Skip to main content
SpringerLink
Log in

Design and Implementation of Low-Cost Respiratory Rate Measurement Device

  • Research Article-Electrical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

A vital sign of the human body is respiration rate defined by the number of breaths a person takes per minute. In Bangladesh, respiratory diseases are very common. To find the respiration rate of patients, doctors use a traditional manual counting method. Sometimes this method is not accurate enough and is troublesome for them and it is time-consuming. Critical patients have very low breathing rates which makes it difficult to be counted and detected manually. That is why we developed a non-contact ultrasonic sensor-based method as well as a contact piezoelectric sensor-based method for obtaining respiration rate, and a comparison between them was demonstrated. The piezoelectric sensor was found to be more efficient and accurate and that is why we selected this sensor for the final design. We placed the sensor onto the subject’s body and collected data from three positions: chest, upper and lower abdomen. We got two best positions based on body mass index (BMI). For low-BMI subjects, the best position was the chest and upper abdomen; for high-BMI subjects, it was the upper and lower abdomen. The accuracy of the device was 96.58%. Respiratory rate, heart rate, oxygen saturation, and BMI data were collected from 49 normal and respiratory disease patients of Chittagong Medical College Hospital and some volunteers to detect respiratory diseases. A logistic regression model was used for binary classification of this dataset to check whether the patient has respiratory diseases or not and found 88% accuracy for this model after five-fold cross-validation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Ciocchetti, M.; Massaroni, C.; Saccomandi, P.; Caponero, M.; Polimadei, A.; Formica, D.; Schena, E.: Smart textile based on fiber Bragg grating sensors for respiratory monitoring: design and preliminary trials. Biosensors 5(3), 602–615 (2015). https://doi.org/10.3390/bios5030602

    Article  Google Scholar 

  2. Karlen, W.; Raman, S.; Ansermino, J.M.; Dumont, G.A.: Multiparameter respiratory rate estimation from the photoplethysmogram. IEEE Trans. Biomed. Eng. 60(7), 1946–1953 (2013). https://doi.org/10.1109/TBME.2013.2246160

    Article  Google Scholar 

  3. Boccignone, G.; D’Amelio, A.; Ghezzi, O.; Grossi, G.; Lanzarotti, R.: An evaluation of non-contact photoplethysmography-based methods for remote respiratory rate estimation. Sensors 23(7), 3387 (2023)

    Article  Google Scholar 

  4. Iqbal, T.; Elahi, A.; Ganly, S.; Wijns, W.; Shahzad, A.: Photoplethysmography-based respiratory rate estimation algorithm for health monitoring applications. J. Med. Biol. Eng. 42(2), 242–252 (2022)

    Article  Google Scholar 

  5. He, X.; Goubran, R.; Knoefel, F.: IR night vision video-based estimation of heart and respiration rates. In: 2017 IEEE Sensors Applications Symposium (SAS), pp. 1–5 (2017). https://doi.org/10.1109/SAS.2017.7894087

  6. Talukdar, D.; De Deus, L.F.; Sehgal, N.: (2022) Evaluation of a camera-based monitoring solution against regulated medical devices to measure heart rate, respiratory rate, oxygen saturation, and blood pressure. Cureus 14(11)

  7. Basra, A.; Mukhopadhayay, B.; Kar, S.: Temperature sensor based ultra low cost respiration monitoring system. In: 2017 9th International Conference on Communication Systems and Networks (COMSNETS), pp. 530–535 (2017). https://doi.org/10.1109/COMSNETS.2017.7945448, iSSN: 2155-2509

  8. Milici, S.; Lorenzo, J.; Lázaro, A.; Villarino, R.; Girbau, D.: Wireless breathing sensor based on wearable modulated frequency selective surface. IEEE Sens. J. 17(5), 1285–1292 (2017). https://doi.org/10.1109/JSEN.2016.2645766

    Article  Google Scholar 

  9. Massaroni, C.; Nicolò, A.; Lo Presti, D.; Sacchetti, M.; Silvestri, S.; Schena, E.: Contact-based methods for measuring respiratory rate. Sensors 19(4), 908 (2019)

    Article  Google Scholar 

  10. Shahshahani, A.; Bhadra, S.; Zilic, Z.: A continuous respiratory monitoring system using ultrasound piezo transducer. In: 2018 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–4 (2018). https://doi.org/10.1109/ISCAS.2018.8351359, iSSN: 2379-447X

  11. Naranjo-Hernández, D.; Talaminos-Barroso, A.; Reina-Tosina, J.; Roa, L.M.; Barbarov-Rostan, G.; Cejudo-Ramos, P.; Márquez-Martín, E.; Ortega-Ruiz, F.: Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing. Sensors 18(7), 2144 (2018). https://doi.org/10.3390/s18072144

    Article  Google Scholar 

  12. Danurwindo, I.; Basari.: Design of respiratory rate measurement based on ultrasound proximity sensor. In: 2019 IEEE R10 Humanitarian Technology Conference (R10-HTC) (47129), pp. 12–15 (2019). https://doi.org/10.1109/R10-HTC47129.2019.9042463, iSSN: 2572-7621

  13. Lin, K.Y.; Chen, D.Y.; Yang, C.; Chen, K.J.; Tsai, W.J.: Automatic human target detection and remote respiratory rate monitoring. In: 2016 IEEE Second International Conference on Multimedia Big Data (BigMM), pp. 354–356 (2016). https://doi.org/10.1109/BigMM.2016.79

  14. Chu, M.; Nguyen, T.; Pandey, V.; Zhou, Y.; Pham, H.N.; Bar-Yoseph, R.; Radom-Aizik, S.; Jain, R.; Cooper, D.M.; Khine, M.: Respiration rate and volume measurements using wearable strain sensors. npj Digit. Med. 2(1), 1–9 (2019). https://doi.org/10.1038/s41746-019-0083-3

    Article  Google Scholar 

  15. Liu, S.; Gao, R.X.; Freedson, P.S.: Non-invasive respiration and ventilation prediction using a single abdominal sensor belt. In: 2011 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), pp. 1–5 (2011). https://doi.org/10.1109/SPMB.2011.6120113

  16. Elsarnagawy, T.; Farrag, M.; Haueisen, J.; Abulaal, M.; Mahmoud, K.; Fouad, H.; Ansari, S.G.: A wearable wireless respiration rate monitoring system based on fiber optic sensors. Sens. Lett. 12(9), 1331–1336 (2014). https://doi.org/10.1166/sl.2014.3367

    Article  Google Scholar 

  17. Arifin, A.; Agustina, N.; Dewang, S.; Idris, I.; Tahir, D.: Polymer optical fiber-based respiratory sensors: various designs and implementations. J. Sens. 2019, e6970708 (2019). https://doi.org/10.1155/2019/6970708

    Article  Google Scholar 

  18. Acharya, S.; Mongan, W.M.; Rasheed, I.; Liu, Y.; Anday, E.; Dion, G.; Fontecchio, A.; Kurzweg, T.; Dandekar, K.R.: Ensemble learning approach via Kalman filtering for a passive wearable respiratory monitor. IEEE J. Biomed. Health Inform. 23(3), 1022–1031 (2019). https://doi.org/10.1109/JBHI.2018.2857924

    Article  Google Scholar 

  19. Pimentel, M.A.F.; Johnson, A.E.W.; Charlton, P.H.; Birrenkott, D.; Watkinson, P.J.; Tarassenko, L.; Clifton, D.A.: Toward a robust estimation of respiratory rate from pulse oximeters. IEEE Trans. Biomed. Eng. 64(8), 1914–1923 (2017). https://doi.org/10.1109/TBME.2016.2613124

    Article  Google Scholar 

  20. Zhou, Z.; Padgett, S.; Cai, Z.; Conta, G.; Wu, Y.; He, Q.; Zhang, S.; Sun, C.; Liu, J.; Fan, E.; Meng, K.; Lin, Z.; Uy, C.; Yang, J.; Chen, J.: Single-layered ultra-soft washable smart textiles for all-around ballistocardiograph, respiration, and posture monitoring during sleep. Biosens. Bioelectron. 155, 112064 (2020). https://doi.org/10.1016/j.bios.2020.112064

    Article  Google Scholar 

  21. Zhao, H.; Gao, X.; Jiang, X.; Hong, H.; Liu, X.: Non-contact robust respiration detection by using radar-depth camera sensor fusion. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 4183–4186 (2020). https://doi.org/10.1109/EMBC44109.2020.9176852, iSSN: 2694-0604

  22. Heydari, F.; Ebrahim, M.P.; Yuce, M.R.: Chest-based real-time pulse and respiration monitoring based on bio-impedance. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 4398–4401 (2020). https://doi.org/10.1109/EMBC44109.2020.9176348, iSSN: 2694-0604

  23. Huang, W.; Bulut, M.; Lieshout, R.V.; Dellimore, K.: Exploration of using a pressure sensitive mat for respiration rate and heart rate estimation. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 298–301 (2021). https://doi.org/10.1109/EMBC46164.2021.9629997, iSSN: 2694-0604

  24. Ahmed, T.; Rahman, M.M.; Yusuf Ahmed, M.; Nemati, E.; Dinh, M.; Folkman, N.; Kuang, J.; Gao, A.: RRMonitor: a resource-aware end-to-end system for continuous monitoring of respiration rate using earbuds. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 2463–2467 (2021). https://doi.org/10.1109/EMBC46164.2021.9631109, iSSN: 2694-0604

  25. Shahshahani, A.; Zilic, Z.; Bhadra, S.: A 4-channel piezo transducer based flexible hybrid sensor for respiratory monitoring. In: 2019 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS), pp. 1–3 (2019). https://doi.org/10.1109/FLEPS.2019.8792242

  26. Jiao, C.; Lyons, P.; Zare, A.; Rosales, L.; Skubic, M.: Heart beat characterization from ballistocardiogram signals using extended functions of multiple instances. In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 756–760 (2016). https://doi.org/10.1109/EMBC.2016.7590812, iSSN: 1558-4615

  27. Hermawan, D.R.; Fahrio Ghanial Fatihah, M.; Kurniawati, L.; Helen, A.: Comparative study of J48 decision tree classification algorithm, random tree, and random forest on in-vehicle couponrecommendation data. In: 2021 International Conference on Artificial Intelligence and Big Data Analytics, pp. 1–6 (2021). https://doi.org/10.1109/ICAIBDA53487.2021.9689701

  28. Zahra, I.; Wisana, I.D.; Nugraha, P.; Hassaballah, H.J.: Design a monitoring device for heart-attack early detection based on respiration rate and body temperature parameters. Indones. J. Electron. Electromed. Eng. Med. Inform. 3(3), 114–120 (2021). https://doi.org/10.35882/ijeeemi.v3i3.5

  29. Park, S.H.; Choi, S.J.; Park, K.S.: Advance continuous monitoring of blood pressure and respiration rate using denoising auto encoder and LSTM. Microsyst. Technol. 28(10), 2181–2190 (2022)

    Article  Google Scholar 

  30. Jung, H.; Kim, D.; Choi, J.; Joo, E.Y.: Validating a consumer smartwatch for nocturnal respiratory rate measurements in sleep monitoring. Sensors 23(18), 7976 (2023)

    Article  Google Scholar 

  31. Tanaka, H.; Yokose, M.; Takaki, S.; Mihara, T.; Saigusa, Y.; Goto, T.: Evaluation of respiratory rate monitoring using a microwave doppler sensor mounted on the ceiling of an intensive care unit: A prospective observational study. J. Clin. Monit. Comput. 36(1), 71–79 (2022)

    Article  Google Scholar 

Download references

Acknowledgements

We are also thankful to Chittagong Medical College Hospital for allowing me to collect data from their respiratory medicine ward.

Author information

Authors and Affiliations

  1. Department of EEE, CUET, Chittagong, 4349, Bangladesh

    Trishita Ghosh Troyee & Md. Manjurul Gani

  2. Department of EEE, BUET, Dhaka, Bangladesh

    Mahmudul Hasan

Authors
  1. Trishita Ghosh Troyee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Md. Manjurul Gani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mahmudul Hasan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Trishita Ghosh Troyee.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Troyee, T.G., Gani, M.M. & Hasan, M. Design and Implementation of Low-Cost Respiratory Rate Measurement Device. Arab J Sci Eng 49, 6959–6969 (2024). https://doi.org/10.1007/s13369-023-08533-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-023-08533-x

Keywords

Search

Navigation