Title :
Online FOG Identification in Parkinson´s disease with a time-frequency combined Algorithm
Author :
Zhao, Y. ; Tonn, K. ; Niazmand, K. ; Fietzek, U.M. ; D´Angelo, L.T. ; Ceballos-Baumann, A. ; Lueth, T.C.
Author_Institution :
Inst. of Micro Technol. & Med. Device Technol., Tech. Univ. of Munich, Munich, Germany
Abstract :
Parkinson´s disease (PD) is a common degenerative neurological disorder. Freezing of Gait (FOG) is a significant symptom in PD. Sudden FOG causes balance disturbances and increases the risk of falls. An online approach for FOG identification is presented using MiMed-Pants and an online test software with a frequency-time combined algorithm. MiMed-Pants are washable jogging-trousers with integrated accelerometers. Eight Parkinson patients with different FOG severity used the MiMed-pants and walked following arbitrary instructions from a physician. FOG events were identified and recorded both by the online approach and by a physician. Results were compared with each other to determine the sensitivity of the developed algorithm. Using this wearable measurement device, FOG events could be identified without distraction of patients´ attention.
Keywords :
accelerometers; automatic test software; diseases; medical computing; medical disorders; neurophysiology; time-frequency analysis; FOG events; MiMed-Pants; PD symptom; Parkinson patients; Parkinson´s disease; degenerative neurological disorder; freezing of gait; integrated accelerometers; online FOG identification; online test software; time-frequency combined algorithm; walked following arbitrary instructions; washable jogging trousers; wearable measurement device; Medical services;
Conference_Titel :
Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-2176-2
Electronic_ISBN :
978-1-4577-2175-5
DOI :
10.1109/BHI.2012.6211542