research-article

Recognition Algorithm for Sleep Postures using a Smart Fabric Pad with Multiple Pressure Sensors

Authors:

Sang Hun Lee,

Jung-uk Ahn,

Byung Mun LeeAuthors Info & Claims

ICCAE 2019: Proceedings of the 2019 11th International Conference on Computer and Automation Engineering

Pages 21 - 26

https://doi.org/10.1145/3313991.3314000

Published: 23 February 2019 Publication History

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Abstract

The existing studies suggest the following methods for measuring sleep postures: installing cameras and record the sleep postures then analyze the postures or measuring the change of the posture by attaching the sensor to the user's body. However, the installation of high-cost devices such as a camera or direct attachment of sensors on the subject's body present issues relating to the cost and convenience. As a solution, this paper develops a recognition algorithm for analyzing sleep postures using a smart pad with embedded fabric type pressure sensors. This algorithm is applied using a fabric-made smart pad with multiple pressure sensors. The sensors detect the distribution of the body pressure on the pad during sleeping, and the collected body pressure distribution data determines the sleep postures of the users. Further, this smart fabric pad does not require any additional analytical devices. This pad allows the users to monitor own sleep postures continuously. With the analyzed sleep posture data, the user can recognize one's typical sleep postures. In order to verify the effectiveness of the algorithm, this paper conducts an experiment to validate using the sleep posture data defined as nine categories. As a result, the algorithm had an average of 91.4% accuracy rate.

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Cited By

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Yoon JMoon ASon S(2024)Effective Posture Classification Using Statistically Significant Data From Flexible Pressure SensorsIEEE Journal on Flexible Electronics10.1109/JFLEX.2024.34001513:5(173-180)Online publication date: May-2024
https://doi.org/10.1109/JFLEX.2024.3400151
Wan QZhao HLi JXu P(2023)Human Sleeping Posture Recognition Based on Sleeping Pressure ImageIEEE Sensors Journal10.1109/JSEN.2022.322529023:4(4069-4077)Online publication date: 15-Feb-2023
https://doi.org/10.1109/JSEN.2022.3225290
Moon ASon SKim MChang SPark H(2023)Exploration Of Lossy Posture Classification Model Using In-Bed Flexible Pressure Sensors2023 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)10.1109/FLEPS57599.2023.10220219(1-4)Online publication date: 9-Jul-2023
https://doi.org/10.1109/FLEPS57599.2023.10220219
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Index Terms

Recognition Algorithm for Sleep Postures using a Smart Fabric Pad with Multiple Pressure Sensors
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
      1. Embedded software

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Published In

ICCAE 2019: Proceedings of the 2019 11th International Conference on Computer and Automation Engineering

February 2019

160 pages

ISBN:9781450362870

DOI:10.1145/3313991

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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The University of Western Australia, Department of Electronic Engineering, University of Western Australia
University of Melbourne: University of Melbourne
Macquarie University-Sydney

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 February 2019

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ICCAE 2019: 2019 11th International Conference on Computer and Automation Engineering

February 23 - 25, 2019

WN, Perth, Australia

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Yoon JMoon ASon S(2024)Effective Posture Classification Using Statistically Significant Data From Flexible Pressure SensorsIEEE Journal on Flexible Electronics10.1109/JFLEX.2024.34001513:5(173-180)Online publication date: May-2024
https://doi.org/10.1109/JFLEX.2024.3400151
Wan QZhao HLi JXu P(2023)Human Sleeping Posture Recognition Based on Sleeping Pressure ImageIEEE Sensors Journal10.1109/JSEN.2022.322529023:4(4069-4077)Online publication date: 15-Feb-2023
https://doi.org/10.1109/JSEN.2022.3225290
Moon ASon SKim MChang SPark H(2023)Exploration Of Lossy Posture Classification Model Using In-Bed Flexible Pressure Sensors2023 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)10.1109/FLEPS57599.2023.10220219(1-4)Online publication date: 9-Jul-2023
https://doi.org/10.1109/FLEPS57599.2023.10220219
Sikka MKumar SGarg S(2023)Smart Textiles for Biomedical Applications2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON)10.1109/ECTIDAMTNCON57770.2023.10139695(511-516)Online publication date: 22-Mar-2023
https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139695
Lim JJeong CLim JChung SKim GNoh KJeong H(2022)Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and ChallengesIEEE Access10.1109/ACCESS.2021.314007410(2063-2076)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2021.3140074
Ahn JLee SKang SHan HLee B(2020)In-Sleep Activity Detecting Algorithm for Sleepcare System2020 IEEE 14th International Conference on Semantic Computing (ICSC)10.1109/ICSC.2020.00070(350-353)Online publication date: Feb-2020
https://doi.org/10.1109/ICSC.2020.00070

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Measurements of lumbar spine kinematics in sitting postures using accelerometers: a preliminary study

Lumbar posture assessment with fabric strain sensors

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

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Measurements of lumbar spine kinematics in sitting postures using accelerometers: a preliminary study

Lumbar posture assessment with fabric strain sensors

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

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