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Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients

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10.1007/s11517-015-1395-3
 
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Ahlrichs, Claas
Samà Monsonís, AlbertMés informacióMés informació
Lawo, Michael
Cabestany Moncusí, JoanMés informacióMés informació
Rodríguez Martín, Daniel ManuelMés informacióMés informació
Pérez López, CarlosMés informació
Quinlan, Leo R.
ÓLaighin, Gearóid
Counihan, Timothy
Lewy, Hadas
Annicchiarico, Roberta
Bayés, Àngels
Rodríguez Molinero, AlejandroMés informació
Document typeArticle
Defense date2015-10-01
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Freezing of gait (FOG) is a common motor symptom of Parkinson’s disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly detected by a support vector machine (SVM). Then, classifier’s outputs are aggregated over time to determine a confidence value, which is used for the final classification of freezing (i.e., second and third approach). All variations are trained with signals of 15 patients and evaluated with signals from another 5 patients. Using a linear SVM kernel, the third approach provides 98.7 % accuracy and a geometric mean of 96.1 %. Moreover, it is investigated whether frequency features are enough to reliably detect FOG. Results show that these features allow the method to detect FOG with accuracies above 90 % and that frequency features enable a reliable monitoring of FOG by using simply a waist sensor.
CitationAhlrichs, C., Sama, A., Lawo, M., Cabestany, J., Rodriguez-Martin, D., Perez, C., Quinlan, L., ÓLaighin, G., Counihan, T., Lewy, H., Annicchiarico, R., Bayés, À., Rodríguez, A. Detecting freezing of gait with a tri-axial accelerometer in Parkinson’s disease patients. "Medical and biological engineering and computing", 01 Octubre 2015, p. 1-11. 
URIhttp://hdl.handle.net/2117/86472
DOI10.1007/s11517-015-1395-3
ISSN0140-0118
Publisher versionhttp://link.springer.com/article/10.1007/s11517-015-1395-3
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  • CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma - Articles de revista [31]
  • Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial - Articles de revista [1.323]
  • Departament d'Enginyeria Electrònica - Articles de revista [1.658]
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