article

Human motion recognition using a wireless sensor-based wearable system

Authors:

John Paul Varkey,

Theodore A. WallsAuthors Info & Claims

Personal and Ubiquitous Computing, Volume 16, Issue 7

Pages 897 - 910

https://doi.org/10.1007/s00779-011-0455-4

Published: 01 October 2012 Publication History

Abstract

The future of human computer interaction systems lies in how intelligently these systems can take into account the user's context. Research on recognizing the daily activities of people has progressed steadily, but little focus has been devoted to recognizing jointly activities as well as movements in a specific activity. For many applications such as rehabilitation, sports medicine, geriatric care, and health/fitness monitoring the importance of combined recognition of activity and movements can drive health care outcomes. A novel algorithm is proposed that can be tuned to recognize on-the-fly range of activities and fine movements within a specific activity. Performance of the algorithm and a case study on obtaining optimal features from sensor and parameter values for the algorithm to detect fine motor movements are presented.

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Cited By

Wang HWang JZhang TKang YLi B(2023)Research on smart wearable clothing for the senior citizenProceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things10.1145/3603781.3603789(42-46)Online publication date: 26-May-2023
https://dl.acm.org/doi/10.1145/3603781.3603789
Thakur SPoddar PRoy R(2022)Real-time prediction of smoking activity using machine learning based multi-class classification modelMultimedia Tools and Applications10.1007/s11042-022-12349-681:10(14529-14551)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s11042-022-12349-6
Agac SShoaib MDurmaz Incel O(2020)Smoking recognition with smartwatch sensors in different postures and impact of user’s heightJournal of Ambient Intelligence and Smart Environments10.3233/AIS-20055812:3(239-261)Online publication date: 1-Jan-2020
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Index Terms

Human motion recognition using a wireless sensor-based wearable system
1. Applied computing
  1. Computers in other domains
    1. Personal computers and PC applications
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        Motion capture
  2. Computer graphics
    1. Animation
      1. Motion capture
      2. Motion processing

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Published In

cover image Personal and Ubiquitous Computing

Personal and Ubiquitous Computing Volume 16, Issue 7

October 2012

173 pages

ISSN:1617-4909

Issue’s Table of Contents

Copyright © Copyright © 2012 Springer-Verlag London Limited.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 October 2012

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Cited By

Wang HWang JZhang TKang YLi B(2023)Research on smart wearable clothing for the senior citizenProceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things10.1145/3603781.3603789(42-46)Online publication date: 26-May-2023
https://dl.acm.org/doi/10.1145/3603781.3603789
Thakur SPoddar PRoy R(2022)Real-time prediction of smoking activity using machine learning based multi-class classification modelMultimedia Tools and Applications10.1007/s11042-022-12349-681:10(14529-14551)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s11042-022-12349-6
Agac SShoaib MDurmaz Incel O(2020)Smoking recognition with smartwatch sensors in different postures and impact of user’s heightJournal of Ambient Intelligence and Smart Environments10.3233/AIS-20055812:3(239-261)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/AIS-200558
Lu JWang JZheng XKarmakar CRajasegarar S(2019)Detection of Smoking Events from Confounding Activities of Daily LivingProceedings of the Australasian Computer Science Week Multiconference10.1145/3290688.3290743(1-9)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3290688.3290743
Jansi RAmutha R(2019)Sparse representation based classification scheme for human activity recognition using smartphonesMultimedia Tools and Applications10.1007/s11042-018-6662-578:8(11027-11045)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11042-018-6662-5
Gao MZöllner J(2019)Sparse Contextual Task Learning and Classification to Assist Mobile Robot Teleoperation with Introspective EstimationJournal of Intelligent and Robotic Systems10.1007/s10846-017-0681-893:3-4(571-585)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s10846-017-0681-8
Casella EOrtolani MSilvestri SDas S(2019)Hierarchical syntactic models for human activity recognition through mobility tracesPersonal and Ubiquitous Computing10.1007/s00779-019-01319-924:4(451-464)Online publication date: 25-Nov-2019
https://dl.acm.org/doi/10.1007/s00779-019-01319-9
Thakur SRoy RRanu SGanguly NRamakrishnan RSarawagi SRoy S(2018)A mobile app based smoking cessation assistance using automated detection of smoking activityProceedings of the ACM India Joint International Conference on Data Science and Management of Data10.1145/3152494.3167989(352-355)Online publication date: 11-Jan-2018
https://dl.acm.org/doi/10.1145/3152494.3167989
Brena RGarcia-Ceja E(2017)A crowdsourcing approach for personalization in human activities recognitionIntelligent Data Analysis10.3233/IDA-17088421:3(721-738)Online publication date: 1-Jan-2017
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Shinmoto Torres RShi Qvan den Hengel ARanasinghe D(2017)A hierarchical model for recognizing alarming states in a batteryless sensor alarm intervention for preventing falls in older peoplePervasive and Mobile Computing10.1016/j.pmcj.2017.04.00240:C(1-16)Online publication date: 1-Sep-2017
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