Enhancing Biomedical Research with ResearchKit: Digitization of IPAQ and MMSE for Sedentary Behavior and Cognitive Impairment Analysis

Medical questionnaires and forms play a crucial role in diagnosing diseases and gathering essential patient information. Traditionally, these assessments are conducted through face-to-face interactions or phone calls, which can be time-consuming, costly, and inefficient. To address these challenges, digital adaptations of medical questionnaires have been developed, enabling faster and more accessible data collection across various platforms and applications.ResearchKit, an open-source framework introduced by Apple, allows researchers and developers to create robust mobile applications for medical research. By leveraging this technology, large-scale data collection can be conducted efficiently, facilitating real-time analysis while reaching a broader population. The availability of extensive datasets is essential for computational techniques such as Machine Learning, which require significant amounts of data for classification, pattern recognition, and predictive modeling in healthcare.This paper focuses on the digitization of medical questionnaires, specifically the International Physical Activity Questionnaire (IPAQ) and the Mini-Mental State Examination (MMSE), using ResearchKit. The transition from paper-based to digital forms significantly improves the efficiency of medical assessments, allowing healthcare professionals to analyze results remotely and optimize patient diagnosis and treatment plans. The findings emphasize the impact of digital health solutions in advancing medical research, reducing costs, and enhancing the accuracy and scalability of data-driven healthcare applications.