Designing an IoT-Based Vest for Elderly People with Dementia

Department of Industrial Engineering, Faculty of Industrial Technology, Islamic University of Indonesia

Abstract

The increasing elderly population is causing various changes that have an impact on health problems, one of which is cognitive function, namely dementia. This research will aim to create a smart vest that will have the main feature of location tracking, especially when the user is outside the home and has no supervision. Quality Function Deployment (QFD) method, usability, and anthropometry will be used to determine appropriate evaluation steps based on product needs analysis to ensure users can use the product easily, efficiently, and satisfactorily. In making VesTi products, several processes are carried out based on the main and body parts, namely the front and back vest, vest pockets, zippers, heart rate sensors, airbags, GPS sensor module, and crash collision sensor. Using the QFD method, the crash sensor variable has a value importance rating of 5.33 and a value relative view of 30%, which means that more attention is needed for developing crash sensors in VesTi products. Based on usability testing, the level of satisfaction at grades A+ or acceptable. The anthropometry used; chest circumference is 106 cm, shoulder width is 37 cm, waist circumference is 100 cm, wrist circumference is 18 cm, and front torso height is 67 cm.