LAPČÍKOVÁ, T. Electroencephalogram (EEG) and machine learning-based classification of various stages of mental stress [online]. Brno: Vysoké učení technické v Brně. Fakulta informačních technologií. 2024.
The thesis demonstrates outstanding proficiency in EEG data analysis and machine learning, significantly advancing our understanding of mental stress classification.
| Kritérium | Známka | Body | Slovní hodnocení |
|---|---|---|---|
| Informace k zadání | This is very difficult bachelor's thesis that used machine learning techniques and sophisticated EEG data analysis to categorize mental stress levels. I am satisfied with the outcomes of the thesis. Though, the student could have provided better technical details in the thesis, however the overall the aims of the thesis were achieved. | ||
| Práce s literaturou | The student was very active in obtaining the related study materials and they work hard to go through that. | ||
| Aktivita během řešení, konzultace, komunikace | Throughout the process, the student was very involved, met deadlines and had fruitful, frequent consultations. She always turned up on time, had a sound knowledge of the subject and took the initiative to incorporate criticism. Her precise and clear communication made for a very productive and collaborative supervision experience. | ||
| Aktivita při dokončování | This thesis was challenging as it involved not only the knowledge from the IT domain but also required knowledge from medical domain in terms of mental stress. I provided guidelines in terms of thesis writing, and the content which should be included in the final thesis. The student was able to complete the project and submit the thesis with one week extension in deadline. | ||
| Publikační činnost, ocenění | The work done can be published as a conference paper. |
The main weakness of the thesis is the shallow literature review. Overall, the work presented in the thesis meets the requirements for a Bachelor thesis. The student studied the problem at hand, proposed two different models for solving the problem, implemented them, and provided the results with enough quality metrics. Comparison and visualization of the results could have been better, but a shallow literature review limited these aspects of the thesis.
| Kritérium | Známka | Body | Slovní hodnocení |
|---|---|---|---|
| Náročnost zadání | It is a difficult project because it requires not only knowledge in computer science but also needs to incorporate psychological, psychiatric and neurological concepts of mental stress. The challenges in understanding the underlying brain mechanisms, and the corresponding features extraction as well as their interpretation with respect to mental stress, makes it a difficult project. | ||
| Rozsah splnění požadavků zadání | The main shortcoming of the thesis is literature review. Since the student did not study the relevant articles, it was not possible for the student to provide a comparison of the results of the proposed method. Overall, it is satisfactory because the student studied the problem, conducted a shallow literature review, proposed a model for the problem, implemented it, and provided the results with good number of quality metrics. | ||
| Rozsah technické zprávy | The thesis meets the minimum 40 standard pages requirement. Though it meets the requirement, the student could have easily expanded to more than 40 pages by including summary sections at the end of the chapters, detailed literature review, and details of human brain anatomy and physiology related with mental stress. | ||
| Prezentační úroveň technické zprávy | 80 | Overall, the structure of the thesis, in terms of chapters organization, is satisfactory. Chapter 1 provides an introduction, followed by literature review in chapter 2. Chapters 3 and 4 provide details of the proposed method and the corresponding implementation of the proposed method. Results are discussed in chapter 5 followed by conclusion in chapter 6. The major observation about the organization of the thesis is the missing flow between the sections in the chapters and this makes this thesis harder to read. Also, the chapters end suddenly. There should be a summary section at the end of the chapters. Also, some figures and tables are not referenced in the text. | |
| Formální úprava technické zprávy | 90 | In terms of language, the thesis is readable and use of English language in the thesis is satisfactory. There are minor typos and grammatical mistakes. However, they are few and in general the thesis is fine. | |
| Práce s literaturou | 75 | The student has done a poor literature review. This is the weakest part of the thesis. Chapter 2 deals with literature review. However, section 2.5 provides some details of the articles published for assessment of mental stress. The total length of section 2.5 is hardly 2 pages. It’s a poorly written chapter. | |
| Realizační výstup | 75 | The proposed methodology is satisfactory. The main shortcomings are the justifications for the various features selected as well as some of the pre-processing steps. In addition, the classifier section could have been written in a clear manner. The results are provided in detail. However, the clarity is not there in the results. Finally, comparison with other methods is not provided. | |
| Využitelnost výsledků | The thesis provides two approaches to the classification of mental stress, that is, traditional machine learning approach and deep learning approach. The student did not provide comparison with state-of-the-art in assessment of mental stress. Hence, it is not possible to assess the possibility of using the results in practice, though it is possible in general for such a thesis. |
eVSKP id 153457