Title :
Bootstrap aggregating decision tree for motion classification based on a textile-integrated and wearable sensorarray
Author :
Teichmann, Daniel ; Kuhn, A. ; Foussier, Jerome ; Kim, Sungho ; Wartzek, Tobias ; Venema, B. ; Brendle, Christian ; Ulbrich, Mark ; Pomprapa, Anake ; Walter, Michael ; Leonhardt, Steffen
Author_Institution :
Med. Inf. Technol., RWTH Aachen Univ., Aachen, Germany
Abstract :
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.
Keywords :
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; data set; input sample length; motion classification; motion pattern classification; noncontact magnetic induction monitoring device; pulse activity; respiratory activity; textile-integrated sensor array; wearable sensor array; Biomedical monitoring; Decision trees; Discrete wavelet transforms; Legged locomotion; Monitoring; Training data;
Conference_Titel :
Point-of-Care Healthcare Technologies (PHT), 2013 IEEE
Conference_Location :
Bangalore
Print_ISBN :
978-1-4673-2765-7
Electronic_ISBN :
978-1-4673-2766-4
DOI :
10.1109/PHT.2013.6461277
