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Currently, the population of people with disabilities who need assistance is increasing year by year. Among them, the number of upper limb disabled persons is about 690,000. Those who have disabilities in their upper limbs have complication in their daily life and it is difficult to eat on their own. Meanwhile, the number of caregivers is short for those who need assistance. For this reason, there is a situation that the work burden per assistant increases. In order to solve this situation, development of various meal assistance robots is advancing. With the development of a meal assistance robot, people with obstacles in upper limbs can now eat on their own. For this reason, it is conceivable that there is no need for a caregiver to support their meal, and there are few circumstances where a caregiver is present next to a person who needs assistance. Therefore, in this research, I will construct a system to resolve the situation of people who need assistance. This system, use the chewing movement of a person who needs assistance and a constructed server so that caregivers can check the situation of people who need help. Then, aimed to verify and confirm the accuracy of the chewing detection method.

Classification of Mouth Movement for Meal Support Robot