Research Article
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Year 2025, Volume: 12 Issue: 3, 873 - 893, 30.09.2025
https://doi.org/10.54287/gujsa.1737897

Abstract

References

  • Barnova, K., Martinek, R., Jaros, R., & Kahankova, R. (2020). Hybrid methods based on empirical mode decomposition for non-invasive fetal heart rate monitoring. IEEE Access, 8, 51200-51218. https://doi.org/10.1109/ACCESS.2020.2980254
  • Carek, A. M., Conant, J., Joshi, A., Kang, H., & Inan, O. T. (2017). SeismoWatch: wearable cuffless blood pressure monitoring using pulse transit time. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 1(3), 1-16. https://doi.org/10.1145/3130905
  • Centracchio, J., Parlato, S., Esposito, D., Bifulco, P., & Andreozzi, E. (2023). ECG-free heartbeat detection in seismocardiography signals via template matching. Sensors, 23(10), 4684.
  • Chen, Y., Yang, X., Song, R., Liu, X., & Zhang, J. (2024). Predicting arterial stiffness from single-channel photoplethysmography signal: a feature interaction-based approach. IEEE Journal of Biomedical and Health Informatics, 28(7), 3928-3941. https://doi.org/10.1109/JBHI.2024.3383234
  • cheol Jeong, I., Bychkov, D., & Searson, P. C. (2018). Wearable devices for precision medicine and health state monitoring. IEEE Transactions on Biomedical Engineering, 66(5), 1242-1258. https://doi.org/10.1109/TBME.2018.2871638
  • Erin, E., & Semiz, B. (2023). Spectral Analysis of Cardiogenic Vibrations to Distinguish Between Valvular Heart Diseases. In: Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (pp. 212-219). 16th International Conference on Bio-inspired Systems and Signal Processing, Lisbon, Portugal. https://doi.org/10.5220/0011663900003414
  • Etemadi, M., Inan, O. T., Heller, J. A., Hersek, S., Klein, L., & Roy, S. (2015). A wearable patch to enable long-term monitoring of environmental, activity and hemodynamics variables. IEEE Transactions on Biomedical Circuits and Systems, 10(2), 280-288. https://doi.org/10.1109/TBCAS.2015.2405480
  • Fattah, S. A., Rahman, M. M., Mustakin, N., Islam, M. T., Khan, A. I., & Shahnaz, C. (2017, October 19-22). Wrist-card: PPG sensor based wrist wearable unit for low cost personalized cardio healthcare system. 2017 IEEE Global Humanitarian Technology Conference (GHTC), San Jose, CA, USA. https://doi.org/10.1109/GHTC.2017.8239326
  • Ganti, V. G., Carek, A. M., Nevius, B. N., Heller, J. A., Etemadi, M., & Inan, O. T. (2020). Wearable cuff-less blood pressure estimation at home via pulse transit time. IEEE Journal of Biomedical and Health Informatics, 25(6), 1926-1937. https://doi.org/10.1109/JBHI.2020.3021532
  • Gupta, J. I., Shea, M. J., & Howlett, J. G. (2025). Cardiovascular Examination. MSD Manual. (Accessed:06/2025) https://www.msdmanuals.com/professional/cardiovascular-disorders/approach-to-the-cardiac-patient/cardiovascular-examination
  • Gupta, P., Moghimi, M. J., Jeong, Y., Gupta, D., Inan, O. T., & Ayazi, F. (2020). Precision wearable accelerometer contact microphones for longitudinal monitoring of mechano-acoustic cardiopulmonary signals. NPJ Digital Medicine, 3(1), 19. https://doi.org/10.1038/s41746-020-0225-7
  • Hayirlioglu, Y. Z., & Semiz, B. (2024). PhysioPatch: A Multi-modal and Adaptable Wearable Patch for Cardiovascular and Cardiopulmonary Assessment. IEEE Sensors Journal, 24(13), 21347-21357.https://doi.org/10.1109/JSEN.2024.3403846
  • Hurnanen, T., Lehtonen, E., Tadi, M. J., Kuusela, T., Kiviniemi, T., Saraste, A., Vasankari, T., Airaksinen, J., Koivisto, T., & Pänkäälä, M. (2016). Automated detection of atrial fibrillation based on time–frequency analysis of seismocardiograms. IEEE Journal of Biomedical and Health Informatics, 21(5), 1233-1241. https://doi.org/10.1109/JBHI.2016.2621887
  • Inan, O. T., Baran Pouyan, M., Javaid, A. Q., Dowling, S., Etemadi, M., Dorier, A., Heller, J. A., Bicen, A. O., Roy, S., & De Marco, T. (2018). Novel wearable seismocardiography and machine learning algorithms can assess clinical status of heart failure patients. Circulation: Heart Failure, 11(1), e004313. https://doi.org/10.1161/CIRCHEARTFAILURE.117.004313
  • Inan, O. T., Migeotte, P.-F., Park, K.-S., Etemadi, M., Tavakolian, K., Casanella, R., Zanetti, J., Tank, J., Funtova, I., & Prisk, G. K. (2014). Ballistocardiography and seismocardiography: A review of recent advances. IEEE Journal of Biomedical and Health Informatics, 19(4), 1414-1427. https://doi.org/10.1109/JBHI.2014.2361732
  • ISO. (2017a). Medical electrical equipment — Part 2-56: Particular requirements for basic safety and essential performance of clinical thermometers for body temperature measurement (ISO 80601-2-56:2017). I. O. f. Standardization.
  • ISO. (2017b). Medical electrical equipment — Part 2-61: Particular requirements for basic safety and essential performance of pulse oximeter equipment (ISO 80601-2-61:2017). I. O. f. Standardization.
  • ISO. (2018). Medical electrical equipment — Part 2-55: Particular requirements for the basic safety and essential performance of respiratory rate monitoring equipment (ISO 80601-2-55:2018). I. O. f. Standardization.
  • Kaiser, J. F. (1990, April 03-06). On a simple algorithm to calculate the'energy'of a signal. In: International conference on acoustics, speech, and signal processing, Albuquerque, NM, USA. https://doi.org/10.1109/ICASSP.1990.115702
  • Klum, M., Urban, M., Tigges, T., Pielmus, A.-G., Feldheiser, A., Schmitt, T., & Orglmeister, R. (2020). Wearable cardiorespiratory monitoring employing a multimodal digital patch stethoscope: estimation of ECG, PEP, LVET and respiration using a 55 mm single-lead ECG and phonocardiogram. Sensors, 20(7), 2033. https://doi.org/10.3390/s20072033
  • Lee, J., Matsumura, K., Yamakoshi, K.-i., Rolfe, P., Tanaka, S., & Yamakoshi, T. (2013). Comparison between red, green and blue light reflection photoplethysmography for heart rate monitoring during motion. 2013 35th annual international conference of the IEEE engineering in medicine and biology society (EMBC).
  • Li, S.-H., Lin, B.-S., Wang, C.-A., Yang, C.-T., & Lin, B.-S. (2017). Design of wearable and wireless multi-parameter monitoring system for evaluating cardiopulmonary function. Medical Engineering & Physics, 47, 144-150. https://doi.org/10.1016/j.medengphy.2017.06.009
  • Lin, Y.-D., & Jhou, Y.-F. (2020). Estimation of heart rate and respiratory rate from the seismocardiogram under resting state. Biomedical Signal Processing and Control, 57, 101779. https://doi.org/10.1016/j.bspc.2019.101779
  • Loro, F. L., Martins, R., Ferreira, J. B., de Araujo, C. L. P., Prade, L. R., Both, C. B., Nobre, J. C. N., Monteiro, M. B., & Dal Lago, P. (2024). Validation of a Wearable Sensor Prototype for Measuring Heart Rate to Prescribe Physical Activity: Cross-Sectional Exploratory Study. JMIR Biomedical Engineering, 9, e57373. https://doi.org/10.2196/57373
  • Maeda, Y., Sekine, M., & Tamura, T. (2011). Relationship between measurement site and motion artifacts in wearable reflected photoplethysmography. Journal of Medical Systems, 35, 969-976. https://doi.org/10.1007/s10916-010-9505-0
  • Nwibor, C., Haxha, S., Ali, M. M., Sakel, M., Haxha, A. R., Saunders, K., & Nabakooza, S. (2023). Remote health monitoring system for the estimation of blood pressure, heart rate, and blood oxygen saturation level. IEEE Sensors Journal, 23(5), 5401-5411. https://doi.org/10.1109/JSEN.2023.3235977
  • Pandia, K., Inan, O. T., & Kovacs, G. T. (2013, July 03-07). A frequency domain analysis of respiratory variations in the seismocardiogram signal. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan. https://doi.org/10.1109/EMBC.2013.6611139
  • Sana, F., Isselbacher, E. M., Singh, J. P., Heist, E. K., Pathik, B., & Armoundas, A. A. (2020). Wearable devices for ambulatory cardiac monitoring: JACC state-of-the-art review. Journal of the American College of Cardiology, 75(13), 1582-1592. https://doi.org/10.1016/j.jacc.2020.01.046
  • Semiz, B. (2025). Clinical Validation of a Custom Wearable Patch for Accurate and Comfortable Vital Sign Monitoring in Pediatric Patients. Acibadem Saglik Bilimleri Dergisi, 16(1). https://doi.org/10.31067/acusaglik.1569618
  • Semiz, B., Carek, A. M., Johnson, J. C., Ahmad, S., Heller, J. A., Vicente, F. G., Caron, S., Hogue, C. W., Etemadi, M., & Inan, O. T. (2020). Non-invasive wearable patch utilizing seismocardiography for peri-operative use in surgical patients. IEEE Journal of Biomedical and Health Informatics, 25(5), 1572-1582. https://doi.org/10.1109/JBHI.2020.3032938
  • Shandhi, M. M. H., Semiz, B., Hersek, S., Goller, N., Ayazi, F., & Inan, O. T. (2019). Performance analysis of gyroscope and accelerometer sensors for seismocardiography-based wearable pre-ejection period estimation. IEEE Journal of Biomedical and Health Informatics, 23(6), 2365-2374. https://doi.org/10.1109/JBHI.2019.2895775
  • Taebi, A., Solar, B. E., Bomar, A. J., Sandler, R. H., & Mansy, H. A. (2019). Recent advances in seismocardiography. Vibration, 2(1), 64-86. https://doi.org/10.3390/vibration2010005
  • WHO. (2024). The top 10 causes of death. World Health Organization. (Accessed:06/2025) https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
  • Yang, C., Aranoff, N. D., Green, P., & Tavassolian, N. (2019). Classification of aortic stenosis using time–frequency features from chest cardio-mechanical signals. IEEE Transactions on Biomedical Engineering, 67(6), 1672-1683. https://doi.org/10.1109/TBME.2019.2942741
  • Zavanelli, N., Kim, H., Kim, J., Herbert, R., Mahmood, M., Kim, Y.-S., Kwon, S., Bolus, N. B., Torstrick, F. B., & Lee, C. S. (2021). At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch. Science Advances, 7(52), eabl4146.

A Compact Multimodal Patch for Continuous and Electrode-Free Cardiopulmonary Monitoring

Year 2025, Volume: 12 Issue: 3, 873 - 893, 30.09.2025
https://doi.org/10.54287/gujsa.1737897

Abstract

Continuous and non-invasive cardiopulmonary monitoring is essential for the early detection and management of both chronic and acute health conditions. This study presents a compact, multimodal wearable patch that captures seismocardiogram (SCG), dual-wavelength photoplethysmogram (PPG), and skin temperature signals without requiring gel electrodes or form factor-limited designs. The system integrates low-noise sensors and a custom-designed PCB within a 3D-printed enclosure, resulting in a lightweight, electrode-free device suitable for a wide range of users. Experimental validation with 12 participants demonstrated accurate estimation of heart rate (HR), heart rate variability (HRV), respiratory rate (RR), and temperature, with low mean percentage errors across all modalities. HR and HRV were estimated with errors below 1%, RR with a mean error of 1.6%, and temperature within a 3.7% error margin. Additionally, the application of Teager-Kaiser energy operator improved the robustness of peak detection in SCG signals, leading to more accurate and reliable HR and HRV estimation. Unlike many existing wearables that rely on adhesive electrodes or single-signal modalities, this system offers a miniaturized, multi-sensor solution for continuous cardiopulmonary monitoring, suitable for both clinical environments and daily-life integration.

Ethical Statement

This study was conducted by a protocol approved by the Koç University Institutional Review Board and all participants have provided written consent (2024.358.IRB2.155).

Thanks

The corresponding author would like to thank Erem Onay and Yusuf Ziya Hayirlioglu for their support during the hardware design.

References

  • Barnova, K., Martinek, R., Jaros, R., & Kahankova, R. (2020). Hybrid methods based on empirical mode decomposition for non-invasive fetal heart rate monitoring. IEEE Access, 8, 51200-51218. https://doi.org/10.1109/ACCESS.2020.2980254
  • Carek, A. M., Conant, J., Joshi, A., Kang, H., & Inan, O. T. (2017). SeismoWatch: wearable cuffless blood pressure monitoring using pulse transit time. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 1(3), 1-16. https://doi.org/10.1145/3130905
  • Centracchio, J., Parlato, S., Esposito, D., Bifulco, P., & Andreozzi, E. (2023). ECG-free heartbeat detection in seismocardiography signals via template matching. Sensors, 23(10), 4684.
  • Chen, Y., Yang, X., Song, R., Liu, X., & Zhang, J. (2024). Predicting arterial stiffness from single-channel photoplethysmography signal: a feature interaction-based approach. IEEE Journal of Biomedical and Health Informatics, 28(7), 3928-3941. https://doi.org/10.1109/JBHI.2024.3383234
  • cheol Jeong, I., Bychkov, D., & Searson, P. C. (2018). Wearable devices for precision medicine and health state monitoring. IEEE Transactions on Biomedical Engineering, 66(5), 1242-1258. https://doi.org/10.1109/TBME.2018.2871638
  • Erin, E., & Semiz, B. (2023). Spectral Analysis of Cardiogenic Vibrations to Distinguish Between Valvular Heart Diseases. In: Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (pp. 212-219). 16th International Conference on Bio-inspired Systems and Signal Processing, Lisbon, Portugal. https://doi.org/10.5220/0011663900003414
  • Etemadi, M., Inan, O. T., Heller, J. A., Hersek, S., Klein, L., & Roy, S. (2015). A wearable patch to enable long-term monitoring of environmental, activity and hemodynamics variables. IEEE Transactions on Biomedical Circuits and Systems, 10(2), 280-288. https://doi.org/10.1109/TBCAS.2015.2405480
  • Fattah, S. A., Rahman, M. M., Mustakin, N., Islam, M. T., Khan, A. I., & Shahnaz, C. (2017, October 19-22). Wrist-card: PPG sensor based wrist wearable unit for low cost personalized cardio healthcare system. 2017 IEEE Global Humanitarian Technology Conference (GHTC), San Jose, CA, USA. https://doi.org/10.1109/GHTC.2017.8239326
  • Ganti, V. G., Carek, A. M., Nevius, B. N., Heller, J. A., Etemadi, M., & Inan, O. T. (2020). Wearable cuff-less blood pressure estimation at home via pulse transit time. IEEE Journal of Biomedical and Health Informatics, 25(6), 1926-1937. https://doi.org/10.1109/JBHI.2020.3021532
  • Gupta, J. I., Shea, M. J., & Howlett, J. G. (2025). Cardiovascular Examination. MSD Manual. (Accessed:06/2025) https://www.msdmanuals.com/professional/cardiovascular-disorders/approach-to-the-cardiac-patient/cardiovascular-examination
  • Gupta, P., Moghimi, M. J., Jeong, Y., Gupta, D., Inan, O. T., & Ayazi, F. (2020). Precision wearable accelerometer contact microphones for longitudinal monitoring of mechano-acoustic cardiopulmonary signals. NPJ Digital Medicine, 3(1), 19. https://doi.org/10.1038/s41746-020-0225-7
  • Hayirlioglu, Y. Z., & Semiz, B. (2024). PhysioPatch: A Multi-modal and Adaptable Wearable Patch for Cardiovascular and Cardiopulmonary Assessment. IEEE Sensors Journal, 24(13), 21347-21357.https://doi.org/10.1109/JSEN.2024.3403846
  • Hurnanen, T., Lehtonen, E., Tadi, M. J., Kuusela, T., Kiviniemi, T., Saraste, A., Vasankari, T., Airaksinen, J., Koivisto, T., & Pänkäälä, M. (2016). Automated detection of atrial fibrillation based on time–frequency analysis of seismocardiograms. IEEE Journal of Biomedical and Health Informatics, 21(5), 1233-1241. https://doi.org/10.1109/JBHI.2016.2621887
  • Inan, O. T., Baran Pouyan, M., Javaid, A. Q., Dowling, S., Etemadi, M., Dorier, A., Heller, J. A., Bicen, A. O., Roy, S., & De Marco, T. (2018). Novel wearable seismocardiography and machine learning algorithms can assess clinical status of heart failure patients. Circulation: Heart Failure, 11(1), e004313. https://doi.org/10.1161/CIRCHEARTFAILURE.117.004313
  • Inan, O. T., Migeotte, P.-F., Park, K.-S., Etemadi, M., Tavakolian, K., Casanella, R., Zanetti, J., Tank, J., Funtova, I., & Prisk, G. K. (2014). Ballistocardiography and seismocardiography: A review of recent advances. IEEE Journal of Biomedical and Health Informatics, 19(4), 1414-1427. https://doi.org/10.1109/JBHI.2014.2361732
  • ISO. (2017a). Medical electrical equipment — Part 2-56: Particular requirements for basic safety and essential performance of clinical thermometers for body temperature measurement (ISO 80601-2-56:2017). I. O. f. Standardization.
  • ISO. (2017b). Medical electrical equipment — Part 2-61: Particular requirements for basic safety and essential performance of pulse oximeter equipment (ISO 80601-2-61:2017). I. O. f. Standardization.
  • ISO. (2018). Medical electrical equipment — Part 2-55: Particular requirements for the basic safety and essential performance of respiratory rate monitoring equipment (ISO 80601-2-55:2018). I. O. f. Standardization.
  • Kaiser, J. F. (1990, April 03-06). On a simple algorithm to calculate the'energy'of a signal. In: International conference on acoustics, speech, and signal processing, Albuquerque, NM, USA. https://doi.org/10.1109/ICASSP.1990.115702
  • Klum, M., Urban, M., Tigges, T., Pielmus, A.-G., Feldheiser, A., Schmitt, T., & Orglmeister, R. (2020). Wearable cardiorespiratory monitoring employing a multimodal digital patch stethoscope: estimation of ECG, PEP, LVET and respiration using a 55 mm single-lead ECG and phonocardiogram. Sensors, 20(7), 2033. https://doi.org/10.3390/s20072033
  • Lee, J., Matsumura, K., Yamakoshi, K.-i., Rolfe, P., Tanaka, S., & Yamakoshi, T. (2013). Comparison between red, green and blue light reflection photoplethysmography for heart rate monitoring during motion. 2013 35th annual international conference of the IEEE engineering in medicine and biology society (EMBC).
  • Li, S.-H., Lin, B.-S., Wang, C.-A., Yang, C.-T., & Lin, B.-S. (2017). Design of wearable and wireless multi-parameter monitoring system for evaluating cardiopulmonary function. Medical Engineering & Physics, 47, 144-150. https://doi.org/10.1016/j.medengphy.2017.06.009
  • Lin, Y.-D., & Jhou, Y.-F. (2020). Estimation of heart rate and respiratory rate from the seismocardiogram under resting state. Biomedical Signal Processing and Control, 57, 101779. https://doi.org/10.1016/j.bspc.2019.101779
  • Loro, F. L., Martins, R., Ferreira, J. B., de Araujo, C. L. P., Prade, L. R., Both, C. B., Nobre, J. C. N., Monteiro, M. B., & Dal Lago, P. (2024). Validation of a Wearable Sensor Prototype for Measuring Heart Rate to Prescribe Physical Activity: Cross-Sectional Exploratory Study. JMIR Biomedical Engineering, 9, e57373. https://doi.org/10.2196/57373
  • Maeda, Y., Sekine, M., & Tamura, T. (2011). Relationship between measurement site and motion artifacts in wearable reflected photoplethysmography. Journal of Medical Systems, 35, 969-976. https://doi.org/10.1007/s10916-010-9505-0
  • Nwibor, C., Haxha, S., Ali, M. M., Sakel, M., Haxha, A. R., Saunders, K., & Nabakooza, S. (2023). Remote health monitoring system for the estimation of blood pressure, heart rate, and blood oxygen saturation level. IEEE Sensors Journal, 23(5), 5401-5411. https://doi.org/10.1109/JSEN.2023.3235977
  • Pandia, K., Inan, O. T., & Kovacs, G. T. (2013, July 03-07). A frequency domain analysis of respiratory variations in the seismocardiogram signal. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan. https://doi.org/10.1109/EMBC.2013.6611139
  • Sana, F., Isselbacher, E. M., Singh, J. P., Heist, E. K., Pathik, B., & Armoundas, A. A. (2020). Wearable devices for ambulatory cardiac monitoring: JACC state-of-the-art review. Journal of the American College of Cardiology, 75(13), 1582-1592. https://doi.org/10.1016/j.jacc.2020.01.046
  • Semiz, B. (2025). Clinical Validation of a Custom Wearable Patch for Accurate and Comfortable Vital Sign Monitoring in Pediatric Patients. Acibadem Saglik Bilimleri Dergisi, 16(1). https://doi.org/10.31067/acusaglik.1569618
  • Semiz, B., Carek, A. M., Johnson, J. C., Ahmad, S., Heller, J. A., Vicente, F. G., Caron, S., Hogue, C. W., Etemadi, M., & Inan, O. T. (2020). Non-invasive wearable patch utilizing seismocardiography for peri-operative use in surgical patients. IEEE Journal of Biomedical and Health Informatics, 25(5), 1572-1582. https://doi.org/10.1109/JBHI.2020.3032938
  • Shandhi, M. M. H., Semiz, B., Hersek, S., Goller, N., Ayazi, F., & Inan, O. T. (2019). Performance analysis of gyroscope and accelerometer sensors for seismocardiography-based wearable pre-ejection period estimation. IEEE Journal of Biomedical and Health Informatics, 23(6), 2365-2374. https://doi.org/10.1109/JBHI.2019.2895775
  • Taebi, A., Solar, B. E., Bomar, A. J., Sandler, R. H., & Mansy, H. A. (2019). Recent advances in seismocardiography. Vibration, 2(1), 64-86. https://doi.org/10.3390/vibration2010005
  • WHO. (2024). The top 10 causes of death. World Health Organization. (Accessed:06/2025) https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
  • Yang, C., Aranoff, N. D., Green, P., & Tavassolian, N. (2019). Classification of aortic stenosis using time–frequency features from chest cardio-mechanical signals. IEEE Transactions on Biomedical Engineering, 67(6), 1672-1683. https://doi.org/10.1109/TBME.2019.2942741
  • Zavanelli, N., Kim, H., Kim, J., Herbert, R., Mahmood, M., Kim, Y.-S., Kwon, S., Bolus, N. B., Torstrick, F. B., & Lee, C. S. (2021). At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch. Science Advances, 7(52), eabl4146.
There are 35 citations in total.

Details

Primary Language English
Subjects Biomedical Instrumentation, Electronic Sensors, Embedded Systems
Journal Section Research Article
Authors

Beren Semiz 0000-0002-7544-5974

Submission Date July 8, 2025
Acceptance Date August 15, 2025
Publication Date September 30, 2025
Published in Issue Year 2025 Volume: 12 Issue: 3

Cite

APA Semiz, B. (2025). A Compact Multimodal Patch for Continuous and Electrode-Free Cardiopulmonary Monitoring. Gazi University Journal of Science Part A: Engineering and Innovation, 12(3), 873-893. https://doi.org/10.54287/gujsa.1737897