Optimization of the pseudorandom input signals used for the forced oscillation technique_Journal of Biomedical Engineering

Authors：

LIU Xiaoli ¹ , ZHANG Nan ² , LIANG Hong ² ,  ZHANG Zhengbo ^1,2 , LI Deyu ¹ , WANG Weidong ²

1. School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, P.R.China;
2. Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing 100853, P.R.China;

Corresponding author：

ZHANG Zhengbo, Email: zhengbozhang@126.com

Keywords：

forced oscillation technique; pseudorandom signals; phase; time-frequency domain swapping algorithm; amplitude-frequency characteristic

DOI：

10.7507/1001-5515.201607064

Video：

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The forced oscillation technique (FOT) is an active pulmonary function measurement technique that was applied to identify the mechanical properties of the respiratory system using external excitation signals. FOT commonly includes single frequency sine, pseudorandom and periodic impulse excitation signals. Aiming at preventing the time-domain amplitude overshoot that might exist in the acquisition of combined multi sinusoidal pseudorandom signals, this paper studied the phase optimization of pseudorandom signals. We tried two methods including the random phase combination and time-frequency domain swapping algorithm to solve this problem, and used the crest factor to estimate the effect of optimization. Furthermore, in order to make the pseudorandom signals met the requirement of the respiratory system identification in 4–40 Hz, we compensated the input signals’ amplitudes at the low frequency band (4–18 Hz) according to the frequency-response curve of the oscillation unit. Resuts showed that time-frequency domain swapping algorithm could effectively optimize the phase combination of pseudorandom signals. Moreover, when the amplitudes at low frequencies were compensated, the expected stimulus signals which met the performance requirements were obtained eventually.

Citation： LIU Xiaoli, ZHANG Nan, LIANG Hong, ZHANG Zhengbo, LI Deyu, WANG Weidong. Optimization of the pseudorandom input signals used for the forced oscillation technique. Journal of Biomedical Engineering, 2017, 34(5): 660-666. doi: 10.7507/1001-5515.201607064 Copy

1.	Dubois A B, Brody A W, Lewis D H, et al. Oscillation mechanics of lungs and chest in man. J Appl Physiol, 1956, 8(6): 587-594.
2.	Oostveen E, Macleod D, Lorino H, et al. The forced oscillation technique in clinical practice: methodology, recommendations and future developments. Eur Respir J, 2003, 22(6): 1026-1041.
3.	张政波, 倪路, 刘晓莉, 等. 振荡肺功能原理及技术实现. 中国医疗器械杂志, 2015, 39(6): 432-436.0.
4.	Lappas A S, Tzortzi A, Behrakis P K. Forced oscillations in applied respiratory physiology: Clinical applications. Clinical Research, 2014, 2: 1016-1033.
5.	Willim G, Tomalak W, Stankiewick J, et al. Forced oscillations technique in evaluating state of the respiratory system in children with chronic lung diseases. European Respiratory Journal, 1997, 10: 328s.
6.	Beydon L, Malassiné P, Lorino A M, et al. Respiratory resistance by end-inspiratory occlusion and forced oscillations in intubated patients. J Appl Physiol (1985), 1996, 80(4): 1105-1111.
7.	Navajas D, Farré R, Rotger M, et al. A new estimator to minimize the error due to breathing in the measurement of respiratory impedance. IEEE Trans Biomed Eng, 1988, 35(12): 1001-1005.
8.	Shirai T, Mori K, Mikamo M, et al. Usefulness of colored 3D imaging of respiratory impedance in asthma. Allergy Asthma Immunol Res, 2013, 5(5): 322-328.
9.	Faria A C D, Silva K K D D, Costa G M D, et al. Forced oscillation technique in the detection of smoking-induced respiratory changes// Hudak R, Penhaker M, Majernik J. Biomedical engineering–Technical applications in medicine. InTech, 2012: 1-10. DOI: 10.5772/48408.
10.	Rotger M, Peslin R, Navajas D, et al. Density dependence of respiratory input impedance re-evaluated with a head generator minimizing upper airway shunt. Eur Respir J, 1988, 1(5): 439-444.
11.	Bickel S, Popler J, Lesnick B, et al. Impulse oscillometry: interpretation and practical applications. Chest, 2014, 146(3): 841-847.
12.	Daróczy B, Hantos Z. Generation of optimum pseudorandom signals for respiratory impedance measurements. Int J Biomed Comput, 1990, 25(1): 21-31.
13.	Maes H, Vandersteen G, Ionescu C. Estimation of respiratory impedance at low frequencies during spontaneous breathing using the forced oscillation technique. Conf Proc IEEE Eng Med Biol Soc, 2014, 2014: 3410-3413.
14.	Schroeder M. Synthesis of low-peak-factor signals and binary sequences with low autocorrelation (Corresp.) IEEE Transactions on Information Theory, 1970, 16(1): 85-89.
15.	张楠, 刘晓莉, 周娟, 等. 基于强迫振荡技术的肺功能测量系统研究. 生物医学工程学杂志, 2016, 33(6): 1110-1115.0.
16.	孙建红, 伍开元. 开口圆管气体的非线性振荡研究及雾化应用. 空气动力学学报, 1997(2): 177-184.
17.	Van der Ouderaa E, Schoukens J, Renneboog J. Peak factor minimization using a time-frequency domain swapping algorithm. IEEE Transactions on Instrumentation & Measurement, 1988, 37(1): 145-147.
18.	Lorino H, Mariette C, Karouia M, et al. Influence of signal processing on estimation of respiratory impedance. J Appl Physiol (1985), 1993, 74(1): 215-223.
19.	Kaczka D W, Dellacá R L. Oscillation mechanics of the respiratory system: applications to lung disease. Crit Rev Biomed Eng, 2011, 39(4): 337-359.

1. Dubois A B, Brody A W, Lewis D H, et al. Oscillation mechanics of lungs and chest in man. J Appl Physiol, 1956, 8(6): 587-594.
2. Oostveen E, Macleod D, Lorino H, et al. The forced oscillation technique in clinical practice: methodology, recommendations and future developments. Eur Respir J, 2003, 22(6): 1026-1041.
3. 张政波, 倪路, 刘晓莉, 等. 振荡肺功能原理及技术实现. 中国医疗器械杂志, 2015, 39(6): 432-436.0.
4. Lappas A S, Tzortzi A, Behrakis P K. Forced oscillations in applied respiratory physiology: Clinical applications. Clinical Research, 2014, 2: 1016-1033.
5. Willim G, Tomalak W, Stankiewick J, et al. Forced oscillations technique in evaluating state of the respiratory system in children with chronic lung diseases. European Respiratory Journal, 1997, 10: 328s.
6. Beydon L, Malassiné P, Lorino A M, et al. Respiratory resistance by end-inspiratory occlusion and forced oscillations in intubated patients. J Appl Physiol (1985), 1996, 80(4): 1105-1111.
7. Navajas D, Farré R, Rotger M, et al. A new estimator to minimize the error due to breathing in the measurement of respiratory impedance. IEEE Trans Biomed Eng, 1988, 35(12): 1001-1005.
8. Shirai T, Mori K, Mikamo M, et al. Usefulness of colored 3D imaging of respiratory impedance in asthma. Allergy Asthma Immunol Res, 2013, 5(5): 322-328.
9. Faria A C D, Silva K K D D, Costa G M D, et al. Forced oscillation technique in the detection of smoking-induced respiratory changes// Hudak R, Penhaker M, Majernik J. Biomedical engineering–Technical applications in medicine. InTech, 2012: 1-10. DOI: 10.5772/48408.
10. Rotger M, Peslin R, Navajas D, et al. Density dependence of respiratory input impedance re-evaluated with a head generator minimizing upper airway shunt. Eur Respir J, 1988, 1(5): 439-444.
11. Bickel S, Popler J, Lesnick B, et al. Impulse oscillometry: interpretation and practical applications. Chest, 2014, 146(3): 841-847.
12. Daróczy B, Hantos Z. Generation of optimum pseudorandom signals for respiratory impedance measurements. Int J Biomed Comput, 1990, 25(1): 21-31.
13. Maes H, Vandersteen G, Ionescu C. Estimation of respiratory impedance at low frequencies during spontaneous breathing using the forced oscillation technique. Conf Proc IEEE Eng Med Biol Soc, 2014, 2014: 3410-3413.
14. Schroeder M. Synthesis of low-peak-factor signals and binary sequences with low autocorrelation (Corresp.) IEEE Transactions on Information Theory, 1970, 16(1): 85-89.
15. 张楠, 刘晓莉, 周娟, 等. 基于强迫振荡技术的肺功能测量系统研究. 生物医学工程学杂志, 2016, 33(6): 1110-1115.0.
16. 孙建红, 伍开元. 开口圆管气体的非线性振荡研究及雾化应用. 空气动力学学报, 1997(2): 177-184.
17. Van der Ouderaa E, Schoukens J, Renneboog J. Peak factor minimization using a time-frequency domain swapping algorithm. IEEE Transactions on Instrumentation & Measurement, 1988, 37(1): 145-147.
18. Lorino H, Mariette C, Karouia M, et al. Influence of signal processing on estimation of respiratory impedance. J Appl Physiol (1985), 1993, 74(1): 215-223.
19. Kaczka D W, Dellacá R L. Oscillation mechanics of the respiratory system: applications to lung disease. Crit Rev Biomed Eng, 2011, 39(4): 337-359.

Journal of Biomedical Engineering

Optimization of the pseudorandom input signals used for the forced oscillation technique

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