The gait disturbances in Parkinson's disease (PD) patients occur occasionally and intermittently, appearing in a random, inexplicable manner. These disturbances include festinations, shuffling, and complete freezing of gait (FOG). Alternation of walking pattern decreases the quality of life and may result in falls. In order to recognize disturbances during walking in PD patients, we recorded gait kinematics with wireless inertial measurement system and designed an algorithm for automatic recognition and classification of walking patterns. The algorithm combines a perceptron neural network with simple signal processing and rule-based classification. In parallel, gait was recorded with video camera. Medical experts identified FOG episodes from videos and their results were used for comparison and validation of this method. The summary result shows that the error in recognition and classification of walking patterns is up to 16%.
TY - CONF
AU - Đurić-Jovičić, Milica
AU - Jovičić, Nenad S.
AU - Milovanović, I.
AU - Radovanović, Saša M.
AU - Kresojević, Nikola D.
AU - Popović, M.B.
PY - 2010
UR - http://rimi.imi.bg.ac.rs/handle/123456789/313
AB - The gait disturbances in Parkinson's disease (PD) patients occur occasionally and intermittently, appearing in a random, inexplicable manner. These disturbances include festinations, shuffling, and complete freezing of gait (FOG). Alternation of walking pattern decreases the quality of life and may result in falls. In order to recognize disturbances during walking in PD patients, we recorded gait kinematics with wireless inertial measurement system and designed an algorithm for automatic recognition and classification of walking patterns. The algorithm combines a perceptron neural network with simple signal processing and rule-based classification. In parallel, gait was recorded with video camera. Medical experts identified FOG episodes from videos and their results were used for comparison and validation of this method. The summary result shows that the error in recognition and classification of walking patterns is up to 16%.
C3 - 10th Symposium on Neural Network Applications in Electrical Engineering, NEUREL-2010 - Proceedings
T1 - Classification of walking patterns in Parkinson's disease patients based on inertial sensor data
EP - 6
SP - 3
DO - 10.1109/NEUREL.2010.5644040
UR - conv_5277
ER -
@conference{
author = "Đurić-Jovičić, Milica and Jovičić, Nenad S. and Milovanović, I. and Radovanović, Saša M. and Kresojević, Nikola D. and Popović, M.B.",
year = "2010",
abstract = "The gait disturbances in Parkinson's disease (PD) patients occur occasionally and intermittently, appearing in a random, inexplicable manner. These disturbances include festinations, shuffling, and complete freezing of gait (FOG). Alternation of walking pattern decreases the quality of life and may result in falls. In order to recognize disturbances during walking in PD patients, we recorded gait kinematics with wireless inertial measurement system and designed an algorithm for automatic recognition and classification of walking patterns. The algorithm combines a perceptron neural network with simple signal processing and rule-based classification. In parallel, gait was recorded with video camera. Medical experts identified FOG episodes from videos and their results were used for comparison and validation of this method. The summary result shows that the error in recognition and classification of walking patterns is up to 16%.",
journal = "10th Symposium on Neural Network Applications in Electrical Engineering, NEUREL-2010 - Proceedings",
title = "Classification of walking patterns in Parkinson's disease patients based on inertial sensor data",
pages = "6-3",
doi = "10.1109/NEUREL.2010.5644040",
url = "conv_5277"
}
Đurić-Jovičić, M., Jovičić, N. S., Milovanović, I., Radovanović, S. M., Kresojević, N. D.,& Popović, M.B.. (2010). Classification of walking patterns in Parkinson's disease patients based on inertial sensor data. in 10th Symposium on Neural Network Applications in Electrical Engineering, NEUREL-2010 - Proceedings, 3-6.
https://doi.org/10.1109/NEUREL.2010.5644040
conv_5277
Đurić-Jovičić M, Jovičić NS, Milovanović I, Radovanović SM, Kresojević ND, Popović M. Classification of walking patterns in Parkinson's disease patients based on inertial sensor data. in 10th Symposium on Neural Network Applications in Electrical Engineering, NEUREL-2010 - Proceedings. 2010;:3-6.
doi:10.1109/NEUREL.2010.5644040
conv_5277 .
Đurić-Jovičić, Milica, Jovičić, Nenad S., Milovanović, I., Radovanović, Saša M., Kresojević, Nikola D., Popović, M.B., "Classification of walking patterns in Parkinson's disease patients based on inertial sensor data" in 10th Symposium on Neural Network Applications in Electrical Engineering, NEUREL-2010 - Proceedings (2010):3-6,
https://doi.org/10.1109/NEUREL.2010.5644040 .,
conv_5277 .
