How data science workers work with data
Michael Muller, Ingrid Lange, et al.
CHI 2019
Parkinson’s disease (PD) is a chronic neurological disorder causing progressive disability that severely affects patients’ quality of life. Although early interventions can provide significant benefits, PD diagnosis is often delayed due to both the mildness of early signs and the high requirements imposed by traditional screening and diagnosis methods. In this paper, we explore the feasibility and accuracy of detecting motor impairment in early PD via sensing and analyzing users’ common touch gestural interactions on smartphones. We investigate four types of common gestures, including flick, drag, pinch, and handwriting gestures, and propose a set of features to capture PD motor signs. Through a 102-subject (35 early PD subjects and 67 age-matched controls) study, our approach achieved an AUC of 0.95 and 0.89/0.88 sensitivity/specificity in discriminating early PD subjects from healthy controls. Our work constitutes an important step towards unobtrusive, implicit, and convenient early PD detection from routine smartphone interactions.
Michael Muller, Ingrid Lange, et al.
CHI 2019
Xiangmin Fan, Junfeng Yao, et al.
CHI EA 2020
João Guerreiro, Dragan Ahmetovic, et al.
CHI 2019
Zahra Ashktorab, Mohit Jain, et al.
CHI 2019