Exploring the Efficacy of Piezoelectric-Based Sensory Systems for Heart Rate Monitoring in Differentiating Stress vs. Relax Conditions

Authors

DOI:

https://doi.org/10.31436/iiumej.v25i2.3017

Keywords:

biosensors, piezoelectric, Healthcare

Abstract

Stress has diverse effects on human physiological reactions, and one such effect is on heart rate (HR). The established methods to acquire HR is by electrocardiogram (ECG) and photoplethysmogram (PPG). ECG electrodes need to be placed on the chest, which can cause inconvenience and is not practical in daily life, while PPG signals are known to contain more noise than ECG. Thus, this work aims to investigate the efficacy of a piezoelectric-based sensory system in measuring HR and using the signal to differentiate stressed and relaxed conditions by means of statistical analysis. Two activities were conducted to achieve the goal. The first experiment involved collecting and analysing piezoelectric signals to measure the pulse rate (bpm) and compare this with the HR from PPG. For the second experiment, the piezoelectric-based HR was calculated from 20 subjects (male and female, age ranging between 20 and 25) in relaxed and stressed conditions. The stress condition was triggered using two stressors: the Stroop Colour Word Test and the Digit Span Test. Statistical analyses reveal a strong positive correlation between piezoelectric-based heart rate (HR) and oximeter readings (r(12) = 0.993, p < 0.001), despite the fact that the values are not precisely identical. In addition, the findings also indicate that there are significant effects by the mental states (stressed and relaxed) on the piezoelectric-based HR readings (p<0.05). Employing a within-subject design condition, the results further illustrated that piezoelectric readings are elevated during stressed conditions (Mean±SD = 72.395±0.097) and diminished during relaxed conditions (Mean±SD = 71.615±0.126). Therefore, the suggested piezoelectric-based sensory system has been validated as an effective means of categorizing stress and relaxation based on heart rate signals.

ABSTRAK: Tekanan mempunyai pelbagai kesan terhadap reaksi fisiologi manusia dan satu daripadanya adalah kadar denyut jantung (HR). Kaedah biasa bagi mengetahui HR adalah melalui elektrokardiogram (ECG) dan fotofetismogram (PPG). Elektrod ECG perlu dipasang pada dada di mana boleh menyebabkan ketidakselesaan dan tidak praktikal dalam kehidupan seharian, manakala isyarat PPG diketahui mengandungi lebih banyak bunyi berbanding ECG. Oleh itu, kajian ini bertujuan mengkaji kecekapan ystem deria berdasarkan piezoeletrik bagi mengukur HR dan menggunakan isyarat ini bagi membezakan keadaan tertekan atau tenang melalui cara analisis ystemic. Bagi mencapai tujuan ini, dua aktiviti dijalankan. Pertama eksperimen melibatkan pengumpulan dan analisis isyarat piezoeletrik bagi mengukur kadar nadi (bpm) dan membandingkan HR daripada PPG. Eksperimen kedua, HR berdasarkan piezoelektrik dikira dari 20 subjek (lelaki dan ystemic, berumur antara 20 dan 25) dalam keadaan tenang dan tertekan. Keadaan tertekan dibuat melalui dua ystemi: Ujian Stroop Patah Warna dan Ujian Rentang Digit. Analisis ystemic mendedahkan hubungkait yang kuat antara kadar denyut jantung (HR) berdasarkan piezoeletrik dan bacaan oksimeter (r(12) = 0.993, p < 0.001), walaupun bacaan tidak benar-benar serupa. Tambahan, penemuan ini menunjukkan terdapat kesan penting terhadap tahap mental (tertekan dan tenang) pada bacaan denyut jantung (HR) berdasarkan piezoeletrik (p<0.05). Dengan mengaplikasi keadaan reka bentuk subjek, dapatan menunjukkan bacaan piezoeletrik meningkat ystem keadaan tertekan (Mean±SD = 72.395±0.097) dan kurang ystem keadaan tenang (Mean±SD = 71.615±0.126). Oleh itu, ystem deria berdasarkan piezoeletrik telah diuji berkesan dalam mengkategori keadaan tertekan dan tenang berdasarkan isyarat denyut jantung.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

J. Chen, M. Abbod, and J. S. Shieh, “Pain and stress detection using wearable sensors and devices—a review,” Sensors (Switzerland), vol. 21, no. 4. 2021. doi: 10.3390/s21041030. DOI: https://doi.org/10.3390/s21041030

Y. S. Can, B. Arnrich, and C. Ersoy, “Stress detection in daily life scenarios using smart phones and wearable sensors: A survey,” J Biomed Inform, vol. 92, p. 103139, Apr. 2019, doi: 10.1016/J.JBI.2019.103139. DOI: https://doi.org/10.1016/j.jbi.2019.103139

G. Giannakakis, D. Grigoriadis, K. Giannakaki, O. Simantiraki, A. Roniotis, and M. Tsiknakis, “Review on Psychological Stress Detection Using Biosignals,” IEEE Trans Affect Comput, vol. 13, no. 1, pp. 440–460, 2022, doi: 10.1109/TAFFC.2019.2927337.

N. Widanti, B. Sumanto, P. Rosa, and M. Fathur Miftahudin, “Stress level detection using heart rate, blood pressure, and GSR and stress therapy by utilizing infrared,” 2015 International Conference on Industrial Instrumentation and Control, ICIC 2015, pp. 275–279, Jul. 2015, doi: 10.1109/IIC.2015.7150752. DOI: https://doi.org/10.1109/IIC.2015.7150752

J. R. Machado Fernández and L. Anishchenko, “Mental stress detection using bioradar respiratory signals,” Biomed Signal Process Control, vol. 43, pp. 244–249, May 2018, doi: 10.1016/J.BSPC.2018.03.006. DOI: https://doi.org/10.1016/j.bspc.2018.03.006

U. Lundberg et al., “Psychophysiological stress and emg activity of the trapezius muscle,” International Journal of Behavioral Medicine 1994 1:4, vol. 1, no. 4, pp. 354–370, Dec. 1994, doi: 10.1207/S15327558IJBM0104_5.

C. H. Vinkers et al., “The effect of stress on core and peripheral body temperature in humans,” Stress, vol. 16, no. 5, pp. 520–530, Sep. 2013, doi: 10.3109/10253890.2013.807243.

V. Engert, A. Merla, J. A. Grant, D. Cardone, A. Tusche, and T. Singer, “Exploring the Use of Thermal Infrared Imaging in Human Stress Research,” PLoS One, vol. 9, no. 3, p. 90782, Mar. 2014, doi: 10.1371/JOURNAL.PONE.0090782. DOI: https://doi.org/10.1371/journal.pone.0090782

U. Lundberg et al., “Psychophysiological stress and emg activity of the trapezius muscle,” Int J Behav Med, vol. 1, no. 4, 1994, doi: 10.1207/s15327558ijbm0104_5. DOI: https://doi.org/10.1207/s15327558ijbm0104_5

C. H. Vinkers et al., “The effect of stress on core and peripheral body temperature in humans,” Stress, vol. 16, no. 5, 2013, doi: 10.3109/10253890.2013.807243. DOI: https://doi.org/10.3109/10253890.2013.807243

A. A. Amiruldin and A. S. Ghazali, “You Are Too Loud! Classification of Psychological Conditions for Stress Detection System Using Galvanic Skin Response,” in Lecture Notes in Electrical Engineering, 2022. doi: 10.1007/978-981-19-2095-0_6.

B. Szakonyi, I. Vassányi, E. Schumacher, and I. Kósa, “Efficient methods for acute stress detection using heart rate variability data from Ambient Assisted Living sensors,” Biomed Eng Online, vol. 20, no. 1, 2021, doi: 10.1186/s12938-021-00911-6. DOI: https://doi.org/10.1186/s12938-021-00911-6

D. Hu and L. Gao, “Psychological Stress Level Detection Based on Heartbeat Mode,” Applied Sciences (Switzerland), vol. 12, no. 3, 2022, doi: 10.3390/app12031409. DOI: https://doi.org/10.3390/app12031409

P. Karthikeyan, M. Murugappan, and S. Yaacob, “Analysis of stroop colorword test-based human stress detection using electrocardiography and heart rate variability signals,” Arab J Sci Eng, vol. 39, no. 3, 2012, doi: 10.1007/s13369-013-0786-8. DOI: https://doi.org/10.1007/s13369-013-0786-8

P. Melillo, M. Bracale, and L. Pecchia, “Nonlinear Heart Rate Variability features for real-life stress detection. Case study: Students under stress due to university examination,” Biomed Eng Online, vol. 10, 2011, doi: 10.1186/1475-925X-10-96. DOI: https://doi.org/10.1186/1475-925X-10-96

S. N. M. Sayed Ismail, N. A. Nor, and S. Z. Ibrahim, “A comparison of emotion recognition system using electrocardiogram (ECG) and photoplethysmogram (PPG),” Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 6, 2022, doi: 10.1016/j.jksuci.2022.04.012. DOI: https://doi.org/10.1016/j.jksuci.2022.04.012

F. Riaz, M. A. Azad, J. Arshad, M. Imran, A. Hassan, and S. Rehman, “Pervasive blood pressure monitoring using Photoplethysmogram (PPG) sensor,” Future Generation Computer Systems, vol. 98, pp. 120–130, Sep. 2019, doi: 10.1016/j.future.2019.02.032. DOI: https://doi.org/10.1016/j.future.2019.02.032

Sattar Y and Chhabra L, “Electrocardiogram. [Updated 2023 Jun 5],” in StatPearls [Internet], Treasure Island (FL): StatPearls Publishing, 2023.

Castaneda D, Esparza A, Ghamari M, Soltanpur C, and Nazeran H, “A review on wearable photoplethysmography sensors and their potential future applications in health care,” Int J Biosens Bioelectron, vol. 4, no. 4, Aug. 2018. DOI: https://doi.org/10.15406/ijbsbe.2018.04.00125

S. Das Mahapatra et al., “Piezoelectric Materials for Energy Harvesting and Sensing Applications: Roadmap for Future Smart Materials,” Advanced Science, vol. 8, no. 17. 2021. doi: 10.1002/advs.202100864. DOI: https://doi.org/10.1002/advs.202100864

J. H. Park, D. G. Jang, J. W. Park, and S. K. Youm, “Wearable sensing of in-ear pressure for heart rate monitoring with a piezoelectric sensor,” Sensors (Switzerland), vol. 15, no. 9, 2015, doi: 10.3390/s150923402. DOI: https://doi.org/10.3390/s150923402

E. Cepeda, D. H. Peluffo-Ordóñez, P. Rosero-Montalvo, M. A. Becerra, A. C. Umaquinga-Criollo, and L. Ramírez, “Heart Rate Detection using a Piezoelectric Ceramic Sensor: Preliminary results,” Bionatura, vol. 7, no. 3, 2022, doi: 10.21931/RB/2022.07.03.30. DOI: https://doi.org/10.21931/RB/2022.07.03.30

Z. Ji and M. Zhang, “Highly sensitive and stretchable piezoelectric strain sensor enabled wearable devices for real-time monitoring of respiratory and heartbeat simultaneously,” Nanotechnology and Precision Engineering, vol. 5, no. 1, 2022, doi: 10.1063/10.0009365. DOI: https://doi.org/10.1063/10.0009365

Y. Hamonangan and W. Purnamaningsih, “Heartbeat detection system using piezoelectric transducer,” in AIP Conference Proceedings, American Institute of Physics Inc., Feb. 2017. doi: 10.1063/1.4976801. DOI: https://doi.org/10.1063/1.4976801

V. Setyowati, J. Muninggar, and M. R. S. Shantina, “Design of heart rate monitor based on piezoelectric sensor using an Arduino,” in Journal of Physics: Conference Series, Institute of Physics Publishing, Feb. 2017. doi: 10.1088/1742-6596/795/1/012016. DOI: https://doi.org/10.1088/1742-6596/795/1/012016

J. Ahmad Rather and Y. Shrivastava, “Effect of music therapy on pre-competition anxiety in college level soccer players of Kashmir,” ~ 1176 ~ International Journal of Physiology, vol. 4, no. 1, pp. 1176–1178, 2019, [Online]. Available: www.journalofsports.com

A. Asif, M. Majid, and S. M. Anwar, “Human stress classification using EEG signals in response to music tracks,” Comput Biol Med, vol. 107, pp. 182–196, Apr. 2019, doi: 10.1016/J.COMPBIOMED.2019.02.015. DOI: https://doi.org/10.1016/j.compbiomed.2019.02.015

L. J. Julian, “Measures of anxiety: State-Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI), and Hospital Anxiety and Depression Scale-Anxiety (HADS-A),” Arthritis Care Res (Hoboken), vol. 63, no. SUPPL. 11, Nov. 2011, doi: 10.1002/acr.20561. DOI: https://doi.org/10.1002/acr.20561

A. J. Donnell, A. Thomas, and W. C. Buboltz, “Psychological reactance: Factor structure and internal consistency of the questionnaire for the measurement of psychological reactance,” Journal of Social Psychology, vol. 141, no. 5, 2001, doi: 10.1080/00224540109600581. DOI: https://doi.org/10.1080/00224540109600581

A. A. Amiruldin and A. S. Ghazali, “You Are Too Loud! Classification of Psychological Conditions for Stress Detection System Using Galvanic Skin Response,” pp. 51–60, 2022, doi: 10.1007/978-981-19-2095-0_6. DOI: https://doi.org/10.1007/978-981-19-2095-0_6

G. Giannakakis, D. Grigoriadis, K. Giannakaki, O. Simantiraki, A. Roniotis, and M. Tsiknakis, “Review on Psychological Stress Detection Using Biosignals,” IEEE Trans Affect Comput, vol. 13, no. 1, pp. 440–460, 2022, doi: 10.1109/TAFFC.2019.2927337 DOI: https://doi.org/10.1109/TAFFC.2019.2927337

Downloads

Published

2024-07-14

How to Cite

Zulkifli, M. H. Z., Jasni , F., Ghazali, A. S., Nordin, N. H. D., Sidek, S. N., Shaharum, S. M., & Kamaru Zaman, F. H. (2024). Exploring the Efficacy of Piezoelectric-Based Sensory Systems for Heart Rate Monitoring in Differentiating Stress vs. Relax Conditions. IIUM Engineering Journal, 25(2), 325–337. https://doi.org/10.31436/iiumej.v25i2.3017

Issue

Section

Mechatronics and Automation Engineering

Funding data

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.