Advancing Indonesian Neuropsychological Assessment with Tools from Computer Science

Many neuropsychological tests developed in Western countries may not accurately reflect Indonesia’s diverse population, necessitating localized data collection.To support neuropsychologists, a digital platform was developed, providing access to normative scores for the Indonesian Boston Naming Test (I-BNT). This platform accounts for demographic factors, improving diagnostic accuracy. Additionally, an Indonesian Neuropsychological Test Battery (INTB) was introduced, highlighting the influence of age and education on cognitive performance. A Principal Component Analysis (PCA) study identified seven cognitive constructs relevant to Indonesia, emphasizing the need for demographic-adjusted normative scores. A computer vision-based scoring system for visual-spatial tests was also developed, improving objectivity in cognitive assessments. Furthermore, an AI-based speech recognition system (Wav2Vec2) was applied to verbal neuropsychological tests, enhancing automated scoring accuracy. These innovations modernize assessments, making neuropsychological services more accessible and reliable across Indonesia.