Eating habits monitoring using wireless wearable in-ear microphone

To realize ubiquitous eating habits monitoring, we proposed the use of chewing sound sensed by an in-ear placed wireless wearable microphone. A prototype of wireless wearable in-ear microphone was developed by utilizing a common Bluetooth headset. We proposed robust chewing number counting algorithm which consists of two recognition stages: ldquochew-likerdquo signal detection and chewing verification stage. As a result, average chewing number counting error rate of 1.93% was achieved. Lastly, chewing sound mapping was proposed to provide an additional intuitive feedback for users to be able to infer the eating habits in their daily life context.

[1]  Vesa T. Peltonen,et al.  Audio-based context recognition , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[2]  Tomi Kinnunen,et al.  Real-time speaker identification and verification , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  Yoshiaki Tadokoro,et al.  No Contact-type Chewing Number Counting Equipment Using Infrared Sensor , 2002 .

[4]  K. Kohyama,et al.  Influence of age and dental status on chewing behaviour studied by EMG recordings during consumption of various food samples. , 2003, Gerodontology.