SafeDriving: An Effective Abnormal Driving Behavior Detection System Based on EMG Signals

Fan, Yuanzhao; Gu, Fei; Wang, Jin; Wang, Jianping; Lu, Kejie; Niu, Jianwei

doi:10.1109/jiot.2021.3135512

Cited by 17 publications

(5 citation statements)

References 30 publications

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“…The researcher's hypothesis is that information has a significant impact on safe driving (Ahmed et al, 2018;Dehkordi et al, 2019;Yang et al, 2021). The more one knows about safe driving, the better one's behaviour will be (Sun et al, 2020;Haramak & Nishino 2019;Fan et al, 2021). On the other hand, the less one knows about driving, (Farooq et al, 2019) the worse one is at it.…”

Section: Discussionmentioning

confidence: 99%

Safety Driving Factors on Palm Oil Transporting Trucks

Sari,

Maryanti,

Haslinah

2022

Jupiter

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As many as 67% of accident victims in 2011 were between the ages of 22 and 50, according to WHO data. There were around 400 thousand victims under the age of 25, with a death toll of 1000 children and teenagers every day on average throughout this time period. PT. Tapian Nadenggan Langga Payung was the focus of this study, which sought to identify the elements that contributed to the safety of oil palm transport trucks. Analytical research with a cross-sectional approach was the research design employed. There are 35 people in total, all of whom work as oil palm fruit truck drivers. In this case, total sampling was employed as the method of sampling. For the knowledge collected from the chi-square test findings, the p value (0.270) was found to be greater than the 0.05 threshold for p value (0.000) based on age and safe driving. Physical Fatigue, on the other hand, has a p value (0.000) 0.05 in the chi-square test. No one's age has any bearing on how safe they are on the road when driving. Driving oil palm transport trucks for PT. Tapian Nadenggan Langga Payung was made more dangerous by lack of experience and exhaustion. Companies should ask their employees, especially truck drivers, to participate in safety driving instruction before they get behind the wheel of a truck.

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Section: Discussionmentioning

confidence: 99%

Safety Driving Factors on Palm Oil Transporting Trucks

Sari,

Maryanti,

Haslinah

2022

Jupiter

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“…Demonstrating the assessment of a driver’s capability to respond to TORs using EMG measurements adequately was exemplified by [ 93 ]. The SafeDriving system by Fan et al (2022) employs EMG sensors and deep learning to identify real-time abnormal driving behaviors [ 94 ]. The system utilizes a wearable EMG sensor on the driver’s forearm to gather data related to five predefined abnormal driving actions, each of which is subsequently labeled [ 94 ].…”

Section: Sensing Users and Tailoring The Experience Of The Autonomous...mentioning

confidence: 99%

Persona-PhysioSync AV: Personalized Interaction through Personality and Physiology Monitoring in Autonomous Vehicles

Giron,

Sela,

Barenboim

et al. 2024

Sensors

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The emergence of autonomous vehicles (AVs) marks a transformative leap in transportation technology. Central to the success of AVs is ensuring user safety, but this endeavor is accompanied by the challenge of establishing trust and acceptance of this novel technology. The traditional “one size fits all” approach to AVs may limit their broader societal, economic, and cultural impact. Here, we introduce the Persona-PhysioSync AV (PPS-AV). It adopts a comprehensive approach by combining personality traits with physiological and emotional indicators to personalize the AV experience to enhance trust and comfort. A significant aspect of the PPS-AV framework is its real-time monitoring of passenger engagement and comfort levels within AVs. It considers a passenger’s personality traits and their interaction with physiological and emotional responses. The framework can alert passengers when their engagement drops to critical levels or when they exhibit low situational awareness, ensuring they regain attentiveness promptly, especially during Take-Over Request (TOR) events. This approach fosters a heightened sense of Human–Vehicle Interaction (HVI), thereby building trust in AV technology. While the PPS-AV framework currently provides a foundational level of state diagnosis, future developments are expected to include interaction protocols that utilize interfaces like haptic alerts, visual cues, and auditory signals. In summary, the PPS-AV framework is a pivotal tool for the future of autonomous transportation. By prioritizing safety, comfort, and trust, it aims to make AVs not just a mode of transport but a personalized and trusted experience for passengers, accelerating the adoption and societal integration of autonomous vehicles.

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“…Most of the available research is based on ofine analysis that excludes noisy data. Many recent articles have employed physiological data to monitor epileptic seizures [194], dynamic changes in the brain [195], vigilance [196], sleep quality [197], fatigue [198], and abnormal driving [199]. Tese methods have primarily used either the brain or muscle signals.…”

Section: Limitations Challenges and Suggestions For Future Researchmentioning

confidence: 99%

A Review on the Applications of Time‐Frequency Methods in ECG Analysis

Pradhan

Neelappu

Jayaraman

et al. 2023

Journal of Healthcare Engineering

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The joint time-frequency analysis method represents a signal in both time and frequency. Thus, it provides more information compared to other one-dimensional methods. Several researchers recently used time-frequency methods such as the wavelet transform, short-time Fourier transform, empirical mode decomposition and reported impressive results in various electrophysiological studies. The current review provides comprehensive knowledge about different time-frequency methods and their applications in various ECG-based analyses. Typical applications include ECG signal denoising, arrhythmia detection, sleep apnea detection, biometric identification, emotion detection, and driver drowsiness detection. The paper also discusses the limitations of these methods. The review will form a reference for future researchers willing to conduct research in the same field.

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SafeDriving: An Effective Abnormal Driving Behavior Detection System Based on EMG Signals

Cited by 17 publications

References 30 publications

Safety Driving Factors on Palm Oil Transporting Trucks

Safety Driving Factors on Palm Oil Transporting Trucks

Persona-PhysioSync AV: Personalized Interaction through Personality and Physiology Monitoring in Autonomous Vehicles

A Review on the Applications of Time‐Frequency Methods in ECG Analysis

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