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Estimating heart rate variation during walking with smartphone

Authors:

Teruhiro Mizumoto,

Keiichi YasumotoAuthors Info & Claims

UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

Pages 245 - 254

https://doi.org/10.1145/2493432.2493491

Published: 08 September 2013 Publication History

Abstract

Aiming to realize the application which supports users to enjoy walking with an appropriate physical load, we propose a method to estimate physical load and its variation during walking only with available functions of a smartphone. Since physical load has a linear relationship with heart rate, our purpose is to estimate heart rate with a smartphone. To this end, we build heart rate prediction models which predict heart rate variation from walking data including acceleration and walking speed by machine learning. In order to track unexpected change of physical load, we focus attention on oxygen uptake which has a similar property to heart rate and devise a novel technique to estimate the oxygen uptake from acceleration and GPS data so that it is used as an input of the model. Moreover, to adapt to difference of heart rate variation among individuals, we devise techniques to optimize parameters for each profile-based category of users and to normalize heart rate to absorb individual difference. We applied the proposed method to actual walking data on various routes by different persons and confirmed that the method estimates heart rate variation with the mean error of less than 7 beat per minute.

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Cited By

Vassilakis CPolychronaki MMargaritis DKogias DLeligou H(2024)OPTORER: A Dynamic Routing and Touring Service for Indoors and Outdoor ToursSensors10.3390/s2408243124:8(2431)Online publication date: 10-Apr-2024
https://doi.org/10.3390/s24082431
Vassilakis CPolychronaki MKogias DLeligou E(2024)OPTORER PPE: A Novel Dynamic Routing and Exploration Service in Outdoor and Indoor Areas of Touristic and Cultural Interest in the Broad Area of AtticaRecent Advancements in Tourism Business, Technology and Social Sciences10.1007/978-3-031-54338-8_6(83-93)Online publication date: 29-May-2024
https://doi.org/10.1007/978-3-031-54338-8_6
Pourbemany JZhu Y(2023)Cross Body Signal Pairing (CBSP): A Key Generation Protocol for Pairing Wearable Devices with Cardiac and Respiratory SensorsProceedings of the 39th Annual Computer Security Applications Conference10.1145/3627106.3627185(424-438)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3627106.3627185
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Index Terms

Estimating heart rate variation during walking with smartphone
1. Applied computing
  1. Computers in other domains
    1. Personal computers and PC applications

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Published In

cover image ACM Conferences

UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing

September 2013

846 pages

ISBN:9781450317702

DOI:10.1145/2493432

General Chairs:
Friedemann Mattern
ETH Zurich, CH
,
Silvia Santini
TU Darmstadt, DE
,
Program Chairs:
John F. Canny
UC Berkeley, US
,
Marc Langheinrich
Università della Svizzera italiana, CH
,
Jun Rekimoto
University of Tokyo, JP

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
University of Florida: University of Florida
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 September 2013

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UbiComp '13

Sponsor:

SIGMOBILE
University of Florida
SIGCHI

UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 8 - 12, 2013

Zurich, Switzerland

Acceptance Rates

UbiComp '13 Paper Acceptance Rate 92 of 394 submissions, 23%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Vassilakis CPolychronaki MMargaritis DKogias DLeligou H(2024)OPTORER: A Dynamic Routing and Touring Service for Indoors and Outdoor ToursSensors10.3390/s2408243124:8(2431)Online publication date: 10-Apr-2024
https://doi.org/10.3390/s24082431
Vassilakis CPolychronaki MKogias DLeligou E(2024)OPTORER PPE: A Novel Dynamic Routing and Exploration Service in Outdoor and Indoor Areas of Touristic and Cultural Interest in the Broad Area of AtticaRecent Advancements in Tourism Business, Technology and Social Sciences10.1007/978-3-031-54338-8_6(83-93)Online publication date: 29-May-2024
https://doi.org/10.1007/978-3-031-54338-8_6
Pourbemany JZhu Y(2023)Cross Body Signal Pairing (CBSP): A Key Generation Protocol for Pairing Wearable Devices with Cardiac and Respiratory SensorsProceedings of the 39th Annual Computer Security Applications Conference10.1145/3627106.3627185(424-438)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3627106.3627185
Polychronaki MVassilakis CKogias DLeligkou HVagiannis I(2022)OPTORER PPEProceedings of the 26th Pan-Hellenic Conference on Informatics10.1145/3575879.3575987(164-168)Online publication date: 25-Nov-2022
https://dl.acm.org/doi/10.1145/3575879.3575987
Maenaka SSuwa HArakawa YYasumoto K(2021)Heart Rate Prediction for Easy Walking Route PlanningSICE Journal of Control, Measurement, and System Integration10.9746/jcmsi.11.28411:4(284-291)Online publication date: 18-Jan-2021
https://doi.org/10.9746/jcmsi.11.284
Kawamura KAe KTomita K(2021)Prediction of the oxygen uptake patterns during an incremental exercise test using long short - term memory in electromyography長・短期記憶ネットワークを用いた表面筋電図による酸素摂取量の経時的な予測Japanese Journal of Physical Fitness and Sports Medicine10.7600/jspfsm.70.35570:6(355-362)Online publication date: 1-Dec-2021
https://doi.org/10.7600/jspfsm.70.355
Shabaan MArshad KYaqub MJinchao FZia MBoja GIftikhar MGhani UAmbati LMunir R(2020)Survey: smartphone-based assessment of cardiovascular diseases using ECG and PPG analysisBMC Medical Informatics and Decision Making10.1186/s12911-020-01199-720:1Online publication date: 29-Jul-2020
https://doi.org/10.1186/s12911-020-01199-7
Otsubo ASuwa HArakawa YYasumoto K(2020)Walking Pace Induction Application Based on the BPM and RhythmValue of MusicWireless Mobile Communication and Healthcare10.1007/978-3-030-49289-2_5(60-74)Online publication date: 28-May-2020
https://doi.org/10.1007/978-3-030-49289-2_5
Otsubo ASuwa HArakawa YYasumoto K(2019)BeatSync: Walking Pace Control Through Beat Synchronization between Music and Walking2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2019.8730833(367-369)Online publication date: Mar-2019
https://doi.org/10.1109/PERCOMW.2019.8730833
Zhang HWen BLiu JZeng Y(2019)The Prediction and Error Correction of Physiological Sign During Exercise Using Bayesian Combined Predictor and Naive Bayesian ClassifierIEEE Systems Journal10.1109/JSYST.2019.290285813:4(4410-4420)Online publication date: Dec-2019
https://doi.org/10.1109/JSYST.2019.2902858
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