Abstract
Uyku apnesi hastalarının apneye girmelerinde yatış pozisyonlarının önemli bir etkisi vardır. Bu çalışmada sleep sense firmasının üretmiş olduğu vücut pozisyon sensörü (SleepSense 1/8" Plug DC Body Position Sensor Kit) kullanılarak hastanın yatış pozisyonu STM mikrodenetleyicisi ile okunmuştur. Bu sensör 0-2V arasında ürettiği anolog sinyallerle sonuç üretmektedir. Bu analog sinyal mikrodenetleyicinin ADC özelliği kullanılarak okunmuştur. Mikrodenetleyici tarafından okunan bu sinyal USB port üzerinden bilgisayara gönderilmiştir. Bilgisayarda hazırlanan C# yazılımı mikrodenetleyiciden gelen verileri okumakta ve bit TXT uzantılı dosyaya bu verileri ve verinin geliş saati ile birlikte kaydetmektedir. Bu TXT uzantılı dosya içerisindeki veriler sinyal işleme yöntemleri ile değerlendirilebilmek için hazır hale gelmiştir. Bu veriler, polisomnografi cihazından elde edilen diğer veriler ile birlikte hastanın apneye girdiği anlardaki vücut pozisyonu öğrenmek için kullanılabilecektir.
Supporting Institution
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu(TÜBİTAK)
Project Number
5190006
Thanks
Bu çalışmayı 1505 Üniversite-Sanayi İşbirliği Destek Programı kapsamında 5190006 proje numarası ile destekleyen Türkiye Bilimsel ve Teknolojik Araştirma Kurumu’na (TÜBİTAK) teşekkürlerimizi sunarız.
References
- [1] J. L. Pépin, S. Bailly, and R. Tamisier, "Big Data in sleep apnoea: Opportunities and challenges," Respirology, vol. 25, pp. 486-494, 2020.
- [2] F. Mendonça, S. S. Mostafa, A. G. Ravelo-García, F. Morgado-Dias, and T. Penzel, "Devices for home detection of obstructive sleep apnea: A review," Sleep medicine reviews, vol. 41, pp. 149-160, 2018.
- [3] R. Jane, "Engineering Sleep Disorders: From classical CPAP devices toward new intelligent adaptive ventilatory therapy," IEEE pulse, vol. 5, pp. 29-32, 2014.
- [4] D. Demirkol Çakmak, "Mobile sleep apnea detection and monitoring based on thermocouple and pulse oximeter sensors," 2018.
- [5] R. Agrawal, J. A. Wang, A. G. Ko, and J. E. Getsy, "A real-world comparison of apnea–hypopnea indices of positive airway pressure device and polysomnography," Plos one, vol. 12, p. e0174458, 2017.
- [6] L. Schwiebert, S. K. Gupta, and J. Weinmann, "Research challenges in wireless networks of biomedical sensors," in Proceedings of the 7th annual international conference on Mobile computing and networking, 2001, pp. 151-165.
- [7] M. Engin, A. Demirel, E. Z. Engin, and M. Fedakar, "Recent developments and trends in biomedical sensors," Measurement, vol. 37, pp. 173-188, 2005.
- [8] STMicroelectronics. (2021, 03.10.2021). STM32F407/417. Available: https://www.st.com/en/microcontrollers-microprocessors/stm32f407-417.html
- [9] SleepSense. (2018, 03.10.2021). DC Body Position Sensor Kit – 1/8″ Female Plug. Available: https://sleepsense.com/shop/sleepsense-body-position-sensors/dc-body-position-sensor-kit-18-female-plug/
Abstract
Sleeping positions have a significant impact on exposure of apnea patients to sleep apnea. In this study, the sleeping position of the patient was read with the STM microcontroller by using the body position sensor (SleepSense 1/8" Plug DC Body Position Sensor Kit) produced by the sleep sense company. This sensor produces results with analog signals between 0-2V. This analog signal was read using the ADC feature of the microcontroller. This signal read by the microcontroller was sent to the computer via the USB port. The C# software prepared on the computer reads the data from the microcontroller and saves this data and the arrival time of the data to the bit TXT file. The data in this TXT file is ready to be evaluated by signal processing methods. These data, together with other data obtained from the polysomnography device, can be used to learn the body position of the patient at the time of apnea.
Project Number
5190006
References
- [1] J. L. Pépin, S. Bailly, and R. Tamisier, "Big Data in sleep apnoea: Opportunities and challenges," Respirology, vol. 25, pp. 486-494, 2020.
- [2] F. Mendonça, S. S. Mostafa, A. G. Ravelo-García, F. Morgado-Dias, and T. Penzel, "Devices for home detection of obstructive sleep apnea: A review," Sleep medicine reviews, vol. 41, pp. 149-160, 2018.
- [3] R. Jane, "Engineering Sleep Disorders: From classical CPAP devices toward new intelligent adaptive ventilatory therapy," IEEE pulse, vol. 5, pp. 29-32, 2014.
- [4] D. Demirkol Çakmak, "Mobile sleep apnea detection and monitoring based on thermocouple and pulse oximeter sensors," 2018.
- [5] R. Agrawal, J. A. Wang, A. G. Ko, and J. E. Getsy, "A real-world comparison of apnea–hypopnea indices of positive airway pressure device and polysomnography," Plos one, vol. 12, p. e0174458, 2017.
- [6] L. Schwiebert, S. K. Gupta, and J. Weinmann, "Research challenges in wireless networks of biomedical sensors," in Proceedings of the 7th annual international conference on Mobile computing and networking, 2001, pp. 151-165.
- [7] M. Engin, A. Demirel, E. Z. Engin, and M. Fedakar, "Recent developments and trends in biomedical sensors," Measurement, vol. 37, pp. 173-188, 2005.
- [8] STMicroelectronics. (2021, 03.10.2021). STM32F407/417. Available: https://www.st.com/en/microcontrollers-microprocessors/stm32f407-417.html
- [9] SleepSense. (2018, 03.10.2021). DC Body Position Sensor Kit – 1/8″ Female Plug. Available: https://sleepsense.com/shop/sleepsense-body-position-sensors/dc-body-position-sensor-kit-18-female-plug/
Details
| Primary Language | English |
|---|---|
| Subjects | Electrical Engineering |
| Journal Section | Research Articles |
| Authors | |
| Project Number | 5190006 |
| Publication Date | April 30, 2022 |
| Submission Date | December 23, 2021 |
| Acceptance Date | April 7, 2022 |
| Published in Issue | Year 2022 Volume: 8 Issue: 1 |
Gazi Journal of Engineering Sciences (GJES) publishes open access articles under a Creative Commons Attribution 4.0 International License (CC BY). 