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Layout   printable version	eGaIT - embedded Gait analysis using Intelligent Technology Parkinson`s disease (PD) is a chronic disorder of the central nervous system, characterized by degeneration of dopaminergic neurons leading to progressive gait dysfunction. To maintain patient's quality of life, objective classification of gait symptoms in PD is crucial to adequately manage the individual treatment. We will establish a sensor based biometric gait-analysis that enables reproducible, objective, rater- independent assessment of gait symptoms. With a therapist independent rating completely comparable results can be reached. Different sensors (gyroscopes, accelerometers, in-sole pressure sensors,...) attached to a comfortable sport shoe detected motion signals assessed during standardized exercises while the subject is walking or sitting on a chair. Using pattern recognition methods, signal features should be analyzed from PD patients and healthy controls. Classification between patients and controls and an identification of different PD stages should be done. A pilot study suggests that biometric gait-analysis may be an important and complementary mean to support disease management in PD. Future biometric studies will help to monitor the disease course, to modify and adjust treatment thus rationalizing therapeutic decisions. To differentiate between PD specific and age dependent gait disorders also data from subjects in different decades of life should be analyzed. Project manager: Ralph Steidl Project participants: Prof. Dr. med. Jürgen Winkler, Prof. Dr. Jochen Klucken, Dipl.-Ing. Jens Barth, Dipl.-Phys. Samuel Reinfelder Keywords: Parkinson; Motion analysis; gait impairments; inertial sensors; gyroscopes; accelerometers; signal analysis Duration: 8.12.2011 - 7.12.2014 Sponsored by: Bayerische Forschungsstiftung Mitwirkende Institutionen: ASTRUM IT GmbH Universitätsklinikum Erlangen, Abteilung für Molekulare Neurologie, Spezialambulanz für Bewegungsstörungen Contact: Barth, Jens Phone +49 9131 85 28990, Fax +49 9131 85 27270, E-Mail: jens.barth@cs.fau.de Publications Barth, Jens ; Sünkel, Michael ; Eskofier, Björn ; Klucken, Jochen: Combined analysis of hand and gait motor function in Parkinson's disease (Talk).Talk: Kongress und Ausstellung MedTech Pharma und Medizin Innovativ 2012, MedTech Pharma, Nürnberg, 05.07.2012 Barth, Jens ; Klucken, Jochen ; Kugler, Patrick ; Kammerer, Thomas ; Steidl, Ralph ; Winkler, Jürgen ; Hornegger, Joachim ; Eskofier, Björn: Biometric and Mobile Gait Analysis for Early Detection and Therapy Monitoring in Parkinson's Disease. In: IEEE Engineering in Medicine and Biology Society (Org.) : Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE (33rd Annual International Conference of the IEEE EMBS Boston, USA August 30 - September 3, 2011). 2011, pp 868-871. Klucken, Jochen ; Barth, Jens ; Maertens, Katharina ; Eskofier, Björn ; Kugler, Patrick ; Steidl, Ralph ; Hornegger, Joachim ; Winkler, Jürgen: Mobile biometrische Ganganalyse. In: Der Nervenarzt 2011 (2011), No. 12, pp 1604-1611 [doi>10.1007/s00115-011-3329-0] Klucken, Jochen ; Barth, Jens ; Eskofier, Björn ; Winkler, Jürgen: Automated gait analysis in Parkinson's disease. In: Basal Ganglia 3 (2013), No. 1, pp 61 [doi>10.1016/j.baga.2013.01.058] Klucken, Jochen ; Barth, Jens ; Eskofier, Björn ; Winkler, Jürgen: Biosensorische Bewegungserfassung beim Parkinson-Syndrom. In: Neurologie & Rehabilitation 19 (2013), No. 0, pp 69-76 Barth, Jens ; Eskofier, Björn ; Winkler, Jürgen ; Klucken, Jochen: Individualized rating of motor impairment using sensor-based gait analysis in Parkinson's disease by multiparametric regression. In: Basal Ganglia 3 (2013), No. 1, pp 52-53 [doi>10.1016/j.baga.2013.01.037] Barth, Jens ; Oberndorfer, Cäcilia ; Kugler, Patrick ; Schuldhaus, Dominik ; Winkler, Jürgen ; Klucken, Jochen ; Eskofier, Björn: Subsequence dynamic time warping as a method for robust step segmentation using gyroscope signals of daily life activities. In: IEEE Engineering in Medicine and Biology Society (Ed.) : Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE (35th Annual International Conference of the IEEE EMBS Osaka, Japan July 3-7, 2013). 2013, pp 6744-6747. [doi>10.1109/EMBC.2013.6611104] Klucken, Jochen ; Barth, Jens ; Kugler, Patrick ; Schlachetzki, Johannes ; Henze, Thore ; Marxreiter, Franz ; Kohl, Zacharias ; Steidl, Ralph ; Hornegger, Joachim ; Eskofier, Björn ; Winkler, Juergen: Unbiased and Mobile Gait Analysis Detects Motor Impairment in Parkinson's Disease. In: PLoS ONE 8 (2013), No. 2, pp e56956 [doi>10.1371/journal.pone.0056956] Institution: Chair of Computer Science 5 (Pattern Recognition) UnivIS is a product of Config eG, Buckenhof