The present invention relates to the field of disease tracking and potentially even diagnostics. Specifically, it relates to a method for predicting the total motor score (TMS) in a subject suffering from Huntington's Disease (HD) comprising the steps of determining at least one performance parameter from a dataset of measurements of central motor function capabilities from said subject, comparing the determined at least one performance parameter to a reference obtained from a computer-implemented regression model generated on training data, in an embodiment using partial least-squares (PLS) analysis, with the at least one performance parameters, and predicting the TMS of the subject based on said comparison. The present invention also relates to a mobile device comprising a processor, at least one sensor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention as well as a system comprising a mobile device comprising at least one sensor and a remote device comprising a processor and a database as well as software which is tangibly embedded to said device and, when running on said device, carries out the method of the invention, wherein said mobile device and said remote device are operatively linked to each other. Furthermore, the invention contemplates the use of the aforementioned mobile device or system for predicting the TMS in a subject suffering from HD using at least one performance parameter from a dataset of measurements of central motor function capabilities from said subject.
MEANS AND METHODS FOR ASSESSING HUNTINGTON´S DISEASE (HD)