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7COM1084 Specialism Research Report

In order to conduct independent research in computer science you must fully understand the research area. You must have a grasp of the current open questions in this area, as well as any common techniques used to solve problems.

In this assignment you must provide an overview of your MSc Research specialism (AI / Networking / Cyber Security / Software Engineering / Data Science). Students without a specialism may choose any one of these specialisms.

You must discuss the research question presented within the relevant specialist lecture for this specialism, propose some research approaches to investigate this question and identify further work you might undertake which builds on this. You must also explore your personal strengths in this area.





Assessing a selected specialization area in research, it has been discovered that the specific practice of real-time hand gesture trajectory prediction is a beneficial way of determining the degree of dementia occurring in individuals who are deaf (Dove and Astel, 2017). Essentially, this study speciality appears to be heavily focused on magnetic resonance imaging (MRI) and computed tomography (CT). The procedures of CT and MRI are intertwined with the principle of automation and machine learning. Resultantly, it has been discovered that this specific research topic is closely related to the concepts dealing with customer science, and thus someone with no specific information can subscribe to it. The particular chosen for the study is concerned with the possibility of obtaining the hand movement patterns of real-time through assessment of a deaf individual’s facial muscles’ visual cues, so that trend distinction with both trajectory motion and facial data becomes efficiently comprehensible.

Open Research Question

  • Is the signing space envelop correlated with mild cognitive impairment and, in particular early stages of dementia?

This research question can help to answer certain significant issues of real-world related to dementia as among ageing singers who use the British Sign Language (BSL). In clinical terms, Mild cognitive impairment refers to a decline that doesn’t fully meet the stated disease requirements. As a result, determining the relationship between signing space and cognitive impairment in the ageing population of BSL signers is a scientifically important open research question. Through this research interest in the use of advanced computers and techniques of data science to check for the early stages of dementia in elderly BSL signers. BSL signers usually practice sign languages, which are human natural cultures that are useful in individuals who are deaf. This technique is related to the movement of hand, body gestures, and facial expressions. As a result, these research questions successfully respond to the success of sign language during dementia vetting.

The real-time progression for checking dementia problems involves numerous advanced data science technologies such as 2D videos, CT, MRI, and ICT (Liang et al. 2019). The research problem identifies various algorithms from the area of data science that should deliver real-world outcomes afterward viewing dementia patients with cognitive impairment. According to Pranav et al. (2020), patients suffering from dementia interact less in any exercise and physical activity that can lead to a decrease in functional ability. The involvement of advanced technological technical algorithms can be beneficial for checking the progression of dementia. This question was taken to determine how skilled staff can successfully use those technologies during dementia diagnosis. The study will go on to explain the benefits of using technology in checking for dementia.

Research problem

The research problem of the given paper can be summarised as – enhancing the checking of dementia in ageing BSL signers with improper tracking of hand movement

Literature Review

Gayathrti et al., (2018) discuss that the term dementia refers to a physical condition that makes it difficult for the patient to recollect anything and impairs wise choice abilities. Other downsides of dementia include neurobiological deterioration due to the occurrence of clinical depression and anxiety. The main cause behind dementia is Alzheimer’s disease and the accumulation of metaflammasome elements, which are responsible for nearly 33% of all dementia cases. It can be observed that the modern technology ADL can be used to check for dementia. On the contrary, Wahlforss and Jonasson (2020), have further clarified that the disease is the aftereffect of neural misfortune in the mind, which can cause cerebrum degeneration before the development of slightly new medical signs. Therefore, it very well may be inferred that the underlying checking assumes a critical part in the conclusion of the condition dementia yet in addition permits time for quite a long-time impacted individuals to recuperate. Hand direction and open posture library models, for instance, can be helpful in the early handling of issues related to dementia. About 60 – 65 percent of absolute dementia patients will encounter social aggravations at some specific time.

Livingston et al., (2019) has discussed that dementia is a significant expansive term that is oftentimes for different neurodegenerative disorders that fundamentally influence memory working, conduct, and language. Khaertdinov et al., in the year 2021 clarified that dementia is a recognized medical problem, particularly in different industrialized nations, it can be dealt with efficiently utilizing present-day computational data frameworks. This amount of literature is adequate to elicit data concerning the negative sides of dementia just as some restorative techniques are dependent on innovation. Yousaf et al., (2019) propose, that all things considered, there is deficient data about the essential arrangement of utilizing progressed information science advancement for the checking of dementia. The study presumes that dementia patients end up receiving only GRADIOR health care, which doesn’t enhance the life quality. As a result, modern technology is required to maintain the hand progression and prototype of the accessible pose library. Nevertheless, the open problem here is the lack of skilled personnel who can handle such modern technology in preserving hand trajectory and accessible face library prototype for dementia check. The existing research work does not focus on the lack of technology and the skilled personnel required to handle the screening of dementia using ICT.


Research approach

Analyzing the available research technique, it is discovered that this particular paper has efficiently concentrated on secondary qualitative research as part of the study. In the research study, BSL Cognitive Check norming data is being utilized as a part of interviews done with 250 signatories ranging in age from 50 to 90. At first, recorded videos of BSL signers are being used to successfully assess the degree of dementia between patient populations. According to Williams et al., (2019), qualitative research focuses due to the ability to sample particular groups and also important views to gather significant data.

Due to the potential of collecting more dependable research samples, the research approach chosen is thought to be highly efficient. This technique assisted the researcher to concentrate on opinions, and facts simultaneously. The RGB video stream is used in the research to ensure that the selected technique is efficient for the course of the study. Another view that is noticeable as information on conduct, the respondents’ mindset is simple to understand as a result of the preferred sampling of the dataset. Nevertheless, the downside of this technique is that the individuals with dementia frequently could provide dependable descriptive answers, which can taint the final result of the study (Sarker et al., 2018). As a result of the data analysis truthfulness issues can be seen in this research. Besides, another obvious issue is the inordinate time that is obligatory for the accomplishment of the general study.

The use of the mixed technique is that one technique that this paper could have taken to make this study more efficient (Toyon, 2021). This may have aided in time management for the research. The open questions can be the perfect complement to the interview, which a few closed-ended questionnaires could be used as a part of ensuring that this study is completed in as little time as possible. Also, this would have ensured that the overall correctness of the research was maintained. Nevertheless, the extracting features model could be used as part of implementing the experiential design. Along with the Automated checking Toolkit, the end outcome could have been substantiated. The assessment study reveals that the OpenPose software for extracting trajectories was used. Non-MRI categorization, on the other hand, should be prioritized as a part of the study technique.

Personal Investment

Dementia is a very difficult disease to deal with. The diseases not only upset the lives of the patients but also that of the caregivers. The personal motivation for the research is to develop ways to introduce data science for neurological impairments such as Dementia. The facet of sign language and its relationship to the concern of dementia, as well as its connectedness with the use of machine language in this research, are explained clearly here. At first, having a thorough understanding of computer science has proven to be one of the most valuable resources that have assisted me in working on this specific topic. Other than that, one among the most considerable variables in this research is my understanding of the quantitative and qualitative research processes, which has allowed me to carefully consider the full procedure regularly.

Reference List

Dove, E. and Astell, A.J., 2017. The use of motion-based technology for people living with dementia or mild cognitive impairment: a literature review. Journal of medical Internet research, 19(1), p.e3.

Gayathri, K.S., Elias, S. and Easwarakumar, K.S., 2018. Assistive dementia care system through smart home. In Proceedings of First International Conference on Smart System, Innovations and Computing (pp. 455-467). Springer, Singapore.

Khaertdinov, B., Semerci, Y.C. and Asteriadis, S., 2021, June. Dementia Wandering Recognition using Classical Machine Learning and Deep Learning Techniques with Skeletal Trajectories. In The 14th PErvasive Technologies Related to Assistive Environments Conference (pp. 446-452).

Livingston, G., Huntley, J., Sommerlad, A., Ames, D., Ballard, C., Banerjee, S., Brayne, C., Burns, A., Cohen-Mansfield, J., Cooper, C., and Costafreda, S.G., 2020. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. The Lancet, 396(10248), pp.413-446.

Pranav, S., Kumar, M., and Srinivasan, R., 2020. DEMENTIA DETECTION FOR ELDERLY PEOPLE USING ROBOTIC PROCESS AUTOMATION. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), 7(1), pp.502-506.

Sarker, K., Masoud, M., Belkasim, S. and Ji, S., 2018, December. Towards robust human activity recognition from RGB video stream with limited labelled data. In 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 145-151). IEEE.

Toyon, M.A.S., 2021. Explanatory sequential design of mixed techniques research: Phases and challenges. International Journal of Research in Business and Social Science (2147-4478)10(5), pp.253-260.

Wahlforss, A. and Jonasson, A.A., 2020. Early dementia diagnosis from a spoken language using a transformer approach. Alzheimer’s & Dementia, 16, p.e043445.

Williams, V., Boylan, A.M. and Nunan, D., 2019. Qualitative research as evidence: expanding the paradigm for evidence-based healthcare. BMJ evidence-based medicine, 24(5), pp.168-169.

Yousaf, K., Mehmood, Z., Awan, I.A., Saba, T., Alharbey, R., Qadah, T. and Alrige, M.A., 2019. A comprehensive study of mobile-health based assistive technology for the healthcare of dementia and Alzheimer’s disease (AD). Health Care Management Science, pp.1-23.



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