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Limited By:	Subject = support vector machines;

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A Data-Driven Modelling Approach for Large Scale Demand Profiling of Residential Buildings (2019)

Tardioli, Giovani; Kerrigan, Ruth; Oates, Mike; O'Donnell, James; Finn, Donal

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A machine learning approach for gesture recognition with a lensless smart sensor system (2018)

Normani, Niccolo; Urru, Andrea; Abraham, Lizy; Walsh, Michael; Tedesco, Salvatore; Cene...

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A Regression Study of Salary Determinants in Indian Job Markets for Entry Level Engineering Graduates (2016)

Singh, Rajveer

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A survey of recent trends in one class classification (2010)

Khan, Shehroz S.; Madden, Michael G.

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An evolutionary approach to automatic kernel construction (2009)

Madden, Michael G.; Howley, Tom

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Analysis of the Effects of Unexpected Outliers in the Classification of Spectroscopy Data (2009)

Glavin, Frank G.; Madden, Michael G.

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Benchmarking Classification Models for Emotion Recognition in Natural Speech: a Multi-Corporal Study (2011)

Tarasov, Alexey; Delany, Sarah Jane

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Brain haemorrhage detection through SVM classification of electrical impedance tomography measurements (2019)

McDermott, Barry; Dunne, Eoghan; O’Halloran, Martin; Porter, Emily; Santorelli, Adam

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Classification of a Target Analyte in Solid Mixtures using Principal Component Analysis, Support Vector Machines and Raman Spectroscopy (2009)

Madden, Michael G.; Leger, Marc N.; Ryder, Alan G.; Howley, Tom; O Connell, Marie-Louise

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Competitive Evaluation of Data Mining Algorithms for Use in Cassification of Leukocyte Subtypes with Raman Microspectroscopy (2014)

Maguire, Adrian; Vega-Carrascal, I.; Bryant, Jane; White, Lisa; Howe, Orla; Lyng, Fiona...

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Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process (2017)

Kelly, Robert

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Detecting freezing of gait with a tri-axial accelerometer in parkinson’s disease patients (2018)

Ahlrichs, Claas; Samà, Albert; Lawo, Michael; Cabestany, Joan; Rodríguez-Martín, Daniel...

Detecting freezing of gait with a tri-axial accelerometer in parkinson’s disease patients (2018)

Ahlrichs, Claas; Samà, Albert; Lawo, Michael; Cabestany, Joan; Rodríguez-Martín, Daniel; Pérez-López, Carlos; Sweeney, Dean; Quinlan, Leo R.; Laighin, Gearòid Ò; Counihan, Timothy; Browne, Patrick; Hadas, Lewy; Vainstein, Gabriel; Costa, Alberto; Annicchiarico, Roberta; Alcaine, Sheila; Mestre, Berta; Quispe, Paola; Bayes, Àngels; Rodríguez-Molinero, Alejandro

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...