Drowsiness detection system based on eye-closure using a low-cost EMG and ESP8266

Artanto, Dian; Sulistyanto, Muhammad Prayadi; Pranowo, Ignatius Deradjad; Pramesta, Ervan Erry

doi:10.1109/icitisee.2017.8285502

Cited by 32 publications

(12 citation statements)

References 7 publications

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“…Surface EMG is a helpful way of identifying discomfort in fatigued and weak muscles and targeting rehabilitation for skeletomuscular problems specially in professional or long-distance drivers (Balasubramanian and Adalarasu, 2007 ). A recent study (Artanto et al, 2017 ) has also used a low-cost EMG system to detect drowsiness. An EMG sensor attached to muscles around eyelid region captured the duration of eyelid closure as an indicator of drowsiness (Artanto et al, 2017 ).…”

Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

“…A recent study (Artanto et al, 2017 ) has also used a low-cost EMG system to detect drowsiness. An EMG sensor attached to muscles around eyelid region captured the duration of eyelid closure as an indicator of drowsiness (Artanto et al, 2017 ). Another recent study has proposed a system that can detect real-time changes in EMG (Mazzetta et al, 2018 ).…”

Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

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A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Lohani

Payne

Strayer

2019

Front. Hum. Neurosci.

241

181

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As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures' unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists' cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems.

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Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

Section: Psychophysiological Measures To Assess Cognitive Statesmentioning

confidence: 99%

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Lohani

Payne

Strayer

2019

Front. Hum. Neurosci.

241

181

View full text Add to dashboard Cite

show abstract

“…Figure A1 (Appendix A) shows the whole circuit. This design was modified and carried out according to a previous study [26].…”

Section: Of 11mentioning

confidence: 99%

Wireless, Skin-Mountable EMG Sensor for Human–Machine Interface Application

et al. 2019

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The development of advanced technologies for wireless data collection and the analysis of quantitative data, with application to a human-machine interface (HMI), is of growing interest. In particular, various wearable devices related to HMIs are being developed. These devices require a customization process that considers the physical characteristics of each individual, such as mounting positions of electrodes, muscle masses, and so forth. Here, the authors report device and calculation concepts for flexible platforms that can measure electrical signals changed through electromyography (EMG). This soft, flexible, and lightweight EMG sensor can be attached to curved surfaces such as the forearm, biceps, back, legs, etc., and optimized biosignals can be obtained continuously through post-processing. In addition to the measurement of EMG signals, the application of the HMI has stable performance and high accuracy of more than 95%, as confirmed by 50 trials per case. The result of this study shows the possibility of application to various fields such as entertainment, the military, robotics, and healthcare in the future.

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“…It is designed for mobile devices, wearable electronic products and Internet of things, and has advanced low power management technology [10]. The working temperature range of ESP8266EX is large, and it can maintain stable performance, and can adapt to various operating environments [11]. In addition, ESP8266EX can connect sensors and other devices through GPIO.…”

Section: Hardware Aspectmentioning

confidence: 99%

Design of a Simplified Wireless Sensor Network Node Based on MQTT Protocol

Shao¹,

Huang²,

Wu³

et al. 2018

dtcse

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MQTT protocol is a publish/subscribe message protocol based on TCP/IP protocol. It has the characteristics of low power consumption, scalability, openness and simplicity. HTTP protocol is an open and low-cost request/reply message protocol based on TCP/IP protocol. It is the main protocol of Internet communication, but it is not suitable for the environment of computing, processing and bandwidth limited. In this paper, a simplified wireless sensor network node was designed based on MQTT protocol. The node was designed to use the Arduino development environment and use the WiFi for networking. It has the characteristics of simple structure, low power consumption and so on. The design can be widely used in smart home, environmental monitoring and medical applications, and is the main contents of the Internet of things (IoT).

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Drowsiness detection system based on eye-closure using a low-cost EMG and ESP8266

Cited by 32 publications

References 7 publications

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Wireless, Skin-Mountable EMG Sensor for Human–Machine Interface Application

Design of a Simplified Wireless Sensor Network Node Based on MQTT Protocol

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