Personalizing Smart Services Based on Data-Driven Personality of User

Krzeminska, Izabella

doi:10.1007/978-3-030-40907-4_21

Cited by 2 publications

(1 citation statement)

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“…The big data generated by the Internet of Things, artificial intelligence, and mobile rehabilitation contribute to the iterative refinement of the design of rehabilitation products and services, particularly within hospital, community, and family settings [32][33][34]. The user is the key element of the service system, with the design centered on meeting the service expectations of users; the existence of the rehabilitation needs of users drives the emergence of other factors [35,36].…”

Section: B Development Of Rehabilitation Product Service Systemmentioning

confidence: 99%

Design Method of a Smart Rehabilitation Product Service System Based on Virtual Scenarios: A Case Study

Zhao,

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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The development of artificial intelligence and virtual reality technology has enabled rehabilitation service systems based on virtual scenarios to provide patients with a multi-sensory simulation experience. However, the design methods of most rehabilitation service systems rarely consider the physician-manufacturer synergy in the patient rehabilitation process, as well as the problem of inaccurate quantitative evaluation of rehabilitation efficacy. Thus, this study proposes a design method for a smart rehabilitation product service system based on virtual scenarios. This method is important for upgrading the rehabilitation service system. First, the efficacy of rehabilitation for patients is quantitatively assessed using multimodal data. Then, an optimization mechanism for virtual training scenarios based on rehabilitation efficacy and a rehabilitation plan based on a knowledge graph are established. Finally, a design framework for a full-stage service system that meets user needs and enables physician-manufacturer collaboration is developed by adopting a "cloud-end-human" architecture. This study uses virtual driving for autistic children as a case study to validate the proposed framework and method. Experimental results show that the service system based on the proposed methods can construct an optimal virtual driving system and its rehabilitation program based on the evaluation results of patients' rehabilitation efficacy at the current stage. It also provides guidance for improving rehabilitation efficacy in the subsequent stages of rehabilitation services.

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