Physical activity group classification algorithm using triaxial acceleration and heart rate

Motofumi Nakanishi, Shintaro Izumi, Sho Nagayoshi, Hironori Sato, Hiroshi Kawaguchi, Masahiko Yoshimoto, Takafumi Ando, Satoshi Nakae, Chiyoko Usui, Tomoko Aoyama, Shigeho Tanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

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%.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages510-513
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 2015 Nov 4
Externally publishedYes
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 2015 Aug 252015 Aug 29

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

Fingerprint

Heart Rate
Locomotives
Energy Metabolism
Decision Trees
Decision trees

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Nakanishi, M., Izumi, S., Nagayoshi, S., Sato, H., Kawaguchi, H., Yoshimoto, M., ... Tanaka, S. (2015). Physical activity group classification algorithm using triaxial acceleration and heart rate. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 (pp. 510-513). [7318411] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7318411

Physical activity group classification algorithm using triaxial acceleration and heart rate. / Nakanishi, Motofumi; Izumi, Shintaro; Nagayoshi, Sho; Sato, Hironori; Kawaguchi, Hiroshi; Yoshimoto, Masahiko; Ando, Takafumi; Nakae, Satoshi; Usui, Chiyoko; Aoyama, Tomoko; Tanaka, Shigeho.

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 510-513 7318411 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nakanishi, M, Izumi, S, Nagayoshi, S, Sato, H, Kawaguchi, H, Yoshimoto, M, Ando, T, Nakae, S, Usui, C, Aoyama, T & Tanaka, S 2015, Physical activity group classification algorithm using triaxial acceleration and heart rate. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015., 7318411, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2015-November, Institute of Electrical and Electronics Engineers Inc., pp. 510-513, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 15/8/25. https://doi.org/10.1109/EMBC.2015.7318411
Nakanishi M, Izumi S, Nagayoshi S, Sato H, Kawaguchi H, Yoshimoto M et al. Physical activity group classification algorithm using triaxial acceleration and heart rate. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 510-513. 7318411. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2015.7318411
Nakanishi, Motofumi ; Izumi, Shintaro ; Nagayoshi, Sho ; Sato, Hironori ; Kawaguchi, Hiroshi ; Yoshimoto, Masahiko ; Ando, Takafumi ; Nakae, Satoshi ; Usui, Chiyoko ; Aoyama, Tomoko ; Tanaka, Shigeho. / Physical activity group classification algorithm using triaxial acceleration and heart rate. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 510-513 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
@inproceedings{c8d3d145f58d4966a55099ae3c62fc8a,
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{\%}.",
author = "Motofumi Nakanishi and Shintaro Izumi and Sho Nagayoshi and Hironori Sato and Hiroshi Kawaguchi and Masahiko Yoshimoto and Takafumi Ando and Satoshi Nakae and Chiyoko Usui and Tomoko Aoyama and Shigeho Tanaka",
year = "2015",
month = "11",
day = "4",
doi = "10.1109/EMBC.2015.7318411",
language = "English",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "510--513",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",

}

TY - GEN

T1 - Physical activity group classification algorithm using triaxial acceleration and heart rate

AU - Nakanishi, Motofumi

AU - Izumi, Shintaro

AU - Nagayoshi, Sho

AU - Sato, Hironori

AU - Kawaguchi, Hiroshi

AU - Yoshimoto, Masahiko

AU - Ando, Takafumi

AU - Nakae, Satoshi

AU - Usui, Chiyoko

AU - Aoyama, Tomoko

AU - Tanaka, Shigeho

PY - 2015/11/4

Y1 - 2015/11/4

N2 - 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%.

AB - 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%.

UR - http://www.scopus.com/inward/record.url?scp=84953218694&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84953218694&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2015.7318411

DO - 10.1109/EMBC.2015.7318411

M3 - Conference contribution

C2 - 26736311

AN - SCOPUS:84953218694

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 510

EP - 513

BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -