Drowsiness Detection Using EEG, Heart Rate Variability, and Eye Movements
Outline
INTRODUCTION
- This segment delves into giving a sufficient background information of the topic study, purpose of study and objectives of the study.
- Drowsiness is a systemic aspect that comes about as a characteristic of reduced or low metabolic activities of the body [1].
- Ideally, experts postulate that drowsiness is an almost involuntary outcome of the body caused by a combination of neurological, metabolic and systemic factors.
- Drowsiness can result at any point in time depending on the articulation of neurological, metabolic and systemic processes. According to well-documented studies, drowsiness characterizes as mild sleep or a state of in and out of sleep [2].
- The focus of the study will be to appraise Drowsiness Detection Using EEG, Heart Rate Variability, and Eye Movements
Background Information
- This segment will cover a concise and precise preamble of facts and information related to the research topic
- A justification of the research study will be provided and supported using key facts such as statistics, retrospective and perspective studies and evidence-based research
Problem Statement
- A brief statement of the research problem or focus will be provided to elaborate the objectives of the study
- Set objectives are provided to mitigate or bridge in the problem gap identified.
BODY
- This segment will include the literature review, analysis from studies and research and relevant discussions
- It is prudent to appreciate the fact that several demerits associate with drowsiness.
- Notably, the occurrence of drowsiness during life activities such as driving, working on machinery or other duties that require undivided attention form the premises of accidents and casualties.
Literature Review
- The provisions of this segment primarily review other research and scholarly studies done in line with the research focus (Drowsiness detection….)
- The scholarly resources used align to the objectives of the research and problem statement.
- Several scholars, explicitly confirm that drowsiness and fatigue are mainly the reasons associated to accidents since they collectively reduce the attention and reaction capability of a driver [2].
- Focus on drowsiness detection and fatigue among drivers is a viable research area. Evidence-based studies show that EEG, Heart rate variability and eye movements are correlative factors linked to drowsiness and will be key parameters of the study [3].
- As an intervention strategy, it is relevant that the drowsiness detection study and research approaches bear regulatory and ethical considerations. Notably, beneficence and policy adherence will form the basis of regulatory and ethical considerations in dealing with drowsiness detection among drivers and other relevant subjects.
Results
- This section forms the information hub of the research done through data mining from studies and research work
- The results are presented using percentiles, tables and graphs.
Discussion
- The provisions of this section delve into analyzing and explaining the results presented in the preceding segment.
- The segment also delves into discussing about ethical considerations associated to the research topic
- Relevant take away, recommendations and call to action are discussed in this section with regards to the research topic
CONCLUSION
- The paper will conclude with a preamble and a take away from the discussions and findings made
- It is relevant to appreciate that understanding and enumerating drowsiness detection will provide potent assistance not just to drivers but also other personnel who conduct attention-guided duties such as surgical doctors, chemical engineers, and advanced care nurses among others [2].
- It is sensible to acknowledge that this drowsiness detection approach bears health costs. The health costs include EEG, Cardio analysis and optic studies, all of which are cost bound.
- However, it is imperative that the intervention be conducted as it bears far more benefits than costs.
References
[1]D. Malimath and K. Jain, “Driver Drowsiness Detection System”, Bonfring International Journal of Software Engineering and Soft Computing, vol. 6, no., pp. 58-63, 2016.
[2] He, “Drowsiness Detection and Management”, Journal of Ergonomics, vol. 03, no. 02, 2013.
[3]L. Joseph, “Arduino based real time driver drowsiness detection and mobile alert system using bluetooth”, International Journal Of Engineering And Computer Science, 2016.
