Means and methods for assessing Huntington's disease of the pre-manifest stage

1 . A method for assessing Huntington's disease of the pre-manifest stage in a subject comprising the steps of:

a) obtaining from said subject using a mobile device a dataset of fine motoric measurements;

b) determining at least one performance parameter from the dataset of fine motoric measurements from said subject, wherein the at least one performance parameter is derived from the dataset by an automated algorithm implemented on a data processing device;

c) comparing by an automated comparison algorithm implemented on the data processing device the determined at least one performance parameter to a reference; and

d) assessing Huntington's disease of the pre-manifest stage in the subject based on said comparison;

wherein the fine motoric measurements are measurements of finger movement accuracy, dexterity, or speed, and wherein the fine motoric measurements are carried out by a speed tapping test using the mobile device; and

wherein the one or more performance parameters for fine motoric capabilities in the speed tapping test are maximum time the finger is lifted between two taps, coefficient of variance of the time the finger is lifted between two taps, coefficient of variance of the distance between two taps, standard deviation of the time the finger touches during a tap, coefficient of variance of the time the finger touches during a tap, and/or maximum time the finger touches during a tap.

2 . The method of claim 1 , wherein said mobile device is comprised of a smartphone, smartwatch, wearable sensor, portable multimedia device or tablet computer.

3 . The method of claim 1 , wherein the reference is at least one performance parameter from a dataset of fine motoric measurements from said subject, wherein said dataset has been obtained prior to the dataset of step a).

4 . The method of claim 1 , wherein the reference is at least one performance parameter from a dataset of fine motoric measurements from at least one subject known to suffer from Huntington's disease of the pre-manifest stage.

5 . The method of claim 4 , wherein at least one performance parameter being identical to the reference is indicative for a subject suffering from Huntington's disease of the pre-manifest stage.

6 . The method of claim 1 , wherein the reference is at least one performance parameter from a dataset of fine motoric measurements from at least one subject known not to suffer from Huntington's disease of the pre-manifest stage.

7 . The method of claim 6 , wherein at least one performance parameter which differs from the reference is indicative for a subject suffering from Huntington's disease of the pre-manifest stage.

8 . The method of claim 1 , wherein said assessing Huntington's disease of the pre-manifest stage comprises diagnosing or predicting Huntington's disease of the pre-manifest stage.

9 . The method of claim 8 , wherein said assessing Huntington's disease of the pre-manifest stage further comprises recommending therapies against Huntington's disease of the pre-manifest stage.

10 . 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 claim 1 .

11 . The mobile device of claim 10 , wherein the mobile device further comprises data transmission equipment.

12 . 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 mobile device and, when running on said mobile device, carries out the method of claim 1 , wherein said mobile device and said remote device are operatively linked to each other.

13 . The system of claim 12 , wherein the mobile device further comprises data transmission equipment and, when running said software on said mobile device, transfers the acquired dataset of fine motoric measurements from the mobile device to the remote device.