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Gait analysis system based on accelerometers
Języki publikacji
Abstrakty
Przedmiotem pracy jest system badania i analizy chodu. Pomiary przyspieszeń wykonywane są w różnych punktach anatomicznych z wykorzystaniem trójosiowych czujników przyspieszenia, transmisja danych odbywa się w standardzie Bluetooth, a do akwizycji wykorzystano przenośny komputer. Oprogramowanie służące do zapisu, przetwarzania i analizy danych zostało napisane w środowisku LabVIEW. Badania chodu przeprowadzono na 17 ochotnikach. Uzyskano parametry związane ze zdarzeniami w cyklu chodu, a także wysokie wartości czułości (91-94%) i specyficzności (88-89%) detekcji zdarzeń oraz satysfakcjonującą wartość parametru %R&R (16%).
Gait analysis provides useful information about spatio-temporal parameters [10, 11], stability and balance [7], progression of the diseases (Parkinson, Huntington) [7, 8], results of rehabilitation [6] or shock attenuation [7, 9]. The paper describes the accelerometer-based system designed for motion and gait examination. The system consists of two measurement modules with triaxial ADXL accelerometers (Tab. 1), portable computer and software implemented in LabVIEW environment. The system features data transmission via a Bluetooth network and during examination the data is received on a portable computer, visualized on a graph and written in a text file (Fig. 2). The text file has a special header which contains information about the examined person, anatomical axes and a name of the place of module attachment. The all information is introduced by a user at the beginning of the examination. After signal processing, several parameters are calculated: mean duration of the gait cycle, mean duration of swing and stance phases in percentage of the gait cycle, acceleration range (Fig. 1, Tab. 2) [15]. Detection of gait cycle events (heel strike, toe off) is based on the analysis of local extremes of the parameter RSS (Formula 1) [16]. For every anatomical point there is also visualized a graph with accelerations for the whole mean gait cycle (Fig. 4). At the end of data analysis, an examination report as a Microsoft Word document file is prepared. System tests were performed on 17 volunteers (Fig. 3) who underwent gait examination. Depending on the goal, only one or both modules were used. There were different places of module attachment: ankles, knees, hips, sacrum, neck and head. High values of sensitivity (91-94%) and specificity (88-89%) of event detection as well as satisfactory value of %R&R parameter (16%) were obtained.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
327--330
Opis fizyczny
Bibliogr. 17 poz., rys., tab., wzory
Twórcy
autor
autor
autor
autor
- AGH Akademia Górniczo-Hutnicza, WEAIIE, Katedra Metrologii, Al. Mickiewicza 30, Kraków, piotr.maj@agh.edu.p
Bibliografia
- [1] Mercer J. A., Bezodis N. E., Russel M., Purdy A., DeLion D.: Kinetic consequences of constraining running behaviour. Journal of Sports Science and Medicine. Asist Group, 4, 2005.
- [2] Mizrahi J., Verbitsky O., Isakov E.: Shock accelerations and attenuation in downhill and level running. Clinical Biomechanics. Elsevier, 15, 2000.
- [3] Pärkkä J., Ermes M., Korpipää P., Mäntyjärvi J., Peltola J., Korhonen I.: Activity classification using realistic data from wearable sensors. Information Technology in Biomedicine. IEEE, 10/1, 2006.
- [4] Doherty S. T.: Emerging methods and technologies for tracking physical activity in built environment. 8th International Conference on Survey Methods in Transport, Annecy, France 25-31 May, 2008.
- [5] Mathie M. J., Coster A. C. F., Lovell N. H., Celler B. G.: Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiological Measurement, Institute of Physics Publishing, 25, 2004.
- [6] Culhane K. M., O’Connor M., Lyons D., Lyons G. M.: Accelerometers in rehabilitation medicine for older adults. Age and Ageing. Oxford Journals, 34, 2005.
- [7] Kavanagh J. J., Menz H. B.: Accelerometry: A technique for quantifying movement patterns during walking. Gait & Posture. Elsevier, 28, 2008.
- [8] Hausdorff J. M., Cudkowicz M. E., Firition R., Wei J., Goldberger A. L.: Gait variability and Basal Ganglia Disorders: Stride to Stride Variations of Gait Cycle Timing in Parknson’s Disease and Huntingon’s Disease. Movement Disorders. The Movement Disorder Society, 3/3, 1998.
- [9] Szczygieł E., Król S., Korbiel T., Mazur T.: Accelerometric testing of selected point sof the human locomotor system. Medical Rehabilitation. Collegium Medicum UJ, 14/3, 2010.
- [10] Moe-Nilssen R., Helbostad J. L.: Estimation of gait cycle characteristics by trunk accelerometry. Journal of Biomechanics. Elsevier, 37, 2004.
- [11] Zijstra W., Hof A. L.: Assesment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait & Posture. Elsevier, 18, 2003.
- [12] Bouten C. V., Westerterp K. R., Verduin M., Janssen J. D.: Assessment of energy expenditure for physical activity using a triaxial accelerometer. Medicine and Science in Sports and Exercise. American College of Sports and Medicine, 26/12, 1994.
- [13] Asano M., Tanabe Y., Watanabe K., Genno H., Niemoto K., Isawa M., Nose H.: Development of an Exercise Meter using Triaxial Acceleration Data. Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference Shanghai, China, September 1-4, 2005.
- [14] Hausdorff J. M.: Gait variability: methods, modeling and meaning. Journal of NeuroEngineering and Rehabilitation. BioMed Central Ltd, 2005.
- [15] Cuccurullo S.: Physical Medicine and Board Review, Demos Medical Publishing, Inc, New York, 2004.
- [16] Bourke A., O’Brien J., Lyons G. M.: Evaluation of a thresh-old-based tri-axial accelerometer fall detection algorithm. Gait & Posture. Elsevier 26/2, 2006.
- [17] Kavanagh J. J., Morrison S., James D. A., Barrett R.: Reliability of segmental accelerations measured using a new wireless gait analysis system. Journal of Biomechanics. Elsevier, 39, 2006.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW4-0119-0006