title: Physical activity group classification algorithm using triaxial acceleration and heart rate.
abstract: As described in this paper, a physical activity classification algorithm is proposed for energy expenditure estimation. The proposed algorithm can improve the classification accuracy using both the triaxial acceleration and heart rate. The optimal classification also contributes to improvement of the accuracy of the energy expenditures estimation. The proposed algorithm employs three indices: the heart rate reserve (%HRreserve), the filtered triaxial acceleration, and the ratio of filtered and unfiltered acceleration. The percentage HRreserve is calculated using the heart rate at rest condition and the maximum heart rate, which is calculated using Karvonen Formula. Using these three indices, a decision tree is constructed to classify physical activities into five classes: sedentary, household, moderate (excluding locomotive), locomotive, and vigorous. Evaluation results show that the average classification accuracy for 21 activities is 91%.
authors.forename: Motofumi
authors.initials: M
authors.lastname: Nakanishi
authors.forename: Shintaro
authors.initials: S
authors.lastname: Izumi
authors.forename: Sho
authors.initials: S
authors.lastname: Nagayoshi
authors.forename: Hironori
authors.initials: H
authors.lastname: Sato
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Kawaguchi
authors.forename: Masahiko
authors.initials: M
authors.lastname: Yoshimoto
authors.forename: Takafumi
authors.initials: T
authors.lastname: Ando
authors.forename: Satoshi
authors.initials: S
authors.lastname: Nakae
authors.forename: Chiyoko
authors.initials: C
authors.lastname: Usui
authors.forename: Tomoko
authors.initials: T
authors.lastname: Aoyama
authors.forename: Shigeho
authors.initials: S
authors.lastname: Tanaka
mesh_terms: D000054:Acceleration; D000465:Algorithms; D004734:Energy Metabolism; D015444:Exercise; D006339:Heart Rate; D006801:Humans; D009043:Motor Activity