Online FOG Identification in Parkinson's disease with a time-frequency combined Algorithm

Y. Zhao, K. Tonn, K. Niazmand, U. M. Fietzek, L. T. D'Angelo, A. Ceballos-Baumann, T. C. Lueth

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

30 Zitate (Scopus)

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.

OriginalspracheEnglisch
TitelProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics
UntertitelGlobal Grand Challenge of Health Informatics, BHI 2012
Seiten192-195
Seitenumfang4
DOIs
PublikationsstatusVeröffentlicht - 2012
VeranstaltungIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering - Hong Kong and Shenzhen, China
Dauer: 2 Jan. 20127 Jan. 2012

Publikationsreihe

NameProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012

Konferenz

KonferenzIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering
Land/GebietChina
OrtHong Kong and Shenzhen
Zeitraum2/01/127/01/12

Fingerprint

Untersuchen Sie die Forschungsthemen von „Online FOG Identification in Parkinson's disease with a time-frequency combined Algorithm“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren