TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Steinmetzer, Tobias
A1  - Bönninger, Ingrid
A1  - Priwitzer, Barbara
A1  - Reinhardt, Fritjof
A1  - Reckhardt, Markus Christoph
A1  - Erk, Dorela
T1  - Clustering of Human gait with Parkinson’s disease by using Dynamic Time Warping
T2  - 2018 IEEE International Work Conference on Bioinspired Intelligence : proceedings : July 18-20, 2018, Instituto Tecnológico de Costa Rica, San Carlos, Costa Rica
N2  - We present a new method for detecting gait disorders according to their stadium using cluster methods for sensor data. 21 healthy and 18 Parkinson subjects performed the time up and go test. The time series were segmented into separate steps. For the analysis the horizontal acceleration measured by a mobile sensor system was considered. We used dynamic time warping and hierarchical custering to distinguish the stadiums. A specificity of 92% was achieved.
KW  - DTW
KW  - clustering
KW  - parkinson disease
KW  - time series
Y1  - 2018
SN  - 978-1-5386-7506-9
SB  - 978-1-5386-7506-9
U6  - https://doi.org/10.1109/IWOBI.2018.8464203
DO  - https://doi.org/10.1109/IWOBI.2018.8464203
SP  - 6
S1  - 6
PB  - IEEE
CY  - Piscataway, NJ
ER  -