Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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Development of Postural Correction App Service with Body Transformation and Sitting Pressure Measurement

체위 변환과 좌압 측정을 통한 자세교정 앱 서비스의 개발

  • Received : 2022.12.19
  • Accepted : 2023.01.10
  • Published : 2023.03.31
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Abstract

In general, maintaining an incorrect sitting posture for a long time is widely known to adversely affect the spine. Recently, several researchers have been interested in the causal relationship between incorrect sitting posture and spinal diseases, and have been studying methods to precisely measure changes in sitting or standing posture to prevent spinal diseases. In previous studies, we have developed a sensor device capable of measuring real-time posture change, applied a momentum calculation algorithm to improve the accuracy of real-time posture change measurement, and verified the accuracy of the postural change measurement sensor. In this study, we developed a posture measurement and analysis device that considers changes in the center of body pressure through the developed sitting pressure measurement, and it confirmed the sensor as an auxiliary tool to increase the accuracy of posture correction training with improving the user's visual feedback.

일반적으로 잘못된 앉은 자세를 장시간 유지하는 것은 척추에 나쁜 영향을 미치는 것으로 널리 알려져 있다. 최근 여러 연구자들이 잘못된 앉은 자세와 척추질환의 인과관계에 관심을 두고 있으며, 척추질환 예방을 위해 앉거나 서는 자세의 변화를 정밀하게 측정할 수 있는 방법을 연구해왔다. 우리는 과거 연구에서 실시간 체위 변환 측정이 가능한 센서 디바이스를 개발하고 운동량 계산 알고리즘을 적용하여 실시간 자세 전환 측정 정확도를 향상시켰으며, 체위 변환 측정 센서의 정확도를 검증하였다. 본 연구에서는 좌압 측정을 통해 체중심의 변화를 고려한 자세 측정 및 분석 장치를 개발하였으며, 개발된 센서는 사용자의 시각적 피드백을 개선하여 자세 교정 훈련 정확도를 높이는 보조 도구로의 활용 가능성을 확인하였다.

Keywords

Acknowledgement

이 연구는 2020년도 산업통상자원부 및 산업기술평가관리원(KEIT) 연구비 지원에 의한 연구임 [과제번호 : 20010234]

References

  1. M. S. Kim, J. Y. Seo, Y. H. Noh, D. U. Jeong, "Implementation of Cushion Type Posture Discrimination System Using FSR Sensor Array", Journal of the Institute of Convergence Signal Processing, vol.20, no.2, pp.99-104, 2019.
  2. M. K. Song, J. Y. Kong, J. H. Park, C. H. Shin, H. S. Kang, "Effects of Sitting Habits and Physical Activity Levels on Spine and Pelvis Deformations in School Children", Journal of Exercise Science, vol.26, no.1, pp.32-39, 2017. https://doi.org/10.15857/ksep.2017.26.1.32
  3. S. Y. Ma, S. P. Hong, H. M. Shim, J. W. Kwon, S. M. Lee, "A study on Sitting Posture Recognition using Machine Learning", The Transactions of the Korean Institute of Electrical Engineers, Vo.65, No.9, pp.1557-1563, 2016 https://doi.org/10.5370/KIEE.2016.65.9.1557
  4. S. J. Moon, Y. S. Park, "The Design and Implementation of the Position Calibration System Using Sensor on u-WBAN", Journal of Korean Institute of The Intelligent System, Vo.20, No.2, pp.304-310, 2010 https://doi.org/10.5391/JKIIS.2010.20.2.304
  5. Y. J. Cho, K. S. Park, "Design and Development of the Multiple Kinect Sensor-based Exercise Pose Estimation System", Journal of The Korea Institute of Information and Communication Engineering, Vo.21, No.3, pp.558-567, 2017
  6. Y. S. An, K. S. Kim, C. G. Song, "Posture guidance system using 3-axis accelerometer for scoliosis patient", Proceeding of the IEEK Conference, pp.396-398, 2009
  7. J. H. Choi, J. H. Park, M. H. Kang, J. Y. Seo, S. C. Kim, "Evaluation of measuring accuracy of body position sensor device for posture correction", Journal of the Institute of Convergence Signal Processing, vol.22, no.3, pp.128-133, 2021.
  8. J. H. Choi, M. H. Kang, Y. K. Sung, J. H. Park, J. Y. Seo, S. H. Noh, J. M. Park, "Development of a body position sensor device with real-time movement measurement", in Proc. of Conferecne of Korea Institute of Convergence Signal Processing, pp.1-2, June, 2022
  9. K. Bakrania, T. Yates, A. V. Rowlands, D. W. Esliger, S. Bunnewell, J. Sanders, M. Davies, K. Khunti, C. L. Edwardson, "Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Aplitude Deviation (MAD) Approaches", PLoS One, 11(10):e0164045, 2016
  10. H. Vaha-Ypya, T. Vasankari, P. Husu, A. Manttari, T. Vuorimaa, J. Suni, H. Sievanen, "Validation of Cut-Points for Evaluating the Intensity of Physical Activity with Accelerometry-Based mean Amplitude Deviation (MAD)", PLos One, 10(8):e0134813, 2015
  11. E. K. Allseits, V. Aawal, A. Prasad, C. Bennett, K. J. Kim, "Characterizing the Impact of Sampling Rate and Filter Design on the Morphology of Lower Limb Angular Velocities", IEEE Sensors Journal, Vol.19, Iss.11, pp.4115-4122, 2019  https://doi.org/10.1109/JSEN.2019.2899724