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3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome

Yıl 2016, Cilt: 5 , 59 - 70, 07.11.2016

Öz

In this study, a data acquisition system that monitoring and recording of the position data of the patients is designed. For this work, a circuit with microcontroller is designed and an acceleration sensor which has ability to define position by using 3-axis cartesian coordinate systems is used. The data obtained from the sensor are recorded on a SD card and transferred to a computer via USB in real time. The data transferred to the computer can also be saved in a text file in order to use in MATLAB program to investigate both time and frequency analyzes.  These data which are received to the computer, are grouped to the axis and plotted the position by the computer interface program which is developed at MATLAB-Gui programming language. Patient position can be detected as 3D real time. This ability gives us advantage to detect of patient’s lying posture for positional sleep apnea study. It is very important that developed system for infants, elderly and disabled individuals with positional sleep apnea disease especially, can easily use to the detection of the position of the lying. They can determine the most ideal sleeping position for themselves. So, the developed system is portable and it can be used for a number of other study and research.

Kaynakça

  • A.Mincholéa, L.Sörnmob, P.Laguna, Detection of body position changes from the ECG using a Laplaciannoise model, Biomedical Signal Processing and Control 14, pp:189–196, 2014.
  • M. Aström, j. Garcia, P. Laguna, O. Pahlm, detection of body position changes using the surface electrocardiogram, Med. Bio. Eng. Comput., 41, 164-171, 2003.
  • Jing Jia, Gongming Xu, Xi Pei, at al, Accuracy and efficiency of an infrared based positioning and tracking system for patient set-up and monitoring in image guided radiotherapy, Infrared Physics & Technology 69, pp:26–31, 2015.
  • http://uykubozuklugu.uludag.edu.tr/ltrt014.htm, ( 02.09.2015, 22:20)
  • H.Sümbül, A. H.Yüzer, İvmealgılayıcı Kullanarak Farklı Pozisyonlara Göre Soluma Sinyallerinin Elde Edilmesi, SİU2015, Sinyal İşleme Ve İletişim Uygulamaları Kurultayı, 16 - 19 May 2015,Processing v. 1, pp:279-282, İnönü Üniversitesi, Malatya, TÜRKİYE.
  • http://www.memorial.com.tr/rehberler/saglik_rehberi/horlama-nedir/, (02.12.2015, 12:25)
  • http://www.medikalakademi.com.tr/bebeklerde-uyku-pozisyonu-nasil-olmali/, (21.12.2014, 20:05)
  • J. Pino Esteban, A. Mor´an Alejandra, Astrid D¨orner De la Paz and Pablo Aqueveque, Validation of Non-Invasive Monitoring Device to Evaluate Sleep Quality, Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:7974-7. doi: 10.1109/EMBC.2015.7320242.
  • H. Enamul, F. Dickerson Robert, A. Stankovic John, Monitoring body positions and movements during sleep using WISPs, Proceeding WH '10 Wireless Health 2010 Pages 44-53 ACM New York, NY, USA, doi:10.1145/1921081.1921088
  • M. Ermes, J. Pärkka, J. Mantyjarvi, I. Korhonen, Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions, IEEE Trans Inf Technol Biomed. 2008 Jan;12(1):20-6. doi: 10.1109/TITB.2007.899496.
  • A. Louis, L.Benny, K. Rachel, Y. Guang-Zhong, Sensor Placement for Activity Detection using Wearable Accelerometers, Body Sensor Networks (BSN), 2010 International Conference on, DOI: 10.1109/BSN.2010.23
  • G.K. Prisk, S. Verhaeghe, D. Padeken, H. Hamacher, M. Paiva., Three-dimensional ballistocardiography and respiratory motion in sustained microgravity, Aviat Space Environ Med. 2001 Dec;72(12):1067-74, PMID:11763106
  • Min Ju Kim, Gha-Hyun Lee, Chun-Sik Kim, Woo Sung Kim, Yoo-Sam Chung, Seockhoon Chung, Sang-Ahm Lee, Comparison of three actigraphic algorithms used to evaluate sleep in patients with obstructive sleep apnea, Sleep Breath (2013) 17:297–304, DOI 10.1007/s11325-012-0689-z.
  • P. Jéssica Fabia, S.S. Rogerio, F. Paula Martins de Oliveira, S.Denis Eduardo, B. Sergio Tufik, L., Is portable monitoring for diagnosing obstructive sleep apnea syndrome suitable in elderly population?, Sleep Breath (2013) 17:679–686, DOI 10.1007/s11325-012-0742-y
  • https://www.arduino.cc/, son erişim: 21.12.2015
  • https://www.mems-exchange.org/MEMS/what-is.html
  • B. Sebastian, S. Axel, B. Stephanus, Three-Axes Monolithic Silicon Low-g Accelerometer, journal of microelectromechanical systems, vol. 9, no. 4, december 2000, pp:551-556, doi: 1057-7157(00)10873-X.
  • A. D. Reis Filho Carlos, P. Pessatti Mudo, Jolo P. C. Cajueiro and Paulo A. Dal Fabbro, Elements for a Monolithically Integrated Rotation Imbalance Detector, Industrial Electronics, 2003. ISIE '03. 2003 IEEE International Symposium on, pp:897-900, doi: 10.1109/ISIE.2003.1267940.
  • MEMS by ADI Innovative technology to measure movement and sound, The World Leader in High-Performance Signal Processing Solutions, Analog Device.
  • Y. Zhenhe, L.Ying, Z.Qiaoxiang, L.Xue, A Falling Detection System with wireless sensor for the Elderly People Based on Ergnomics, International Journal of Smart Home Vol.8, No.1 (2014), pp.187-196, doi:10.14257/ijsh.2014.8.1.20.
  • S.Jivko, S.Vladimir, S.Ritika, S.Alexander, Vibrotactile Recognition and Categorization of Surfaces by a Humanoid Robot, IEEE Transactions On Robotics, pp:1-10. 2011, doi: 10.1109/TRO.2011.2127130.
  • K.Adil Mehmood, L.Young-Koo, Y. Lee Sungyoung, Tae-Seong Kim, A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer, IEEE transactions on information technology in biomedicine, vol. 14, no. 5, september 2010, pp:1166-1172, doi: 10.1109/TITB.2010.2051955.
  • M. Nolan, B. Madden, E. Burke, Accelerometer based measurement for the mapping of neck surface vibrations during vocalized speech., Conf Proc IEEE Eng Med Biol Soc. 2009;2009:4453-6. doi: 10.1109/IEMBS.2009.5333817.
  • Y. Yurish Sergey, Practical Circuits and Interface Techniques for MEMS Accelerometers with Quasi-Digital Output, Sensors & Transducers Magazine (S&T e-Digest), Vol.58, Issue 8, August 2005, pp.352-359, ISSN:1726-5479.
  • H. Sümbül, A. H. Yüzer, Measuring of Diaphragm Movements by using iMEMS Acceleration Sensor, International Conference on Electrical and Electronics Engineering, ELECO 2015, Processing, pp:166-170, Bursa, TÜRKİYE.
  • MPU-6000/MPU-6050 Product Specification, 2012 http://www.seeedstudio.com/wiki/images/b/b1/MPU6050.pdf (son erişim: 20.12.2015 23:41)
  • J. Fisher Christopher, Using an Accelerometer for Inclination Sensing, AN-1057 Application Note, Analog Device, 2010.
  • R.David Barbosa, L. Rojas Ojeda Juan, F. Crespo Foix Luis, M.Daniel Sánchez, A. Fernández Miguel, Mapping the Human Body for Vibrations using an Accelerometer, Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp: 1671-1674, 2007.
  • W.Woranat, Q. Le Trung, T.S. Bukkapatnam Satish, Wireless Wearable Multi-Sensory System for Monitoring of Sleep Apnea and Other Cardiorespiratory Disorders, 2013 IEEE International Conference on Automation Science, and Engineering (CASE), pp: 605-610, doi: 978-1-4799-1515-6/13/$31.00 ©2013 IEEE
  • G. Illapha Cuba, G. Bonomi Alberto, Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life, IEEE transactions on biomedical engineering, vol. 58, no. 9, pp: 2656-2663, 2011, doi: 10.1109/TBME.2011.2160723.
  • Wu Dan, Wang Lei, Zhang YT, Huang BY, Wang Bo, Lin SJ, Xu XW, A wearable respiration monitoring system based on digital respiratory inductive plethysmography, Conf Proc IEEE Eng Med Biol Soc. 2009, pp: 4844-7. doi: 10.1109/IEMBS.2009.5332665.
  • D. Hung Phan., S. Bonnet, R. Guillemaud, E. Castelli, Pham. Thi. N. Yen, Estimation of respiratory waveform and heart rate using an accelerometer, Conf Proc IEEE Eng Med Biol Soc., 2008, pp:4916-9. doi: 10.1109/IEMBS.2008.4650316.
  • M. Chan Alexander, F.Nima, N.Ravi, Ambulatory respiratory rate detection using ECG and a triaxial accelerometer, Conf Proc IEEE Eng Med Biol Soc.,2013, pp:4058-61. doi: 10.1109/EMBC.2013.6610436.
  • M. Chan Alexander, S.Nandakumar, F.Nima, N.Ravi, Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls, Conf Proc IEEE Eng Med Biol Soc.,2013, pp:6115-8. doi: 0.1109/EMBC.2013.6610948.
  • W.Qinghui, W.Ye Jin, Lifeng, F.Ansong, Design of Novel Fire Rescue System Based on Wireless Sensor Network, Sensors & Transducers, Vol. 157, Issue 10, October 2013, pp: 168-172, doi: 10.1007/978-3-642-31869-6_35.
  • W. Aung Aung Phyo, F. Siang Fook, H.Weimin, Jit Biswas, Chi-Chun Hsia, Koujuch Liou, Y. Philip, Lying Posture Classification for Pressure Ulcer Prevention, Journal of Healthcare Engineering • Vol.1, No. 2, 2010. pp: 217–238, doi:10.1260/2040-2295.1.2.217.
Yıl 2016, Cilt: 5 , 59 - 70, 07.11.2016

Öz

Kaynakça

  • A.Mincholéa, L.Sörnmob, P.Laguna, Detection of body position changes from the ECG using a Laplaciannoise model, Biomedical Signal Processing and Control 14, pp:189–196, 2014.
  • M. Aström, j. Garcia, P. Laguna, O. Pahlm, detection of body position changes using the surface electrocardiogram, Med. Bio. Eng. Comput., 41, 164-171, 2003.
  • Jing Jia, Gongming Xu, Xi Pei, at al, Accuracy and efficiency of an infrared based positioning and tracking system for patient set-up and monitoring in image guided radiotherapy, Infrared Physics & Technology 69, pp:26–31, 2015.
  • http://uykubozuklugu.uludag.edu.tr/ltrt014.htm, ( 02.09.2015, 22:20)
  • H.Sümbül, A. H.Yüzer, İvmealgılayıcı Kullanarak Farklı Pozisyonlara Göre Soluma Sinyallerinin Elde Edilmesi, SİU2015, Sinyal İşleme Ve İletişim Uygulamaları Kurultayı, 16 - 19 May 2015,Processing v. 1, pp:279-282, İnönü Üniversitesi, Malatya, TÜRKİYE.
  • http://www.memorial.com.tr/rehberler/saglik_rehberi/horlama-nedir/, (02.12.2015, 12:25)
  • http://www.medikalakademi.com.tr/bebeklerde-uyku-pozisyonu-nasil-olmali/, (21.12.2014, 20:05)
  • J. Pino Esteban, A. Mor´an Alejandra, Astrid D¨orner De la Paz and Pablo Aqueveque, Validation of Non-Invasive Monitoring Device to Evaluate Sleep Quality, Conf Proc IEEE Eng Med Biol Soc. 2015 Aug;2015:7974-7. doi: 10.1109/EMBC.2015.7320242.
  • H. Enamul, F. Dickerson Robert, A. Stankovic John, Monitoring body positions and movements during sleep using WISPs, Proceeding WH '10 Wireless Health 2010 Pages 44-53 ACM New York, NY, USA, doi:10.1145/1921081.1921088
  • M. Ermes, J. Pärkka, J. Mantyjarvi, I. Korhonen, Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions, IEEE Trans Inf Technol Biomed. 2008 Jan;12(1):20-6. doi: 10.1109/TITB.2007.899496.
  • A. Louis, L.Benny, K. Rachel, Y. Guang-Zhong, Sensor Placement for Activity Detection using Wearable Accelerometers, Body Sensor Networks (BSN), 2010 International Conference on, DOI: 10.1109/BSN.2010.23
  • G.K. Prisk, S. Verhaeghe, D. Padeken, H. Hamacher, M. Paiva., Three-dimensional ballistocardiography and respiratory motion in sustained microgravity, Aviat Space Environ Med. 2001 Dec;72(12):1067-74, PMID:11763106
  • Min Ju Kim, Gha-Hyun Lee, Chun-Sik Kim, Woo Sung Kim, Yoo-Sam Chung, Seockhoon Chung, Sang-Ahm Lee, Comparison of three actigraphic algorithms used to evaluate sleep in patients with obstructive sleep apnea, Sleep Breath (2013) 17:297–304, DOI 10.1007/s11325-012-0689-z.
  • P. Jéssica Fabia, S.S. Rogerio, F. Paula Martins de Oliveira, S.Denis Eduardo, B. Sergio Tufik, L., Is portable monitoring for diagnosing obstructive sleep apnea syndrome suitable in elderly population?, Sleep Breath (2013) 17:679–686, DOI 10.1007/s11325-012-0742-y
  • https://www.arduino.cc/, son erişim: 21.12.2015
  • https://www.mems-exchange.org/MEMS/what-is.html
  • B. Sebastian, S. Axel, B. Stephanus, Three-Axes Monolithic Silicon Low-g Accelerometer, journal of microelectromechanical systems, vol. 9, no. 4, december 2000, pp:551-556, doi: 1057-7157(00)10873-X.
  • A. D. Reis Filho Carlos, P. Pessatti Mudo, Jolo P. C. Cajueiro and Paulo A. Dal Fabbro, Elements for a Monolithically Integrated Rotation Imbalance Detector, Industrial Electronics, 2003. ISIE '03. 2003 IEEE International Symposium on, pp:897-900, doi: 10.1109/ISIE.2003.1267940.
  • MEMS by ADI Innovative technology to measure movement and sound, The World Leader in High-Performance Signal Processing Solutions, Analog Device.
  • Y. Zhenhe, L.Ying, Z.Qiaoxiang, L.Xue, A Falling Detection System with wireless sensor for the Elderly People Based on Ergnomics, International Journal of Smart Home Vol.8, No.1 (2014), pp.187-196, doi:10.14257/ijsh.2014.8.1.20.
  • S.Jivko, S.Vladimir, S.Ritika, S.Alexander, Vibrotactile Recognition and Categorization of Surfaces by a Humanoid Robot, IEEE Transactions On Robotics, pp:1-10. 2011, doi: 10.1109/TRO.2011.2127130.
  • K.Adil Mehmood, L.Young-Koo, Y. Lee Sungyoung, Tae-Seong Kim, A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer, IEEE transactions on information technology in biomedicine, vol. 14, no. 5, september 2010, pp:1166-1172, doi: 10.1109/TITB.2010.2051955.
  • M. Nolan, B. Madden, E. Burke, Accelerometer based measurement for the mapping of neck surface vibrations during vocalized speech., Conf Proc IEEE Eng Med Biol Soc. 2009;2009:4453-6. doi: 10.1109/IEMBS.2009.5333817.
  • Y. Yurish Sergey, Practical Circuits and Interface Techniques for MEMS Accelerometers with Quasi-Digital Output, Sensors & Transducers Magazine (S&T e-Digest), Vol.58, Issue 8, August 2005, pp.352-359, ISSN:1726-5479.
  • H. Sümbül, A. H. Yüzer, Measuring of Diaphragm Movements by using iMEMS Acceleration Sensor, International Conference on Electrical and Electronics Engineering, ELECO 2015, Processing, pp:166-170, Bursa, TÜRKİYE.
  • MPU-6000/MPU-6050 Product Specification, 2012 http://www.seeedstudio.com/wiki/images/b/b1/MPU6050.pdf (son erişim: 20.12.2015 23:41)
  • J. Fisher Christopher, Using an Accelerometer for Inclination Sensing, AN-1057 Application Note, Analog Device, 2010.
  • R.David Barbosa, L. Rojas Ojeda Juan, F. Crespo Foix Luis, M.Daniel Sánchez, A. Fernández Miguel, Mapping the Human Body for Vibrations using an Accelerometer, Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp: 1671-1674, 2007.
  • W.Woranat, Q. Le Trung, T.S. Bukkapatnam Satish, Wireless Wearable Multi-Sensory System for Monitoring of Sleep Apnea and Other Cardiorespiratory Disorders, 2013 IEEE International Conference on Automation Science, and Engineering (CASE), pp: 605-610, doi: 978-1-4799-1515-6/13/$31.00 ©2013 IEEE
  • G. Illapha Cuba, G. Bonomi Alberto, Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life, IEEE transactions on biomedical engineering, vol. 58, no. 9, pp: 2656-2663, 2011, doi: 10.1109/TBME.2011.2160723.
  • Wu Dan, Wang Lei, Zhang YT, Huang BY, Wang Bo, Lin SJ, Xu XW, A wearable respiration monitoring system based on digital respiratory inductive plethysmography, Conf Proc IEEE Eng Med Biol Soc. 2009, pp: 4844-7. doi: 10.1109/IEMBS.2009.5332665.
  • D. Hung Phan., S. Bonnet, R. Guillemaud, E. Castelli, Pham. Thi. N. Yen, Estimation of respiratory waveform and heart rate using an accelerometer, Conf Proc IEEE Eng Med Biol Soc., 2008, pp:4916-9. doi: 10.1109/IEMBS.2008.4650316.
  • M. Chan Alexander, F.Nima, N.Ravi, Ambulatory respiratory rate detection using ECG and a triaxial accelerometer, Conf Proc IEEE Eng Med Biol Soc.,2013, pp:4058-61. doi: 10.1109/EMBC.2013.6610436.
  • M. Chan Alexander, S.Nandakumar, F.Nima, N.Ravi, Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls, Conf Proc IEEE Eng Med Biol Soc.,2013, pp:6115-8. doi: 0.1109/EMBC.2013.6610948.
  • W.Qinghui, W.Ye Jin, Lifeng, F.Ansong, Design of Novel Fire Rescue System Based on Wireless Sensor Network, Sensors & Transducers, Vol. 157, Issue 10, October 2013, pp: 168-172, doi: 10.1007/978-3-642-31869-6_35.
  • W. Aung Aung Phyo, F. Siang Fook, H.Weimin, Jit Biswas, Chi-Chun Hsia, Koujuch Liou, Y. Philip, Lying Posture Classification for Pressure Ulcer Prevention, Journal of Healthcare Engineering • Vol.1, No. 2, 2010. pp: 217–238, doi:10.1260/2040-2295.1.2.217.
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Bölüm Articles
Yazarlar

Harun Sümbül

Ahmet Hayrettin Yüzer Bu kişi benim

Yayımlanma Tarihi 7 Kasım 2016
Yayımlandığı Sayı Yıl 2016 Cilt: 5

Kaynak Göster

APA Sümbül, H., & Yüzer, A. H. (2016). 3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome. Journal of New Results in Science, 5, 59-70.
AMA Sümbül H, Yüzer AH. 3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome. JNRS. Kasım 2016;5:59-70.
Chicago Sümbül, Harun, ve Ahmet Hayrettin Yüzer. “3D Monitoring of Lying Position for Patients With Positional Sleep Apnea Syndrome”. Journal of New Results in Science 5, Kasım (Kasım 2016): 59-70.
EndNote Sümbül H, Yüzer AH (01 Kasım 2016) 3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome. Journal of New Results in Science 5 59–70.
IEEE H. Sümbül ve A. H. Yüzer, “3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome”, JNRS, c. 5, ss. 59–70, 2016.
ISNAD Sümbül, Harun - Yüzer, Ahmet Hayrettin. “3D Monitoring of Lying Position for Patients With Positional Sleep Apnea Syndrome”. Journal of New Results in Science 5 (Kasım 2016), 59-70.
JAMA Sümbül H, Yüzer AH. 3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome. JNRS. 2016;5:59–70.
MLA Sümbül, Harun ve Ahmet Hayrettin Yüzer. “3D Monitoring of Lying Position for Patients With Positional Sleep Apnea Syndrome”. Journal of New Results in Science, c. 5, 2016, ss. 59-70.
Vancouver Sümbül H, Yüzer AH. 3D Monitoring of Lying Position for Patients with Positional Sleep Apnea Syndrome. JNRS. 2016;5:59-70.


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