Literature DB >> 8872654

Effect of skin temperature on multifrequency bioelectrical impedance analysis.

R Gudivaka1, D Schoeller, R F Kushner.   

Abstract

This study assessed the effects of changes in skin temperature on multifrequency bioimpedance analysis (MF-BIA) and on the prediction of body water compartments. Skin temperature (baseline 29.3 +/- 2.1 degrees C) of six healthy adults was raised over 50 min to 35.8 +/- 0.6 degrees C, followed by cooling for 20 min to 26.9 +/- 1.3 degrees C, by using an external heating and cooling blanket. MF-BIA was measured at both distal (conventional) and proximal electrode placements. Both distal and proximal impedance varied inversely with a change in skin temperature across all frequencies (5-500 kHz). The change in proximal impedance per degree centigrade change in skin surface temperature was approximately 60% of distal impedance. The change in measured impedance at 50 kHz erroneously increased predicted total body water (TBW) by 2.6 +/- 0.9 liters (P < 0.001) and underpredicted fat mass by 3.3 +/- 1.3 kg (P < 0.0001). Computer modeling of the MF-BIA data indicated changes in predicted water compartments with temperature modifications; however, the ratio of extracellular water (ECW) to TBW did not significantly change (P < 0.4). This change in impedance was not due to a change in the movement of water of the ECW compartment and thus probably represents a change in cutaneous impedance of the skin. Controlled ambient and skin temperatures should be included in the standardization of BIA measurements. The error in predicted TBW is < 1% within an ambient temperature range of 22.3 to 27.7 degrees C (72.1-81.9 degrees F).

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Year:  1996        PMID: 8872654     DOI: 10.1152/jappl.1996.81.2.838

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  11 in total

1.  The compensation of perturbing temperature fluctuation in glucose monitoring technologies based on impedance spectroscopy.

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Journal:  Med Biol Eng Comput       Date:  2007-07-28       Impact factor: 2.602

2.  Noninvasive glucose monitoring: a novel approach.

Authors:  Ilana Harman-Boehm; Avner Gal; Alexander M Raykhman; Jeffrey D Zahn; Eugene Naidis; Yulia Mayzel
Journal:  J Diabetes Sci Technol       Date:  2009-03-01

3.  Noninvasive glucose monitoring: increasing accuracy by combination of multi-technology and multi-sensors.

Authors:  Ilana Harman-Boehm; Avner Gal; Alexander M Raykhman; Eugene Naidis; Yulia Mayzel
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

4.  Effects of Heat Exposure on Body Water Assessed using Single-Frequency Bioelectrical Impedance Analysis and Bioimpedance Spectroscopy.

Authors:  Brett S Nickerson; Michael R Esco; Phillip A Bishop; Brian M Kliszczewicz; Henry N Williford; Kyung-Shin Park; Bailey A Welborn; Ronald L Snarr; Danilo V Tolusso
Journal:  Int J Exerc Sci       Date:  2017-11-01

5.  Ratiometric Impedance Sensing of Fingers for Robust Identity Authentication.

Authors:  Hyung Wook Noh; Chang-Geun Ahn; Hyoun-Joong Kong; Joo Yong Sim
Journal:  Sci Rep       Date:  2019-09-19       Impact factor: 4.379

6.  Electrical Impedance of Upper Limb Enables Robust Wearable Identity Recognition against Variation in Finger Placement and Environmental Factors.

Authors:  Hyung Wook Noh; Joo Yong Sim; Chang-Geun Ahn; Yunseo Ku
Journal:  Biosensors (Basel)       Date:  2021-10-16

Review 7.  Is bioelectrical impedance accurate for use in large epidemiological studies?

Authors:  Mahshid Dehghan; Anwar T Merchant
Journal:  Nutr J       Date:  2008-09-09       Impact factor: 3.271

8.  Wearable Multi-Frequency and Multi-Segment Bioelectrical Impedance Spectroscopy for Unobtrusively Tracking Body Fluid Shifts during Physical Activity in Real-Field Applications: A Preliminary Study.

Authors:  Federica Villa; Alessandro Magnani; Martina A Maggioni; Alexander Stahn; Susanna Rampichini; Giampiero Merati; Paolo Castiglioni
Journal:  Sensors (Basel)       Date:  2016-05-11       Impact factor: 3.576

9.  Prediction and discrimination of skeletal muscle function by bioelectrical impedance vector analysis using a standing impedance analyzer in healthy Taiwanese adults.

Authors:  Li-Wen Lee; Hsueh-Kuan Lu; Yu-Yawn Chen; Chung-Liang Lai; Lee-Ping Chu; Meng-Che Hsieh; Kuen-Chang Hsieh
Journal:  PLoS One       Date:  2020-06-12       Impact factor: 3.240

10.  Differences in Fat Mass Estimation Formulas in Physically Active Adult Population and Relationship with Sums of Skinfolds.

Authors:  Raquel Vaquero-Cristóbal; Mario Albaladejo-Saura; Ana E Luna-Badachi; Francisco Esparza-Ros
Journal:  Int J Environ Res Public Health       Date:  2020-10-23       Impact factor: 3.390

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