New technologies on capturing clinical data show an increasing role both in clinical trials and in routine management of patients suffering from Multiple Sclerosis (MS). One example are 3D camera-based quantifications of standardized movements like PASS-MS and Assess MS. The first computes typical movement parameters like gait speed from human poses, which are estimated in real-time by machine learning algorithms. The latter uses machine learning algorithms to directly analyse 3D-depth-sensor recordings of MS patients performing standard motor tests. Both potentially allow finer grading of motor dysfunction and tracking of clinical disability over time. Further, physical assessments including the quantification of disability progression (usually defined by the expanded disability status scale, EDSS) are important end-points in phase 3 trials for approval of new disease modifying treatments. However, they are prone to a high level of subjectivity and depend on many factors, e.g. the rater’s experience. Thus, standardization of the clinical assessment is crucial. To achieve this, several efforts were made in the last years. For example, an algorithm-based electronic version of the EDSS, the Neurostatus-eEDSS, provides real-time feedback to the raters and reduces inconsistencies in the assessments. It allows for direct storage of full-scale clinical data in electronic format. The use of so called “digital biomarkers” provides crucial information on how patients master their daily challenges. One example is the Floodlight study, in which active and passive tests were provided on smartphones to patients with MS as well as to healthy controls. These tests capture the patients’ daily performance and correlate with conventional in-clinic disability metrics. The use of new technologies and electronic tools in MS could provide a standardized, more reliable and sensitive capture and storage of clinical data. This development is crucial for clinical routine and clinical studies, particularly in progressive MS, where only slight clinical changes may be seen during short periods of time.