Detection of chewing motion in the elderly using a glasses mounted accelerometer in a real-life environment.
Annu Int Conf IEEE Eng Med Biol Soc
; 2017: 4521-4524, 2017 Jul.
Article
em En
| MEDLINE
| ID: mdl-29060902
ABSTRACT
This paper describes a method of detecting an elderly person's chewing motion using a glasses mounted accelerometer. A real-life dataset was collected from 13 elderly adults, aged 65 or older, during meal times in a care facility. A supervised classifier is used to automatically distinguish between epochs of chewing and non-chewing activity. Results are compared to a lab dataset of 5 young to middle-aged adults captured in previous work. K-Nearest Neighbor, Random Forest and Support Vector Machine classifiers are evaluated. All are able to achieve similar performance, with the Support Vector Machine performing the best with an F1-score of 0.73.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Mastigação
Tipo de estudo:
Diagnostic_studies
Limite:
Aged
/
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Ano de publicação:
2017
Tipo de documento:
Article