The purpose of this study is to realize customized precision medicine for stroke patients and the visual digitization of patient medical information required in the era of digital transformation. This study will collect large-scale, high-quality clinical data and daily life exercise pattern data covering the subacute to chronic stages of stroke patients. Based on this, we will use artificial intelligence analysis technology to predict the functional status of stroke patients in the chronic stage after their disability is fixed. We aim to develop the next generation of personalized digital twins by creating a prognostic prediction model.