Displaying all 2 publications

Abstract:
Sort:
  1. Fulltext Classification of Visual and Non-visual Learners Using Electroencephalographic Alpha and Gamma Activities
    Jawed S, Amin HU, Malik AS, Faye I
    Front Behav Neurosci, 2019;13:86.
    PMID: 31133829 DOI: 10.3389/fnbeh.2019.00086
    This study analyzes the learning styles of subjects based on their electroencephalo-graphy (EEG) signals. The goal is to identify how the EEG features of a visual learner differ from those of a non-visual learner. The idea is to measure the students' EEGs during the resting states (eyes open and eyes closed conditions) and when performing learning tasks. For this purpose, 34 healthy subjects are recruited. The subjects have no background knowledge of the animated learning content. The subjects are shown the animated learning content in a video format. The experiment consists of two sessions and each session comprises two parts: (1) Learning task: the subjects are shown the animated learning content for an 8-10 min duration. (2) Memory retrieval task The EEG signals are measured during the leaning task and memory retrieval task in two sessions. The retention time for the first session was 30 min, and 2 months for the second session. The analysis is performed for the EEG measured during the memory retrieval tasks. The study characterizes and differentiates the visual learners from the non-visual learners considering the extracted EEG features, such as the power spectral density (PSD), power spectral entropy (PSE), and discrete wavelet transform (DWT). The PSD and DWT features are analyzed. The EEG PSD and DWT features are computed for the recorded EEG in the alpha and gamma frequency bands over 128 scalp sites. The alpha and gamma frequency band for frontal, occipital, and parietal regions are analyzed as these regions are activated during learning. The extracted PSD and DWT features are then reduced to 8 and 15 optimum features using principal component analysis (PCA). The optimum features are then used as an input to the k-nearest neighbor (k-NN) classifier using the Mahalanobis distance metric, with 10-fold cross validation and support vector machine (SVM) classifier using linear kernel, with 10-fold cross validation. The classification results showed 97% and 94% accuracies rate for the first session and 96% and 93% accuracies for the second session in the alpha and gamma bands for the visual learners and non-visual learners, respectively, for k-NN classifier for PSD features and 68% and 100% accuracies rate for first session and 100% accuracies rate for second session for DWT features using k-NN classifier for the second session in the alpha and gamma band. For PSD features 97% and 96% accuracies rate for the first session, 100% and 95% accuracies rate for second session using SVM classifier and 79% and 82% accuracy for first session and 56% and 74% accuracy for second session for DWT features using SVM classifier. The results showed that the PSDs in the alpha and gamma bands represent distinct and stable EEG signatures for visual learners and non-visual learners during the retrieval of the learned contents.
  2. Fulltext The metabolic associated fatty liver disease responses of lifestyle changes using diet and exercise
    Altaf B, Mohamed M, Jawed S, Ghazali WSW
    Pak J Med Sci, 2023;39(6):1875-1882.
    PMID: 37936729 DOI: 10.12669/pjms.39.6.7990
    OBJECTIVE: This review is aimed to study MAFLD responses of lifestyle modifications using Diet and Exercise.

    METHODS: The sources for this MAFLD review following PRISMA protocol were PubMed, Google scholar, Scopus and Science Direct. Quality of evidence was assessed by consistent results with previous studies. Assessment of quality was done by Joanna Briggs Institute criteria. Quality of evidence was assessed by GRADE approach tool.

    RESULTS: This review included 12 studies, from which five were qualitative and seven quantitative. The later showed poor dietary habits and sedentary lifestyle exhibiting MAFLD which eventually affect their quality of life. Further studies suggested that by introducing healthy lifestyle in MAFLD group using diet and exercise caused reduction in BMI, obesity levels, improved glycemic control and reversal of liver fat content with improved liver enzymes.

    CONCLUSION: Subjects with MAFLD experienced poor quality of life. Altering lifestyle by diet and exercise can improve their physical wellbeing.

Related Terms
    Try searching for something
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links