Improvement of Design Parameters for Health Monitoring in Wearable Fitness Device: A Fuzzy Analytic Kano Approach

Abstract

The development of cloud storage and integrated technology makes traditional health-monitoring devices change towards the direction of wearable intelligence. The most prominent of wearables is miniaturization, but multifunction is also required to meet the diversity needs of users. Under these contradictory conditions, the optimization of design parameters to meet user needs become one critical factor for the success of wearable devices. Accordingly, the probe of user needs for wearable fitness device attracted many researchers’ attention. These studies mainly draw the outline of user preferences or depicted critical design factors at the early development stage, but they were short of analyzing specific design parameters for the product already on the market. Therefore, this study aims to classify and then rank design parameters in a more comprehensive manner in order to improve end user satisfaction. Specifically, 146 experienced users’ responses for one wearable activity tracker were collected to extract user preferences by combining fuzzy sets and Kano model. Finally, by virtue of satisfaction increment index (SII) and dissatisfaction decrement index (DDI), the rank of design parameters for improvement is obtained.