Ambulatory monitoring of physical activities in patients with Parkinson's disease.

Details

Serval ID
serval:BIB_5584AD375516
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Ambulatory monitoring of physical activities in patients with Parkinson's disease.
Journal
Ieee Transactions On Bio-medical Engineering
Author(s)
Salarian A., Russmann H., Vingerhoets F.J., Burkhard P.R., Aminian K.
ISSN
0018-9294[print], 0018-9294[linking]
Publication state
Published
Issued date
2007
Volume
54
Number
12
Pages
2296-2299
Language
english
Notes
Publication types: Controlled Clinical Trial ; Journal Article ; Research Support, Non-U.S. Gov't
Abstract
A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.
Keywords
Acceleration, Activities of Daily Living, Artificial Intelligence, Diagnosis, Computer-Assisted/methods, Electric Stimulation Therapy, Equipment Design, Equipment Failure Analysis, Female, Humans, Male, Middle Aged, Monitoring, Ambulatory/instrumentation, Monitoring, Ambulatory/methods, Motor Activity, Parkinson Disease/diagnosis, Parkinson Disease/physiopathology, Treatment Outcome
Pubmed
Web of science
Create date
08/03/2011 12:26
Last modification date
20/08/2019 14:10
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