Authors:
Haruka Kamachi
1
;
Sae Ohkubo
2
;
Anna Yokokubo
2
;
1
and
Guillaume Lopez
2
;
1
Affiliations:
1
Graduate School of Science and Engineering, Aoyama Gakuin University, Sagamihara, Japan
;
2
Department of Integrated Information Technology, Aoyama Gakuin University, Sagamihara, Japan
Keyword(s):
Eating Activity Detection, Dietary Sound, Wearable Devices, Behavior Transformation.
Abstract:
Obesity may cause lifestyle diseases such as diabetes and high blood pressure. Eating slowly and chewing well are essential to prevent obesity. This research aims to improve the consciousness of dietary behavior based on eating habits by quantifying eating behavior. It proposes “ChewReminder,” a smartphone application software that detects eating activities in real-time under a natural meal environment and gives feedback based on detected activity. ChewReminder detects four activities: chewing, swallowing, talking, and other.The smartwatch gives feedback using vibration depend on chewing count per one bite which information was linked from the smartphone. Also, the total feedback about the meal was displayed on the smartphone after finishing the meal. The chewing count for 70% subjects and chewing pace for more than half subjects was improved with using ChewReminder by the result of total chewing count, average of chewing count per bite and chewing pace. ChewReminder is effective esp
ecially people who are aware of fast eating. Also, the result of long-term experiment indicated that feedback displayed on a smartphone was effective to improve consciousness of eating activity. Therefore, the result of both experiment shows that ChewReminder is a valid system to improve consciousness of eating activity especially chewing activity.
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