The study of time domain features of EMG signals for detecting driver’s drowsiness

QR Code

The study of time domain features of EMG signals for detecting driver’s drowsiness

Fatigue or drowsiness is one of the major causes of traffic accidents in Malaysia. Physiological signals such as EMG is a useful input to detect drowsiness in drivers. The time domain features are easy to compute and well researched in the field of EMG hand motion detection. The focus of this paper...

Full description

Bibliographic Details
Main Authors:	Faradila, Naim, Mahfuzah, Mustafa, Norizam, Sulaiman, Noor Aisyah, Ab Rahman
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Science and Business Media Deutschland GmbH 2022
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	https://umpir.ump.edu.my/id/eprint/42244/

Similar Items

Dual-layer ranking feature selection method based on statistical formula for driver fatigue detection of EMG signals
by: Faradila, Naim, et al.
Published: (2022)

Enhancing driver safety : Real-time eye detection for drowsiness prevention driver assistance systems †
by: Zainah, Md Zain, et al.
Published: (2023)

Time and Frequency Domain Features of EMG Signal during Islamic Prayer (Salat)
by: Rabbi, M. F., et al.
Published: (2017)

Driver drowsiness detection using different classification algorithms
by: Nor Shahrudin, Nur Shahirah, et al.
Published: (2020)

Drowsiness detection for car assisted driver system using image processing analysis
by: Ani Syazana, Jasni
Published: (2010)

The classification of movement intention through machine learning models: the identification of significant time-domain EMG features
by: Ismail, Mohd Khairuddin, et al.
Published: (2021)

Driver's Face Tracking Based On Improved CAMShift for Drowsiness Detection
by: Jie, Ma, et al.
Published: (2013)

Driver Drowsiness Detection System
by: Ranjitha, M.M., et al.
Published: (2024)

Drowsiness detection for car assisted driver system using image processing analysis-interfacing with hardware
by: Huong, Nice Quan
Published: (2010)

A review of ECG data acquisition for driver drowsiness detection
by: Nor Shahrudin, Nur Shahirah, et al.
Published: (2020)

Enhancement of morlet mother wavelet in time–frequency domain in electroencephalogram (EEG) signals for driver fatigue classification
by: Rafiuddin, Abdubrani, et al.
Published: (2023)

Investigation of time-domain and frequency-domain based features to classify the EEG auditory evoked potentials (AEPs) responses
by: Islam, Md Nahidul, et al.
Published: (2022)

Relation Between EMG Signal Activation and Time Lags Using Feature Analysis During Dynamic Contraction
by: Ahamed, Nizam Uddin, et al.
Published: (2015)

4D : A real-time driver drowsiness detector using deep learning
by: Jahan, Israt, et al.
Published: (2023)

The Classification of Wink-Based EEG Signals: The Identification of Significant Time-Domain Features
by: Jothi Letchumy, Mahendra Kumar, et al.
Published: (2021)

Development of a driver drowsiness monitoring system using electrocardiogram
by: Nor Shahrudin, Nur Shahirah, et al.
Published: (2018)

The Classiﬁcation of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals
by: Farhan Anis, Azhar, et al.
Published: (2022)

The classification of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals
by: Farhan Anis, Azhar, et al.
Published: (2022)

Offline LabVIEW-Based EEG Signals Analysis to Detect Vehicle Driver Microsleep
by: Norizam, Sulaiman, et al.
Published: (2020)

Seat belt control system : drowsiness detector system
by: Nur Aisyah, Abdul Rahman
Published: (2022)

A hybrid environment control system combining EMG and SSVEP signal based on brain-computer interface technology
by: Rashid, Mamunur, et al.
Published: (2021)

A hybrid deep learning model for detecting driver fatigue using electroencephalogram signals
by: Rafiuddin, Abdubrani, et al.
Published: (2024)

An intelligent system for hearing disorder detection using auditory evoked potential (AEP) signals
by: Islam, Md Nahidul, et al.
Published: (2021)

Advanced noise removal techniques for the detection of EMG signal
by: Ahsan, Md. Rezwanul, et al.
Published: (2011)

Electromyograph (EMG) signal analysis to predict muscle fatigue during driving
by: Muhammad Amzar Syazani, Mohd Azli, et al.
Published: (2018)

EEG mechanism interaction to evaluate vehicle’s driver microsleep
by: Hazim, Yusof, et al.
Published: (2022)

Time domain analyis of acoustic emissions signal for milling process
by: Wan Shalamyza , Wan Husin
Published: (2012)

Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels
by: Rashid, Mamunur, et al.
Published: (2021)

The Classification of Hallucination: The Identification of Significant Time-Domain EEG Signals
by: Chin, Hau Lim, et al.
Published: (2022)

Noninversive EMG signals measurement and control of robotic system for rehabilitation
by: Sidek, Shahrul Na'im, et al.
Published: (2011)

Time domain feature extraction technique for earth’s electric field signal prior to the earthquake
by: Astuti , Winda, et al.
Published: (2013)

Age Related Differences in the Surface EMG Signals on Adolescent's Muscle during Contraction
by: Ahamed, Nizam Uddin, et al.
Published: (2016)

The classification of blinking: an evaluation of significant time-domain features
by: Kai, Gavin Lim Jiann, et al.
Published: (2022)

IOT – eye drowsiness detection system by using intel edison with gps navigation
by: Auni Syahirah, Abu Bakar, et al.
Published: (2019)

IoT – eye drowsiness detection system by using Intel Edison with GPS navigation
by: Rohana, Abdul Karim, et al.
Published: (2018)

The enhancement on stress levels based on physiological signal and self-stress assessment
by: Zarith Liyana, Zahari, et al.
Published: (2021)

Neural network classifier for hand motion detection from EMG signal
by: Ibrahimy, Muhammad Ibn, et al.
Published: (2011)

The classification of heart murmurs: The identification of significant time domain features
by: Cheng, Wai Kit, et al.
Published: (2020)

Feature extraction of GNSS signals based on signal processing techniques for land deformation detection
by: Norliana, Khamisan, et al.
Published: (2021)

Ensemble-based machine learning models for vehicle drivers’ fatigue state detection utilizing EEG signals
by: Hasan, Md Mahmudul, et al.
Published: (2024)