NDLI: Gait assessment in Parkinson's disease patients through a network of wearable accelerometers in unsupervised environments

Content Provider	IEEE Xplore Digital Library
Author	Cancela, J. Pastorino, M. Arredondo, M.T. Pansera, M. Pastor-Sanz, L. Villagra, F. Pastor, M.A. Gonzalez, A.P.
Copyright Year	2011
Description	Author affiliation: Division of Neurosciences, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain (Villagra, F.; Pastor, M.A.) \|\| Life Supporting Technologies, Technical University of Madrid (UPM), Madrid 28804 Spain (Cancela, J.; Pastorino, M.; Arredondo, M.T.; Pansera, M.; Pastor-Sanz, L.) \|\| Neurophotonics group, Technical University of Madrid (UPM), Madrid 28804 Spain (Gonzalez, A.P.)
Abstract	Parkinson's disease (PD) predominantly alters the motor performance of the affected individuals. In particular, the loss of dopaminergic neurons compromises the speed, the automaticity and fluidity of movements. As the disease evolves, PD patient's motion becomes slower and tremoric and the response to medication fluctuates along the day. In addition, the presence of involuntary movements deteriorates voluntary movement in advanced state of the disease. These changes in the motion can be detected by studying the variation of the signals recorded by accelerometers attached in the limbs and belt of the patients. The analysis of the most significant changes in these signals make possible to build an individualized motor profile of the disease, allowing doctors to personalize the medication intakes and consequently improving the response of the patient to the treatment. Several works have been done in a laboratory and supervised environments providing solid results; this work focused on the design of unsupervised method for the assessment of gait in PD patients. The development of a reliable quantitative tool for long-term monitoring of PD symptoms would allow the accurate detection of the clinical status during the different PD stages and the evaluation of motor complications. Besides, it would be very useful both for routine clinical care as well as for novel therapies testing.
Starting Page	2233
Ending Page	2236
File Size	691844
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6090423
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Parkinson's disease Entropy Accelerometers Belts Acceleration
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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