A data-driven innovative design method for smart product-service systems to achieve mass personalization in rehabilitation

Abstract

Smart product-service system (Smart PSS), as an emerging digital paradigm, offers users solution bundles to enhance the digitalization capability of the system by utilizing user-generated data. Massive information can be collected to investigate the dynamic changes of user requirements and assists the developers in designing personalized products and services. Meanwhile, key technologies (i.e. big data analysis and cloud computing) have enabled upgrading the rehabilitation equipment from the traditional physical training device to the personalized smart rehabilitation product-service system. However, few studies focus on gathering and utilizing user-generated physiological data to guide the innovative design of rehabilitation solutions in the Smart PSS environment. To fill this gap, an innovative design method is proposed to guide the Smart PSS development in the personalized rehabilitation field. The presented approach can be divided into three phases: the research phase, the development phase, and the usage phase. A personalized lower limb rehabilitation smart product-service system was described to explain the proposed approach.