Abstract
Motor signs are critical features of psychosis that remain underutilized in clinical practice. These signs, including social motor behaviors, mechanistically relevant motor signs, and other motor abnormalities, have demonstrated potential as biomarkers for early detection and intervention. However, their application in clinical settings remains limited due to challenges such as cost, accessibility, and integration into clinical workflows. Recent advancements in related research fields, such as Human Movement Sciences and Affective Computing, offer promising solutions, enabling scalable and precise measurement of patients motor signs. In this editorial, we explore the spectrum of motor signs and highlight the evolving role of motor assessments in psychosis research. By examining traditional assessment methods alongside alternative and innovative tools, we underscore the potential of leveraging technology and methodology to bridge the gap between research and clinical application, ultimately advancing personalized care and improving outcomes.