Movement disorder recovery system and method

摘要

Most particularly, the present invention relates to a customized and adaptive movement recovery system and a method of improving the functional motor recovery of a subject with a movement disorder. The present invention provides for a system and method, which in some embodiments can accurately quantify treatment device parameters and protocols including electrical stimulation amplitude (volts/amps), frequency (Hz), and pulse width (microseconds), and medication titrations, doses, and times by utilizing accelerometric, gyroscopic or other movement related information, such as electromyography (EMG) data, or the like, and a central database, or system of databases, of patient and treatment histories. In other embodiments, the system and method provide for an adaptive central database system and automated control of movement disorder treatment devices.

主权项

1. A system for providing treatment recommendations for movement disorders comprising:
a movement measuring apparatus for measuring external body motion of a subject with a movement disorder and for calculating a movement score representative of a score that a skilled clinician might give to a subject during a movement analysis exam using a standardized scale, the movement measuring apparatus comprising at least one sensor and a transmitter; an algorithm trained for correlating at least in part movement scores calculated from the subject with at least in part movement scores stored in at least one central database; at least one central database where historical movement data comprising at least in part movement data, including at least in part movement scores, from a plurality of other subjects is stored; a processor for correlating at least in part the calculated movement scores to the at least one central database and determining a recommended treatment using the algorithm; and a device for outputting or otherwise communicating the recommended treatment to a clinician or other user for review and administering; wherein the at least one central database contains at least former patient disorder and treatment information; and the algorithm is trained through a supervised learning process that uses as algorithm inputs at least any three of patient demographics, treatment history, disorder details, recorded movement data, current treatment protocols, and movement scores, and uses as matched outputs recommended treatment stimulation parameters; and the algorithm performs a stepwise regression to determine a combination of algorithm inputs and matched outputs with a correlation to clinician treatments for subjects, wherein, when calculated by the processor or algorithm, the resultant correlation to clinician treatments for subjects with successful outcomes has a correlation coefficient of greater than 0.25.