Bootstrap aggregating decision tree for motion classification based on a textile-integrated and wearable sensorarray

Daniel Teichmann,Andrea A Kuhn,Jerome Foussier,Saim Kim,Tobias Wartzek,Boudewijn Venema,Christian Brendle,Mark Ulbrich,Anake Pomprapa,Marian Walter,Steffen Leonhardt

Point-of-Care Healthcare Technologies（2013）

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摘要

In this work a system for instant classification of motion patterns is presented. It is based on a non-contact magnetic induction monitoring device, which is textile-integrated, wearable, and able to measure pulse and respiratory activity. The proposed classificator is based on a decision tree algorithm generated by bootstrap aggregating. Its accurate classification performance is validated with the help of a data set comprising five exemplary motion patterns. Furthermore, the dependance of the misclassification error on the input sample length is investigated.

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关键词

array signal processing,biomedical equipment,decision trees,electroencephalography,electromagnetic induction,medical signal processing,patient monitoring,pattern classification,pneumodynamics,sensor arrays,signal classification,statistical analysis,eeg,bootstrap aggregating decision tree,input sample length,motion classification,motion pattern classification,noncontact magnetic induction monitoring device,pulse activity,respiratory activity,textile-integrated sensor array,wearable sensor array

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