Article Preview
TopLiterature Review
The evaluation of brain function is critical in understanding various neurological conditions, including brain injuries and dementia. Traditional assessment methods have relied heavily on subjective measures, which can introduce bias and variability in results. Recent advancements have focused on objective measurement techniques, which can provide more reliable data.
Existing objective measurement and evaluation methods for brain function can be categorized into three main types: clinical methods, wearable devices, and computerized evaluation systems. These methods effectively mitigate the influence of subjective factors on measurement results (Winter et al., 2022; Elliott et al., 2020; Marek et al., 2022). However, they often face challenges, such as high environmental requirements and limited sensitivity to pre-disease testing (Lau et al., 2022).
Recent studies have explored innovative approaches to brain health assessment. For instance, Karimullah et al. (2024) developed a method for detecting and classifying brain tumors using advanced imaging techniques and deep learning algorithms. This work highlights the potential of integrating artificial intelligence with traditional imaging methods to enhance diagnostic accuracy.
The brain function encompasses various aspects, such as perception, thinking, emotion, and memory. Understanding the cognitive processes involved in piano sight-reading can provide a robust theoretical framework for its use as a cognitive assessment tool. Piano sight-reading engages several cognitive functions, including memory, pattern recognition, and motor control (Imai-Matsumura & Mutou, 2023; Tarbet & Park, 2023). Memory plays a crucial role as musicians must recall musical notations and their corresponding finger placements. Pattern recognition is essential for quickly identifying musical sequences and structures, allowing for fluid performance. Motor control is equally important, as it involves the coordination of hand movements to produce music accurately (Jia & Roongruang, 2023).