic capacitance
blink detection
fatigue driving recognition
neural network
url https://www.mdpi.com/1424-8220/24/23/7633
work_keys_str_mv AT chengzeng capacitancebaseduntetheredfatiguedrivingrecognitionundervariouslightconditions
AT haipengwang capacitancebaseduntetheredfatiguedrivingrecognitionundervariouslightconditions