TY  - CONF
ID  - Amft2007-P_BIBM
T1  - Automatic Identification of Temporal Sequences in Chewing Sounds
A1  - Amft, Oliver
A1  - Kusserow, Martin
A1  - Tröster, Gerhard
ED  - Hu, Tony
ED  - Mandoiu, Ion
ED  - Obradovic, Zoran
TI  - BIBM 2007: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine
Y1  - 2007
SP  - 194
EP  - 201
PB  - IEEE Press
AD  - San Jose, CA, USA
M2  - doi: 10.1109/bibm.2007.18
N2  - Chewing is an essential part of food intake. The analysis and detection of food patterns is an important component of an automatic dietary monitoring system. However chewing is a time-variable process depending	on food properties. We present an automated methodology to extract sub-sequences of similar chews from chewing sound recordings. The approach is based on a chew-accurate segmentation of the sound signal, a multi-objective evolutionary search for temporal partitions in	the sequence using NSGA-II and a validation of the best solution by classification. We evaluate the method on chewing sound recordings from a four participant study, eating foods with different rheological properties. The proposed methodology allows to determine the most	appropriate partitioning of the sequences and extract relevant sound	features at the same time. Potato chips and chocolate showed a two-phase	structure, for lasagne and apples a single-phase structure was derived. The results led to the hypothesis that a sequential structure can be found in chewing sounds from brittle or rigid foods.
M1  - owner={oam}
M1  - 
timestamp={2007/10/09}
ER  -