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Model-based correction of the influence of body position on continuous segmental and hand-to-foot bioimpedance measurements

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Abstract

Bioimpedance spectroscopy (BIS) is suitable for continuous monitoring of body water content. The combination of body posture and time is a well-known source of error, which limits the accuracy and therapeutic validity of BIS measurements. This study evaluates a model-based correction as a possible solution. For this purpose, an 11-cylinder model representing body impedance distribution is used. Each cylinder contains a nonlinear two-pool model to describe fluid redistribution due to changing body position and its influence on segmental and hand-to-foot (HF) bioimpedance measurements. A model-based correction of segmental (thigh) and HF measurements (Xitron Hydra 4200) in nine healthy human subjects (following a sequence of 7 min supine, 20 min standing, 40 min supine) has been evaluated. The model-based compensation algorithm represents a compromise between accuracy and simplicity, and reduces the influence of changes in body position on the measured extracellular resistance and extracellular fluid by up to 75 and 70%, respectively.

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Abbreviations

α:

Heuristic parameter (Cole–Cole model)

c :

Circumference

C PRO :

Protein concentration

C PRO,P :

Protein concentration in plasma

C PRO,IntF :

Protein concentration in interstitial fluid

D B :

Body density

D Muscle :

Density of muscle

IntFRel :

Relative amount of interstitial fluid

K f :

Filtration coefficient

K ECF,Muscle :

Amount of interstitial fluid per muscle mass

P C :

Capillary hydrostatic pressure

ΠC :

Capillary oncotic pressure

P IntF :

Interstitial hydrostatic pressure

ΠIntF :

Interstitial oncotic pressure

Q L,S :

Nominal lymphatic flow for a segment

Q Lymph,S :

Effective lymphatic flow for a segment

Q Rel,S :

Relative lymphatic flow

Q PI,S :

Fluid shift ratio from capillary to interstitial space

ρECF :

Specific resistivity of extracellular fluid

RV/RA:

Postcapillary to precapillary resistance ratio

R e :

Extracellular resistance

R i :

Intracellular resistance

T D :

Time delay

S:

Segment

V S :

Segmental volume

V B :

Body volume

BIS:

Bioimpedance spectroscopy

ECF:

Extracellular fluid

HF:

Hand-to-foot

ICF:

Intracellular fluid

IntF:

Interstitial fluid

PV:

Plasma volume

References

  1. Barchansky A (2007) Simulations of low-frequency electromagnetic fields in the human body. PhD thesis. Technical University Darmstadt, Germany

  2. Berg H, Tedner B, Tesch P (1993) Changes in lower limb muscle cross-sectional area and tissue fluid volume after transition from standing to supine. Acta Physiol Scand 148:379–385

    Article  CAS  PubMed  Google Scholar 

  3. Blomqvist C, Lowell H (1983) Cardiovascular adjustments to gravitational stress. In: Handbook of physiology, The cardiovascular system. Peripheral circulation and organ blood flow, sect 2, vol III, pt 2, chap 28. Am. Physiol. Soc., Bethesda, pp 1025–1063

  4. Burton A (1969) Physiologie und Biophysik des Kreislaufs. 1969. From the original Physiology and biophysics of the circulation 1965. F.K. Schattauer Verlag, Stuttgart

    Google Scholar 

  5. Chamney P, Johner C, Aldridge C, Kramer M, Valasco N, Tattersall J, Aukaidey T, Gordon R, Greenwood R (1999) Fluid balance modelling in patients with kidney failure. J Med Eng Technol 23(2):45–52

    Article  CAS  PubMed  Google Scholar 

  6. Chamney P, Wabel P, Moissl U, Müller M, Bosy-Westphal A, Korth O, Fuller N (2007) A whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J Clin Nutr 85:80–89

    CAS  PubMed  Google Scholar 

  7. Christ F, Gamble J, Baranov V, Kotov A, Garside I, Nehring I, Messmer K (1999) Microvascular fluid filtration capacity (kf) assessed with cumulative small venous pressure steps and various degrees of tilt. Eur J Med Res 4:264–270

    CAS  PubMed  Google Scholar 

  8. Drye J (1948) Intraperitoneal pressure in the human. Surg Gynecol Obstet 87:472–475

    CAS  PubMed  Google Scholar 

  9. Fenech M, Jaffrin M (2004) Extracellular and intracellular volume variations during postural change measured by segmental and wrist-ankle bioimpedance spectroscopy. IEEE Trans Biomed Eng 51(1):166–175

    Article  PubMed  Google Scholar 

  10. Fresenius Medical Care (2006) Body composition monitor (BCM). Operating instructions. Fresenius Medical Care

  11. Gamble J, Gartside I, Christ F (1993) A reassessment of Mercury in silastic strain gauge plethysmography for the microvascular permeability in man. J Physiol 464:407–422

    CAS  PubMed  Google Scholar 

  12. Guder W, Nolte J (2005) Das Laborbuch für Klinik und Praxis, 1st edn. Elsevier, München

    Google Scholar 

  13. Guyton A, Hall J (2006) Textbook of medical physiology, 11th edn. Elsevier/Saunders, USA

    Google Scholar 

  14. Guyton A, Granger H, Taylor A (1971) Interstitial pressure. Physiol Rev 51(3):527–563

    CAS  PubMed  Google Scholar 

  15. Hanai T (1968) Electrical properties of emulsions. In: Sherman P (ed) Emulsions science. Academic Press, London, pp 374–475

    Google Scholar 

  16. Hinghofer-Szalkay H, Moser M (1986) Fluid and protein shifts after postural changes in humans. Am J Physiol 250:H68–H75

    CAS  PubMed  Google Scholar 

  17. Hong KH, Lim YG, Park KS (2009) Effectiveness of thigh-to-thigh current path for the measurement of abdominal fat in bioelectrical impedance analysis. Med Biol Eng Comput 47:1265–1271

    Article  PubMed  Google Scholar 

  18. Jaffrin M, Morel H (2009) Extracellular volume measurements using bioimpedance spectroscopy-Hanai method and wrist-to-ankle resistance at 50 kHz. Med Bio Eng Comput 47:77–84

    Article  Google Scholar 

  19. Jaffrin M, Fenech M, Moreno MV, Kieffer R (2006) Total body water measurement by a modification of the bioimpedance spectroscopy method. Med Bio Eng Comput 44:873–882

    Article  Google Scholar 

  20. Klabunde R (2005) Cardiovascular physiology concepts. Ed. Lippincott Williams & Wilkins, USA

  21. Kushner R, Gudivaka R, Schoeller D (1996) Clinical characteristics influencing bioelectrical impedance analysis measurements. Am J Clin Nutr 64(3 Suppl):423–427

    Google Scholar 

  22. Landis E, Pappenheimer J (1963) Exchange of substances through the capillary walls. In: Hamilton W, Dow P (eds) Handbook of physiology. Waverly Press, Washington DC, pp 961–1034

  23. Matthie J (2005) Second generation mixture theory equation for estimating intracellular water using bioimpedance spectroscopy. J Appl Physiol 99:780–781

    Article  PubMed  Google Scholar 

  24. Maw G, Mackenzie I, Taylor N (1995) Redistribution of body fluids during postural manipulations. Acta Physiol Scand 155:157–163

    Article  CAS  PubMed  Google Scholar 

  25. Medrano G, Beckmann L, Zimmermann N, Grundmann T, Gries T, Leonhardt S (2007) Bioimpedance spectroscopy with textile electrodes for a continuous monitoring application. In: Fourth international workshop on wearable and implantable body sensor networks (BSN), Aachen, IFMBE proceedings, vol 13, pp 23–28

  26. Medrano G, Leonhardt S, Zhang P (2007) Modeling the influence of body position in bioimpedance measurements. In: Proceedings of the 29th annual international conference of the IEEE EMBS. Cité Internationale, Lyon, France, pp 3934–3937

  27. Medrano G, Eitner F, Floege J, Leonhardt S (2010) A novel bioimpedance technique to monitor fluid volume state during hemodialysis treatment. ASAIO J 56(3) (in press)

  28. Mitchell G (2009) Clinical achievements of impedance analysis. Med Biol Eng Comput 47:153–163

    Article  PubMed  Google Scholar 

  29. Moissl U, Wabel P, Chamney P, Bosaeus I, Levin N, Bosy-Westphal A, Korth O, Müller M, Ellegård L, Malmros V, Kaitwatcharachai Ch, Kuhlmann M, Zhu F, Fuller N (2006) Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas 27:921–933

    Article  PubMed  Google Scholar 

  30. Noddeland H (1982) Influence of body posture on transcapillary pressures in human subcutaneous tissue. Scand J Clin Lab Invest 42:131–138

    CAS  PubMed  Google Scholar 

  31. Oczenski W, Werba A, Andel H (1997) Breathing and mechanical support, 3rd edn. Blackwell Science, Berlin

    Google Scholar 

  32. Pappenheimer J, Soto-Rivera A (1948) Effective osmotic pressure of the plasma proteins and other quantities associated with capillary circulation in the hindlimbs of cats and dogs. Am J Physiol 152:471–491

    CAS  PubMed  Google Scholar 

  33. Paterno A, Stiz R, Bertemes-Filho P (2009) Frequency-domain reconstruction of signals in electrical bioimpedance spectroscopy. Med Bio Eng Comput 47:1093–1102

    Article  Google Scholar 

  34. Sakamoto K, Kanai H, Furuya N (2004) Electrical admittance method for estimating fluid removal during artificial dialysis. Med Biol Eng Comput 42:356–365

    Article  CAS  PubMed  Google Scholar 

  35. Scharfetter H, Monif M, László Z, Lambauer T, Hutten H, Hinghofer-Szalkay H (1997) Effect of postural changes on the reliability of volume estimations from bioimpedance spectroscopy data. Kidney Int 51:1078–1087

    Article  CAS  PubMed  Google Scholar 

  36. Skelton H (1927) The storage of water by various tissues of the body. Arch Int Med 40:140

    CAS  Google Scholar 

  37. Slinde F, Bark A, Jansson J, Rossander-Hulthén L (2003) Bioelectrical impedance variation in healthy subjects during 12 h in the supine position. Clin Nutr 22(2):153–157

    Article  CAS  PubMed  Google Scholar 

  38. Snyder W, Cook M, Nasset E, Karhausen L, Howells P, Tipton I (1975) Report of the task group on reference man, international commission on radiological protection (ICRP), report no. 23. Pergamon Press, Oxford

    Google Scholar 

  39. Winter R (1973) The body fluids in pediatrics. Medical, surgical and neonatal disorders of acid-basis status, hydration and oxigenation. Little, Brown and Company, Boston

    Google Scholar 

  40. Xitron Technologies (2001) Hydra ECF/ICF (Model 4200), Bioimpedance spectrum analyser. Operating manual, Xitron Technologies Inc., San Diego

  41. Zhu F, Schneditz D, Wang E, Levin NW (1998) Dynamics of segmental extracellular volumes during changes in body position by bioimpedance analysis. J Appl Physiol 85:497–504

    CAS  PubMed  Google Scholar 

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Acknowledgments

Special thanks go to Dr. Chamney, Dr. Wabel, and Dr. Moissl at Fresenius Medical Care GmbH for their help with the literature and for interesting discussions. This work was partially supported by the Science and Technology National Board of the Mexican government (CONACYT).

Author information

Authors and Affiliations

  1. Philips Chair for Medical Information Technology (MedIT), Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, Germany

    Guillermo Medrano, Marian Walter & Steffen Leonhardt

  2. Department of Nephrology (Medical Clinic II), University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany

    Frank Eitner

Authors
  1. Guillermo Medrano
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Corresponding author

Correspondence to Guillermo Medrano.

Appendix

Appendix

1.1 Calculation of P IntF for the torso

Fluid shifts from the legs to the torso for the change of vertical to supine position, and vice versa, as observed through bioimpedance [9, 35, 41] and computer tomography [2] measurements. Accordingly, fluid in the torso should flow from the capillaries into the interstitium during supine position and in the opposite direction during standing position. Values reported for the chest (lungs capillaries) [13] were taken to capture the effect of Starling’s forces in the torso, resulting in the right direction during supine (Fig. 6a, left), but in the opposite direction during standing position (Fig. 6a, right).

Fig. 6
figure 6

Starling’s forces in the torso (in mmHg, signs have been represented as directions) and expected and produced direction of the fluid shift between interstitial and capillary spaces for supine and standing position. a ΠC, ΠIntF, and P IntF according to [13]. P C as explained in the Sect. 2.6.1. b P IntF according to analysis (see text)

Full size image

To satisfy the desired result during standing position, the following relation must be fulfilled:

$$ {P_{\text{C}} + P_{\text{IntF}} + \Uppi_{\text{IntF}} < \Uppi_{\text{C}} } $$
(22)

Equation 22 indicates that during a change from supine to standing position, a fast change in one of the pressures (in addition to the change already considered in P C) is necessary. As a fast change in ΠIntF and ΠC is not expected [16, 30] the values for P C, ΠIntF, and ΠC for the standing position can be substituted on Eq.  22:

$$ {12 + P_{\text{IntF}} + 14 < 28\;({\text{mmHg)}}} $$
(23)
$$ {P_{\text{IntF}} < 2\;({\text{mmHg}})} $$
(24)

Considering the directions of the arrows, a value of |P IntF| = 1 mmHg (physiologically −1 mmHg) during standing position was assumed. The result can be seen in Fig. 6b. Explanations for this value could be: (a) the influence of gravity in the pleura (standing position should lead to a reduction of |P IntF|) [31] or (b) an increase in the intraperitoneal pressure in the lower part of the abdomen [8], producing a reduction of |P IntF|.

1.1.1 Sensitivity analysis

The influence of model parameter values on ΔR e has been determined through simulations using nominal parameter values +10%. Anthropometric changes influenced only the initial R e value. Changes in the amount of proteins (C Pro,P) and in fluid volume state (IntF (P IntF)) present a relatively large influence on the simulated ΔR e (see details in Table 3).

Table 3 Influence of using initialisation values +10% on the simulated ΔR e (%) and R e (%)
Full size table

Suitability of the influence of different C Pro,P and IntF (P IntF) values on ΔR e:

  • As healthy C Pro,P can range from 6.5 to 7.2 g/dl (reference [38]) or even between 6.4 and 8.3 g/dl (reference [12]), which is more than +10%, this parameter may influence the differences between simulations and measurements.

  • Since a mild dehydration constitutes a loss of 3% of body weight and about 20% of ECF without presenting any clear symptoms [39], a local change of IntF by 10% is very possible and the local PIntF for each subject could vary from the assumed initial PIntF = −3 mmHg.

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Medrano, G., Eitner, F., Walter, M. et al. Model-based correction of the influence of body position on continuous segmental and hand-to-foot bioimpedance measurements. Med Biol Eng Comput 48, 531–541 (2010). https://doi.org/10.1007/s11517-010-0602-5

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