TUG test instrumentation for parkinson's disease patients using inertial sensors and dynamic time warping

Biomedizinische Technik

Volumn 57, Issue SUPPL. 1 TRACK-E, 2012, Pages 1071-1074

  Adame, M Reyes ^a   Al Jawad, A ^b   Romanovas, M ^b   Hobert, M A ^d,e   Maetzler, W ^d,e   Moller K ^a   Manoli, Y ^b,c  

^a FURTWANGEN UNIVERSITY   (Germany)

^b Institut für Mikro und Informationstechnik der Hahn Schickard Gesellschaft E V HSG IMIT Villingen Schwenningen   (Germany)

^c UNIVERSITY OF TÜBINGEN   (Germany)

^d GERMAN CENTER FOR NEURODEGENERATIVE DISEASES DZNE   (Germany)

^e UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL ENGINEERING;

AUTOMATIC ASSESSMENT; DYNAMIC TIME WARPING; FUNCTIONAL ACTIVITIES; HEALTHY INDIVIDUALS; OBJECTIVE INFORMATION; TEST INSTRUMENTATION; TIMED UP AND GO (TUG); VISUAL OBSERVATIONS;

NEURODEGENERATIVE DISEASES;

EID: 84903949928     PISSN: 00135585     EISSN: None     Source Type: Journal    
DOI: 10.1515/bmt-2012-4426     Document Type: Article

References (16)

1. Chen JJ "Parkinson's disease: health-related quality of life, economic cost, and implications of early treatment." Am J Manag Care. 2010 Mar;16 Suppl Implications:S87-93. Review.
2. Simo S. Oja, Arne Schousboe, Pirjo Saransaari, Abel Lajtha "Handbook of Neurochemistry and Molecular Neurobiolo-gy: Amino Acids and Pep-tides in the Nervous System" 3rd edition, Springer Verlag, 2007, ISBN-10: 0387303421
3. Maetzler W, Liepelt I, Berg D. Progression of Parkinson's disease in the clinical phase: potential markers. Lancet Neu-rol 2009; 8: 1158-71.
4. Salarian A, Horak FB, Zampieri C, Carlson-Kuhta P, Nutt JG, Aminian K. iTUG, a sensitive and reliable measure of mobility. IEEE Trans Neural Syst Rehabil Eng. 2010 Jun;18(3):303-10. Epub 2010 Apr 12.
5. Grimaldi G, Manto M. Neurological tremor: sensors, signal processing and emerging applications. Sensors (Basel). 2010;10(2):1399-422.
6. Brusse KJ, Zimdars S, Zalewski KR, et al. Testing functional performance in people with Parkinson disease. Phys Ther. 2005; 85:134-141.
7. Pierre Jallon, Benjamin Dupre and Michel Antonakios "A graph based method for timed up and go test qualification using inertial sensors", 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011, Pages: 689-692
8. Luca Palmerini, Sabato Mellone, Laura Rocchi, Lorenzo Chiari "Dimensionality reduction for the quantitative eval-uation of a smartphone-based Timed Up and Go test", IEEE Engineering in Medicine and Biology Society, Aug 2011
9. Weiss A, Herman T, Plotnik M, Brozgol M, Giladi N, Hausdorff JM. "An instrumented Timed Up and Go: the added value of an accelerometer for identifying fall risk in idiopathic fallers". Physiol Meas. 2011 Dec;32(12):2003-18.
10. Higashi, Y.; Yamakoshi, K.; Fujimoto, T.; Sekine, M.; Tamura, T.;, "Quantitative evaluation of movement using the timed up-and-go test," Engineering in Medicine and Biology Magazine, IEEE, vol.27, no.4, pp.38-46, July-Aug. 2008
11. Sasiwan Paiyarom, Poj Tungamchit, Rachapor Keinprasit, Prakasith Kayasith "Activity Monitoring System using Dy-namic Time Warping for the Elderly and Disabled people", Computer, Control and Communication, 2009, IEEE 2009
12. Rossana Muscillo, Silvia Conforto, Maurizio Schmid, Paolo Caselli, Tommaso D'Alessio "Classification of motor activi-ties through derivative dynamic time warping applied on ac-celerometer data", Engineering in Medicine and Biology Society, 2007. EMBS 2007
13. McRobersts Moving Technology. [Online]. Available: http://www.mcroberts. nl [last accessed: march 2012]
14. Müller M., "Information Retrieval for Music and Motion", Springer-Verlag 2007, Chapter 4 Dynamic Time Warping
15. Ming Hsiao Ko, Geoff West, Svetha Venkatesh, Mohan Kumar, "Using dynamic time warping for online temporal fusion in multisensor systems", Information Fusion, Volume 9, Issue 3, July 2008, Pages 370-388, ISSN 1566-2535
16. H. B. Mitchell, "Multi-Sensor Data Fusion: An Introduction", 1st ed. Springer, Sep. 2007.