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FOTOPLETİSMOGRAFİ TEKNOLOJİSİNE DAYALI KALP ATIM HIZI ÖLÇÜMÜ YAPAN GİYİLEBİLİR AKILLI SAATLERİN KARŞILAŞTIRMALI DEĞERLENDİRİLMESİ: HUAWEI HONOR BAND 5 VS XIAOMI MI SMART BAND 5

Year 2022, , 105 - 118, 30.03.2022
https://doi.org/10.33689/spormetre.1019059

Abstract

Öz: Bu araştırmanın amacı, kalp atım hızı (KAH) ölçümünde fotopletismografi (PPG) teknolojisini kullanan Huawei Honor Band 5 (Huawei) ve Xiaomi Mi Smart Band 5 (Xiaomi) giyilebilir akıllı saatlerinin (GAS) KAH ölçümünde altın standart olarak referans alınan Polar V800 (Polar) saati karşısında geçerli veriler verip veremeyeceğinin kontrol edilmesidir. Araştırmaya, Erzincan Binali Yıldırım Üniversitesi (EBYÜ), Spor Bilimleri Fakültesi öğrencisi, 11’i kadın, 19’u erkek toplam 30 katılımcı (Yaş: 21,9±3 yıl, Boy: 172±9,5 cm, Kilo: 70,6±12,4 kg) gönüllülük esasına göre katılmıştır. Katılımcılara Polar, Huawei ve Xiaomi saatleri aynı anda ve farklı kollara takılmıştır. Polar saat takılı olduğu sağ kolda sabit kalırken, Huawei sağ ve Xiaomi ise sol kola takılmıştır. Katılımcıların Dinlenik Kalp Atım Hızları (DKAH) kaydedildikten sonra katılımcılar şiddeti sürekli artan Yo-Yo dinlenmeli koşu testine tabi tutularak ulaşabildikleri maksimum KAH’larının %75 ve %100’üne ulaşan değerleri ölçülmüştür. Her mekik sonunda katılımcıların üzerinde yer alan üç farklı saatten KAH ölçümleri alınarak kaydedilmiştir. Verilerin değerlendirilmesinde One-Sample T Testi, Pearson Korelasyon Katsayısı, Sınıfiçi Korelasyon Katsayısı (ICC) ve Bland-Altman Analizi kullanılmıştır. Araştırma sonuçlarına göre, katılımcıların DKAH ölçümlerinde bu üç saat arasında istatistiksel olarak anlamlı bir farklılık olmadığı (Polar: 81,3 atım/dk, Huawei: 81,9 atım/dk, Xiaomi: 81,1 atım/dk) (p>0.05), fakat katılımcıların maksimum KAH’larının %75 (Polar: 142,9 atım/dk, Huawei: 121,1 atım/dk, Xiaomi: 121,2 atım/dk) (p<0.05) ve %100’üne (Polar: 190,5 atım/dk, Huawei: 162 atım/dk, Xiaomi: 157,5 atım/dk) (p<0.05) denk gelen ölçümlerinde ise istatistiksel olarak anlamlı farklılıklar olduğu gözlemlenmiştir. Bu sonuçlara göre, KAH takibinde Huawei ve Xiaomi saatlerinin günlük kullanımlarının uygun olabileceği, ancak egzersiz sırasında sporcu gelişimi ve sağlığı açısından kullanımlarının uygun olmayacağı anlaşılmaktadır.

References

  • Achten, J., Jeukendrup, A.E. (2003). Heart rate monitoring. Sports medicine, 33(7), 517±538. https://doi.org/10.2165/00007256-200333070-00004 PMID: 12762827
  • Allen, J. (2007). Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement, 28, https://doi.org/10.1088/0967-3334/28/3/r01 PMID: 17322588
  • Benedetto, S., Caldato, C., Bazzan, E., Greenwood, D., Pensabene, V., Actis, P. (2018). Assessment of the fitbit charge 2 for monitoring heart rate. PLOS ONE, 13(2), e0192691. https://doi.org/10.1371/journal.pone.0192691
  • Butler, M.J., Crowe, J.A., Hayes-Gill, B.R., Rodmell, P.I. (2016). Motion limitations of non-contact photoplethysmography due to the optical and topological properties of skin. Physiological Measurement, 37, 27-37.
  • Caminal, P., Sola, F., Gomis, P., Guasch, E., Perera, A., Soriano, N., Mont, L. (2018). Validity of the Polar V800 monitor for measuring heart rate variability in mountain running route conditions. Eur J Appl Physiol, 118(3), 669-677. doi:10.1007/s00421-018-3808-0. PMID: 29356949.
  • Ghamari, M., Arora, H., Sherratt, R.S., Harwin, W. (2015). Comparison of low-power wireless communication technologies for wearable health-monitoring applications. I4CT - 2nd International Conference on Computer, Communications, and Control Technology in book, (ss. 1–6). Kuching: Malaysia.
  • Giles, D., Draper, N., Neil, W. (2016) Validity of the Polar V800 heart rate monitor to measure RR intervals at rest. Eur J Appl Physiol, 116(3), 563-71. doi:10.1007/s00421-015-3303-9. PMID:26708360; PMCID:PMC4751190.
  • Grand View Research. (2015). https://www.grandviewresearch.com/industry-analysis/wearable-technology-market adresinden erişilmiştir.
  • Huang, C.J., Chan, H.L., Chang, Y.J., Chen, S.M., Hsu, M.J. (2021). Validity of the Polar V800 monitor for assessing heart rate variability in elderly adults under mental stress and dual task conditions. Int J Environ Res Public Health, 18(3), 869. doi:10.3390/ijerph18030869. PMID:33498381; PMCID:PMC7908342.
  • Islam, S.M.R., Kwak, D., Kabir, H., et al. (2015). The internet of things for health care: A Comprehensive Survey. IEEE Access, 3, 678–708.
  • Jo, E., Lewis, K., Directo, D., Kim, M.J., Dolezal, B.A. (2016). Validation of biofeedback wearables for photoplethysmographic. Heart rate tracking. Journal of Sports Science & Medicine, 15(3), 540±547 28179
  • John, D.E., Bronzino, J.D. (2012). Introduction to biomedical engineering. San Diego: Academic Press.
  • Kavsaoğlu, A.R., Polat, K., Hariharan, M. (2015). Non-invasive prediction of hemoglobin level using machine learning techniques with the PPG signal’s characteristics features. Appl Soft Comput, 37, 983–991.
  • Lai, P.H., Kim, I. (2015). Lightweight wrist photoplethysmography for heavy exercise: motion robust heart rate monitoring algorithm. Healthcare Technology Letters, 2(1), 6-11.
  • Li, M., Kim, Y. T. (2017). Design of a wireless sensor system with the algorithms of heart rate and agility index for athlete evaluation. Sensors, 17(10), 2373.
  • Massimiliano, D.Z., Aimee, G., Stephanie, C., Ian, M.C., Fiona, C.B. (2018). A validation study of Fitbit Charge 2™ compared with polysomnography in adults. Chronobiology International, 35(4), 465-476, DOI:10.1080/07420528.2017.1413578
  • Pietilä, J., Mehrang, S., Tolonen, J., Helander, E., Jimison, H., Pavel, M., & Korhonen, I. (2017). Evaluation of the accuracy and reliability for photoplethysmography based heart rate and beat-to-beat detection during daily activities. In EMBEC & NBC, 5, 145-148.
  • Rafolt, D., Gallasch, E. (2004). Influence of contact forces on wrist photoplethysmography--prestudy for a wearable patient monitor. Biomedical Technology (Berl), 49, 22-26.
  • Rawassizadeh, R., Price, B.A., Petre, M. (2015). Wearables: has the age of smartwatches finally arrived? Commun ACM, 58(1), 45–47.
  • Spierer, D. K., Rosen, Z., Litman, L. L., Fujii, K. (2015). Validation of photoplethysmography as a method to detect heart rate during rest and exercise. Journal of Medical Engineering & Technology, 39(5), 264–271. doi:10.3109/03091902.2015.1047536
  • Stahl, S.E., An, H.S., Dinkel, D.M., Noble, J.M., Lee, J.M. (2016). How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough? BMJ Open Sport & Exercise Medicine, https://doi.org/10.1136/bmjsem-2015-000106 PMID: 27900173
  • Sviridova, N., Sakai. K,. (2015). Human photoplethysmogram: new insight into chaotic characteristics. Chaos Solitons & Fractals, 77, 53–63.
  • Takacs, J., Pollock, C.L., Guenther, J.R., Bahar, M., Napier, C., Hunt, M.A. (2014). Validation of the Fitbit One activity monitor device during treadmill walking. Journal of Science and Medicine in Sport, 17, 496±500. https://doi.org/10.1016/j.jsams.2013.10.241 PMID: 24268570
  • Tamura, T., Maeda, Y., Sekine., M., et al. (2014). Wearable photoplethysmographic sensors—past and present. Electronics, 3, 282–302.
  • Teng, X.F., Zhang, Y.T. (2004). The effect of contacting force on photoplethysmographic signals. Physiological Measurement, 25, 1323-1335.
  • Wallen, M. P., Gomersall, S. R., Keating, S. E., Wisløff, U., Coombes, J. S., Calbet, J. A. L. (2016). Accuracy of heart rate watches: Implications for weight management. PLoS One, 11(5), e0154420. doi:10.1371/journal.pone.0154420
  • Wang, C., Li, Z., Wei, X.. (2013). Monitoring heart and respiratory rates at radial artery based on PPG. Opt Int J Light Electron Opt., 124(4), 3954–3956.
  • Wright, S.P., Brown, T.S.H., Collier, S.R., Sandberg, K. (2017). How consumer physical activity monitors could transform human physiology research. American Journal of PhysiologyÐRegulatory, Integrative and Comparative Physiology, 312. https://doi.org/10.1152/ajpregu.00349.2016 PMID: 28052867
  • Yang, Bai., Paul, Hibbing., Constantine, Mantis., Gregory, J. Welk. (2018). Comparative evaluation of heart rate-based monitors: Apple Watch vs Fitbit Charge HR. Journal of Sports Sciences, 36, 1734-1741, doi:10.1080/02640414.2017.1412235
  • Zhang, Y., Liu, B., Zhang, Z. (2015). Combining ensemble empirical mode decomposition with spectrum subtraction technique for heart rate monitoring using wrist-type photoplethysmography. Biomed Signal Process Control, 21, 119–125.
  • Zhang, Z., Pi, Z., Liu, B. (2015). Troika: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise. IEEE Trans Biomed Eng, 62(2), 522–531.

COMPARATIVE EVALUATION OF WEARABLE SMARTWATCHES THAT MEASURE HEART RATE BASED ON PHOTOPLETHYSMOGRAPHY TECHNOLOGY: HUAWEI HONOR BAND 5 VS XIAOMI MI SMART BAND 5

Year 2022, , 105 - 118, 30.03.2022
https://doi.org/10.33689/spormetre.1019059

Abstract

Wearable technologies are becoming indicators of variables such as the intensity and duration that the athletes want to achieve in their exercise and training. These indicators should be accurately reflected to the athletes in monitoring the exercise load. The purpose of this study was to investigate whether Huawei Honor Band 5 (Huawei) and Xiaomi Mi Smart Band 5 (Xiaomi) could provide valid scores when compared the Polar V800 (Polar), that has been accepted as gold standard for heart rate assessment. This research has a quasi-experimental research model without a control group. In total, 11 females and 19 males (Age: 21,9±3 years, height: 172±9,5 cm, weight: 70,6±12,4 kg) individuals from Erzincan Binali Yıldırım University (EBYU) voluntarily participated in this study Participants wore Polar, Huawei and Xiaomi watches at the same time and on different wrists. The Polar watch is fixed on the right wrist, while Huawei is on the right and Xiaomi is on the left. After recording resting heart rate, participants were asked to perform Yo-Yo intermittent recovery test protocol. During the test 75% and 100% of maximal heart rate scores were recorded. Each shuttle result was measured. One sample t-test, Pearson Correlation Coefficient, Intra Class Correlation Coefficient and Bland-Altman were used for statistical analysis. Results showed that there were no significant differences among each other at resting conditions (Polar: 81,3 bpm, Huawei: 81,9 bpm, Xiaomi: 81,1 bpm) (p>0.05). However significant findings were observed in both 75% (Polar: 142,9 bpm, Huawei: 121,1 bpm, Xiaomi: 121,2 bpm (p<0.05) and 100% (Polar: 190,5 bpm, Huawei: 162 bpm, Xiaomi: 157,5 bpm) (p<0.05) of their maximal heart rate. According to findings, Huawei and Xiaomi can be used for daily use, on the other hand it may not be appropriate for athletic performance assessments.

References

  • Achten, J., Jeukendrup, A.E. (2003). Heart rate monitoring. Sports medicine, 33(7), 517±538. https://doi.org/10.2165/00007256-200333070-00004 PMID: 12762827
  • Allen, J. (2007). Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement, 28, https://doi.org/10.1088/0967-3334/28/3/r01 PMID: 17322588
  • Benedetto, S., Caldato, C., Bazzan, E., Greenwood, D., Pensabene, V., Actis, P. (2018). Assessment of the fitbit charge 2 for monitoring heart rate. PLOS ONE, 13(2), e0192691. https://doi.org/10.1371/journal.pone.0192691
  • Butler, M.J., Crowe, J.A., Hayes-Gill, B.R., Rodmell, P.I. (2016). Motion limitations of non-contact photoplethysmography due to the optical and topological properties of skin. Physiological Measurement, 37, 27-37.
  • Caminal, P., Sola, F., Gomis, P., Guasch, E., Perera, A., Soriano, N., Mont, L. (2018). Validity of the Polar V800 monitor for measuring heart rate variability in mountain running route conditions. Eur J Appl Physiol, 118(3), 669-677. doi:10.1007/s00421-018-3808-0. PMID: 29356949.
  • Ghamari, M., Arora, H., Sherratt, R.S., Harwin, W. (2015). Comparison of low-power wireless communication technologies for wearable health-monitoring applications. I4CT - 2nd International Conference on Computer, Communications, and Control Technology in book, (ss. 1–6). Kuching: Malaysia.
  • Giles, D., Draper, N., Neil, W. (2016) Validity of the Polar V800 heart rate monitor to measure RR intervals at rest. Eur J Appl Physiol, 116(3), 563-71. doi:10.1007/s00421-015-3303-9. PMID:26708360; PMCID:PMC4751190.
  • Grand View Research. (2015). https://www.grandviewresearch.com/industry-analysis/wearable-technology-market adresinden erişilmiştir.
  • Huang, C.J., Chan, H.L., Chang, Y.J., Chen, S.M., Hsu, M.J. (2021). Validity of the Polar V800 monitor for assessing heart rate variability in elderly adults under mental stress and dual task conditions. Int J Environ Res Public Health, 18(3), 869. doi:10.3390/ijerph18030869. PMID:33498381; PMCID:PMC7908342.
  • Islam, S.M.R., Kwak, D., Kabir, H., et al. (2015). The internet of things for health care: A Comprehensive Survey. IEEE Access, 3, 678–708.
  • Jo, E., Lewis, K., Directo, D., Kim, M.J., Dolezal, B.A. (2016). Validation of biofeedback wearables for photoplethysmographic. Heart rate tracking. Journal of Sports Science & Medicine, 15(3), 540±547 28179
  • John, D.E., Bronzino, J.D. (2012). Introduction to biomedical engineering. San Diego: Academic Press.
  • Kavsaoğlu, A.R., Polat, K., Hariharan, M. (2015). Non-invasive prediction of hemoglobin level using machine learning techniques with the PPG signal’s characteristics features. Appl Soft Comput, 37, 983–991.
  • Lai, P.H., Kim, I. (2015). Lightweight wrist photoplethysmography for heavy exercise: motion robust heart rate monitoring algorithm. Healthcare Technology Letters, 2(1), 6-11.
  • Li, M., Kim, Y. T. (2017). Design of a wireless sensor system with the algorithms of heart rate and agility index for athlete evaluation. Sensors, 17(10), 2373.
  • Massimiliano, D.Z., Aimee, G., Stephanie, C., Ian, M.C., Fiona, C.B. (2018). A validation study of Fitbit Charge 2™ compared with polysomnography in adults. Chronobiology International, 35(4), 465-476, DOI:10.1080/07420528.2017.1413578
  • Pietilä, J., Mehrang, S., Tolonen, J., Helander, E., Jimison, H., Pavel, M., & Korhonen, I. (2017). Evaluation of the accuracy and reliability for photoplethysmography based heart rate and beat-to-beat detection during daily activities. In EMBEC & NBC, 5, 145-148.
  • Rafolt, D., Gallasch, E. (2004). Influence of contact forces on wrist photoplethysmography--prestudy for a wearable patient monitor. Biomedical Technology (Berl), 49, 22-26.
  • Rawassizadeh, R., Price, B.A., Petre, M. (2015). Wearables: has the age of smartwatches finally arrived? Commun ACM, 58(1), 45–47.
  • Spierer, D. K., Rosen, Z., Litman, L. L., Fujii, K. (2015). Validation of photoplethysmography as a method to detect heart rate during rest and exercise. Journal of Medical Engineering & Technology, 39(5), 264–271. doi:10.3109/03091902.2015.1047536
  • Stahl, S.E., An, H.S., Dinkel, D.M., Noble, J.M., Lee, J.M. (2016). How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough? BMJ Open Sport & Exercise Medicine, https://doi.org/10.1136/bmjsem-2015-000106 PMID: 27900173
  • Sviridova, N., Sakai. K,. (2015). Human photoplethysmogram: new insight into chaotic characteristics. Chaos Solitons & Fractals, 77, 53–63.
  • Takacs, J., Pollock, C.L., Guenther, J.R., Bahar, M., Napier, C., Hunt, M.A. (2014). Validation of the Fitbit One activity monitor device during treadmill walking. Journal of Science and Medicine in Sport, 17, 496±500. https://doi.org/10.1016/j.jsams.2013.10.241 PMID: 24268570
  • Tamura, T., Maeda, Y., Sekine., M., et al. (2014). Wearable photoplethysmographic sensors—past and present. Electronics, 3, 282–302.
  • Teng, X.F., Zhang, Y.T. (2004). The effect of contacting force on photoplethysmographic signals. Physiological Measurement, 25, 1323-1335.
  • Wallen, M. P., Gomersall, S. R., Keating, S. E., Wisløff, U., Coombes, J. S., Calbet, J. A. L. (2016). Accuracy of heart rate watches: Implications for weight management. PLoS One, 11(5), e0154420. doi:10.1371/journal.pone.0154420
  • Wang, C., Li, Z., Wei, X.. (2013). Monitoring heart and respiratory rates at radial artery based on PPG. Opt Int J Light Electron Opt., 124(4), 3954–3956.
  • Wright, S.P., Brown, T.S.H., Collier, S.R., Sandberg, K. (2017). How consumer physical activity monitors could transform human physiology research. American Journal of PhysiologyÐRegulatory, Integrative and Comparative Physiology, 312. https://doi.org/10.1152/ajpregu.00349.2016 PMID: 28052867
  • Yang, Bai., Paul, Hibbing., Constantine, Mantis., Gregory, J. Welk. (2018). Comparative evaluation of heart rate-based monitors: Apple Watch vs Fitbit Charge HR. Journal of Sports Sciences, 36, 1734-1741, doi:10.1080/02640414.2017.1412235
  • Zhang, Y., Liu, B., Zhang, Z. (2015). Combining ensemble empirical mode decomposition with spectrum subtraction technique for heart rate monitoring using wrist-type photoplethysmography. Biomed Signal Process Control, 21, 119–125.
  • Zhang, Z., Pi, Z., Liu, B. (2015). Troika: a general framework for heart rate monitoring using wrist-type photoplethysmographic signals during intensive physical exercise. IEEE Trans Biomed Eng, 62(2), 522–531.
There are 31 citations in total.

Details

Primary Language Turkish
Subjects Sports Medicine
Journal Section Research Article
Authors

Oğulhan Kayabaş 0000-0003-2531-1107

Mutlu Cuğ 0000-0002-1265-0073

Cemalettin Budak 0000-0002-7119-9235

Publication Date March 30, 2022
Published in Issue Year 2022

Cite

APA Kayabaş, O., Cuğ, M., & Budak, C. (2022). FOTOPLETİSMOGRAFİ TEKNOLOJİSİNE DAYALI KALP ATIM HIZI ÖLÇÜMÜ YAPAN GİYİLEBİLİR AKILLI SAATLERİN KARŞILAŞTIRMALI DEĞERLENDİRİLMESİ: HUAWEI HONOR BAND 5 VS XIAOMI MI SMART BAND 5. SPORMETRE Beden Eğitimi Ve Spor Bilimleri Dergisi, 20(1), 105-118. https://doi.org/10.33689/spormetre.1019059

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