title: VO2 estimation using 6-axis motion sensor with sports activity classification.
abstract: In this paper, we focus on oxygen consumption (VO2) estimation using 6-axis motion sensor (3-axis accelerometer and 3-axis gyroscope) for people playing sports with diverse intensities. The VO2 estimated with a small motion sensor can be used to calculate the energy expenditure, however, its accuracy depends on the intensities of various types of activities. In order to achieve high accuracy over a wide range of intensities, we employ an estimation framework that first classifies activities with a simple machine-learning based classification algorithm. We prepare different coefficients of linear regression model for different types of activities, which are determined with training data obtained by experiments. The best-suited model is used for each type of activity when VO2 is estimated. The accuracy of the employed framework depends on the trade-off between the degradation due to classification errors and improvement brought by applying separate, optimum model to VO2 estimation. Taking this trade-off into account, we evaluate the accuracy of the employed estimation framework by using a set of experimental data consisting of VO2 and motion data of people with a wide range of intensities of exercises, which were measured by a VO2 meter and motion sensor, respectively. Our numerical results show that the employed framework can improve the estimation accuracy in comparison to a reference method that uses a common regression model for all types of activities.
authors.forename: Takashi
authors.initials: T
authors.lastname: Nagata
authors.forename: Naoteru
authors.initials: N
authors.lastname: Nakamura
authors.forename: Masato
authors.initials: M
authors.lastname: Miyatake
authors.forename: Akira
authors.initials: A
authors.lastname: Yuuki
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Yomo
authors.forename: Takashi
authors.initials: T
authors.lastname: Kawabata
authors.forename: Shinsuke
authors.initials: S
authors.lastname: Hara
mesh_terms: D000465:Algorithms; D003663:Decision Trees; D004734:Energy Metabolism; D015444:Exercise; D006801:Humans; D009038:Motion; D010101:Oxygen Consumption / Q000502:physiology*; D013177:Sports