@inproceedings{50fc06454d9f4f65accc2f48f182abb4,
title = "Combined analysis of sensor data from hand and gait motor function improves automatic recognition of Parkinson's disease",
abstract = "Objective and rater independent analysis of movement impairment is one of the most challenging tasks in medical engineering. Especially assessment of motor symptoms defines the clinical diagnosis in Parkinson's disease (PD). A sensor-based system to measure the movement of the upper and lower extremities would therefore complement the clinical evaluation of PD.",
author = "Jens Barth and Michael S{\"u}nkel and Katharina Bergner and Gerald Schickhuber and Jurgen Winkler and Jochen Klucken and Bjorn Eskofier",
year = "2012",
doi = "10.1109/EMBC.2012.6347146",
language = "English",
isbn = "9781424441198",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
pages = "5122--5125",
booktitle = "2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012",
note = "34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 ; Conference date: 28-08-2012 Through 01-09-2012",
}