Objective: The aim of this study is to derive digital anthropometric indexes related to spinal function, conduct a comprehensive systematic literature review study on the decision criteria and analyze the importance between indexes.
Background: Due to the increase in office workers using personal computer and mobile usage time, the number of patients with spine-related diseases such as VDT syndrome is increasing, and it is necessary to study various health care services for them. In order to conveniently and accurately measure the state of spinal function using digital technology, it is necessary to derive anthropometric indexes and research on the evidence criteria.
Method: According to the systematic literature review research protocol, digital anthropometric indexes based on 5 assessment tools were derived. An integrated analysis was performed on the data of previous studies for the determination of normal and abnormal states in digital anthropometric indexes. The importance of digital anthropometric indexes through analytic hierarchy process for providing comprehensive spinal function information (service data) was analyzed.
Results: Distinct differences between data from normal and abnormal states were observed across all five tools and specific anthropometric indexes. In assessing the importance of anthropometric indexes within the five assessments, the priority order was as follows: Adams forward bend test (34.7%), cervical range of motion (27.5%), Tragus to wall distance (21.2%), Trendelenbrug test (10.9%), and Chest expansion test (5.8%).
Conclusion: The procedures and methodologies employed in this study to derive digital anthropometric indexes for assessing spinal function hold significance as a foundational step towards digitizing body function evaluation and anthropometry.
Application: Anticipated effect of this research include the provision of high-quality healthcare services and enhanced user experiences. This stems from the ability to conveniently, accurately, and comprehensively assess, record, and leverage users' spinal health function data.