End-stage kidney disease (ESKD) patients often face complications like anemia, malnutrition, and cardiovascular issues. Serological tests, which are uncomfortable and not frequently conducted, assist in medical assessments. A non-invasive, convenient method for determining these test results would be beneficial for monitoring patient health.

This study develops machine learning models to estimate key serological test results using non-invasive cellular bioelectrical impedance measurements, a routine procedure for ESKD patients.

The study employs two machine learning models, Support Vector Machine (SVM) and Random Forest (RF), to determine key serological tests by classifying cell bioelectrical indicators. Data from 688 patients, comprising 3,872 biochemical-bioelectrical records, were used for model validation.

Both SVM and RF models effectively categorized key serological results (albumin, phosphorus, parathyroid hormone) into low, normal, and high. RF generally outperformed SVM, except in classifying calcium levels in women.

The machine learning models effectively classified serological test results for maintenance hemodialysis patients using cellular bioelectrical indicators, therefore can help in making judgments about physicochemical indicators using electrical signals, thereby reducing the frequency of serological tests.

Instrument-assisted soft tissue mobilization (IASTM) is thought to alter fluid dynamics in human soft tissue. The aim of this study was to investigate the influence of IASTM on the thoracolumbar fascia (TLF) on the water content of the lumbar myofascial tissue.

In total, 21 healthy volunteers were treated with IASTM. Before and after the procedure and 5 and 10 min later, lumbar bioimpedance was measured by bioimpedance analysis (BIA) and TLF stiffness was measured by indentometry. Tissue temperature was recorded at the measurement time points using an infrared thermometer.

Bioimpedance increased significantly from 58.3 to 60.4 Ω (p < 0.001) at 10-min follow-up after the treatment. Temperature increased significantly from 36.3 to 36.6 °C from 5 to 10 min after treatment (p = 0.029), while lumbar myofascial stiffness did not change significantly (p = 0.84).

After the IASTM intervention, there was a significant increase in bioimpedance, which was likely due to a decrease in water content in myofascial lumbar tissue. Further studies in a randomized control trial design are needed to extrapolate the results in healthy subjects to a symptomatic population as well and to confirm the reliability of BIA in myofascial tissue.

Body composition assessment is a relevant element in the biomedical field, in research and daily practice in the medical and nutritional fields, and in the management of athletes. This paper aimed to operate in an Italian sample investigating the possibility of predicting the somatotype from bioimpedance analysis and comparing the predicted results with those obtained from anthropometric measurements. This observational study was conducted with retrospective data collected from 2827 subjects. The somatotype of each subject was calculated both with the Heath−Carter method and by a multiple regression model based on bioimpedance and anthropometric parameters. Somatotypes (endomorph, mesomorph, and ectomorph) were predicted with a high goodness of fit (R2 adjusted > 0.80). Two different somatocharts were obtained from anthropometric measures and bioimpedance parameters and subsequentially compared. Bland−Altman plots showed acceptable accuracy. This study could be a first step in developing a new approach that allows the detection of a subject’s somatotype via bioimpedance analysis, stratified according to sex, with a time-saving and more standardized procedure. It would allow, for example, during the COVID-19 pandemic, to minimize operator−patient contact in having measurements.

Understanding the effects of acute feeding on body composition and metabolic measures is essential to the translational component and practical application of measurement and clinical use. To investigate the influence of acute feeding on the validity of dual-energy X-ray absorptiometry (DXA), a four-compartment model (4C) and indirect calorimetry metabolic outcomes, thirty-nine healthy young adults (n 19 females; age: 21·8 (sd 3·1) years, weight; 71·5 (sd 10·0) kg) participated in a randomised cross-over study. Subjects were provided one of four randomised meals on separate occasions (high carbohydrate, high protein, ad libitum or fasted baseline) prior to body composition and metabolic assessments. Regardless of macronutrient content, acute feeding increased DXA percent body fat (%fat) for the total sample and females (average constant error (CE):-0·30 %; total error (TE): 2·34 %), although not significant (P = 0·062); the error in males was minimal (CE: 0·11 %; TE: 0·86 %). DXA fat mass (CE: 0·26 kg; TE: 0·75 kg) and lean mass (LM) (CE: 0·83 kg; TE: 1·23 kg) were not altered beyond measurement error for the total sample. 4C %fat was significantly impacted from all acute feedings (avg CE: 0·46 %; TE: 3·7 %). 4C fat mass (CE: 0·71 kg; TE: 3·38 kg) and fat-free mass (CE: 0·55 kg; TE: 3·05 kg) exceeded measurement error for the total sample. RMR was increased for each feeding condition (TE: 1666·9 kJ/d; 398 kcal/d). Standard pre-testing fasting guidelines may be important when evaluating DXA and 4C %fat, whereas additional DXA variables (fat mass and LM) may not be significantly impacted by an acute meal. Measuring body composition via DXA under less stringent pre-testing guidelines may be valid and increase feasibility of testing in clinical settings.

Bioelectrical impedance vector analysis (BIVA) is a technique used for the assessment of body composition based on the electrical properties of biological tissues and for evaluating variations related to hydration and nutrition status changes. The present study aimed to investigate the possibility of predicting performance status and injuries using segmental BIVA analysis. Data were collected from 14 professional male athletes aged between 20 and 39 years of Caucasian and Afro-American ethnicity belonging to the US Victoria Libertas Pallacanestro Pesaro team in the Italian Serie A basketball championship. From an analysis of training injuries, the data highlight a possible positive link between the number of training injuries and upper hemisoma reactance (XCEmsSup) (t = 2.881, p = 0.007), an inverse relationship between training injury duration and higher right lower limb reactance (XCLegDx) (t = −4.213, p < 0.001), and an inverse relationship between injury duration and higher body mass index (t = −4.213, p < 0.001), highlighting how higher cellularity seems less prone to severe training injuries. Analyzing match-day injuries, right upper-limb higher reactance (XCArmdx) negatively correlates with match-day number of injuries (t = −4.469, p < 0.001), right upper limb resistance (RZArmDx) negatively correlates with lower match-day injury duration (t = −4.202, p < 0.001), and trunk resistance (RZTrunk) positive correlates with lower match-day injury duration (t = 2.803, p = 0.008), in contrast with the training data analysis. Analyzing the relationship between the BIVA parameters and performance indicators, right upper limb resistance (RzArmDx) has a positive link with plus−minus (t = 2.889, p = 0.007); however, RzArmDx negatively correlates with assist number (t = −3.362, p = 0.002), and BMI is directly proportional to assist number (t = 2.254, p = 0.032). These first data suggest a good correlation between the cellularity of different body districts and the risk of injuries in training but still leave several doubts surrounding the concrete predictive potential regarding performance and injuries during competitions while considering the numerous factors involved. Further studies on BIVA and similar applications could provide tools for managing athlete health and physical integrity preservation and potentially help us better understand the factors involved in improving performance.

The present study reports the validity of multiple assessment methods for tracking changes in body composition over time and quantifies the influence of unstandardised pre-assessment procedures. Resistance-trained males underwent 6 weeks of structured resistance training alongside a hyperenergetic diet, with four total body composition evaluations. Pre-intervention, body composition was estimated in standardised (i.e. overnight fasted and rested) and unstandardised (i.e. no control over pre-assessment activities) conditions within a single day. The same assessments were repeated post-intervention, and body composition changes were estimated from all possible combinations of pre-intervention and post-intervention data. Assessment methods included dual-energy X-ray absorptiometry (DXA), air displacement plethysmography, three-dimensional optical imaging, single- and multi-frequency bioelectrical impedance analysis, bioimpedance spectroscopy and multi-component models. Data were analysed using equivalence testing, Bland-Altman analysis, Friedman tests and validity metrics. Most methods demonstrated meaningful errors when unstandardised conditions were present pre- and/or post-intervention, resulting in blunted or exaggerated changes relative to true body composition changes. However, some methods - particularly DXA and select digital anthropometry techniques - were more robust to a lack of standardisation. In standardised conditions, methods exhibiting the highest overall agreement with the four-component model were other multi-component models, select bioimpedance technologies, DXA and select digital anthropometry techniques. Although specific methods varied, the present study broadly demonstrates the importance of controlling and documenting standardisation procedures prior to body composition assessments across distinct assessment technologies, particularly for longitudinal investigations. Additionally, there are meaningful differences in the ability of common methods to track longitudinal body composition changes.

To evaluate body composition, fat distribution, and metabolism at rest and during exercise in premenopausal, perimenopausal, and postmenopausal women.

This cross-sectional study in 72 women ages 35 to 60 years evaluated body composition via a fourcompartment model, fat distribution using dual-energy x-ray absorptiometry-derived android to gynoid ratio, metabolic measures via indirect calorimetry, and lifestyle factors using surveys. One-way analyses of variance and one-way analyses of covariance covaried for age and hormone levels (estrogen and progesterone) were used to compare groups.

Body fat percent was significantly lower in premenopausal than perimenopausal women (mean difference ± standard error: - 10.29 ± 2.73%, P = 0.026) despite similarities in fat mass and fat-free mass between groups (P≥0.217). Android to gynoid ratio was significantly lower in premenopausal than perimenopausal women (MD ± SE: -0.16 ± 0.05 a.u., P = 0.031). Resting energy expenditure was similar between groups (P = 0.999). Fat oxidation during moderate intensity cycle ergometer exercise was significantly greater in premenopausal than postmenopausal women (MD ± SE: 0.09 ± 0.03 g/min, P = 0.045). The change in respiratory exchange ratio between rest and moderate intensity exercise was significantly lower in premenopausal women than peri- (MD ± SE: -0.05 ± 0.03 a.u., P = 0.035) and postmenopausal women (MD ± SE: -0.06 ± 0.03 a.u., P = 0.040). Premenopausal women reported significantly fewer menopause symptoms than peri- (MD ± SE: -6.58 ± 1.52 symptoms, P = 0.002) and postmenopausal participants (MD ± SE: -4.63 ± 1.52 symptoms, P = 0.044), while similarities between groups were observed for lifestyle factors including diet and physical activity (P>0.999).

Perimenopause may be the most opportune window for lifestyle intervention, as this group experienced the onset of unfavorable body composition and metabolic characteristics.

http://links.lww.com/MENO/A932.

This study aimed to identify the effects of early follicular (EF) and midfollicular (MF) menstrual phases on body composition, resting metabolic rate (RMR), and respiratory quotient (RQ) assessment accuracy to identify an optimal testing period.

Body composition was obtained from a four-compartment (4C) criterion model (fat mass (FM), fat-free mass, body fat percent, and dual-energy x-ray absorptiometry (DXA; FM, lean mass (LM), trunk FM, and trunk LM) in 19 eumenorrheic females (mean ± SD: age, 21.3 ± 3.1 yr, body mass index, 23.6 ± 1.8 kg·m-2). RMR (kcal·d-1) and RQ (a.u.) were measured via indirect calorimetry for 25 min. Body composition, RMR, and RQ were measured during the EF and MF phases. Dependent-samples t-tests were used to compare outcomes between EF and MF.

4C outcomes were similar between phases (P > 0.05). During EF, the following 4C components were significantly greater (P < 0.05): body volume (mean difference (MD) ± SD, 0.70 ± 1.05 L), extracellular fluid (MD ± SD, 0.27 ± 0.51 L), and body mass (MD ± SD, 0.56 ± 0.80 kg). DXA-measured LM, body fat percent, trunk LM, and trunk FM were similar (P > 0.05); however, DXA FM was significantly greater during EF (MD ± SD, 0.29 ± 0.40 kg; P = 0.005), yet within measurement error of the device. Although RMR was not significantly different between phases (MD ± SD, 6.0 ± 190.93 kcal·d-1; P > 0.05), RQ was significantly higher during EF (mean ± SD, 0.03 ± 0.06 a.u.; P = 0.029) compared with MF.

Body composition from 4C and DXA do not seem to be affected beyond measurement error as a result of compartmental changes from the menstrual cycle. During MF, women oxidized more fat as demonstrated by a lower RQ. Researchers should aim to be more inclusive and schedule testing for females within 11-12 d from the onset of menstruation.

Electrophysiological sensing of cardiomyocytes (CMs) in optogenetic preparations applies various techniques, such as patch-clamp, microelectrode array, and optical mapping. However, challenges remain in decreasing the cost, system dimensions, and operating skills required for these technologies.

This study developed a low-cost, portable impedance plethysmography (IPG)-based electrophysiological measurement of cultured CMs for optogenetic applications.

To validate the efficacy of the proposed sensor, optogenetic stimulation with different pacing cycle lengths (PCL) was performed to evaluate whether the channelrhodopsin-2 (ChR2)-expressing CM beating rhythm measured by the IPG sensor was consistent with biological responses.

The experimental results show that the CM field potential was synchronized with external optical pacing with PCLs ranging from 250 ms to 1000 ms. Moreover, irregular fibrillating waveforms induced by CM arrhythmia were detected after overdrive optical pacing. Through the combined evidence of the theoretical model and experimental results, this study confirmed the feasibility of long-term electrophysiological sensing for optogenetic CMs.

This study proposes an IPG-based sensor that is low-cost, portable, and requires low-operating skills to perform real-time CM field potential measurement in response to optogenetic stimulation.

This study demonstrates a new methodology for convenient electrophysiological sensing of CMs in optogenetic applications.

Multi-frequency bioelectrical impedance analysis (MF-BIA) offers enhanced body composition outcomes in a time-efficient manner. The accuracy of stand-up MF-BIA compared against a four-compartment (4C) criterion lacks evidence.

To validate a stand-up MF-BIA compared to a 4C criterion for fat mass (FM), fat-free mass (FFM) and body fat percentage (%fat).

Eighty-two healthy (32% men) normal-weight (BMI: 18.5-24.9 kg/m² ) young adults were measured for body composition determined from a stand-up MF-BIA and 4C model. Validity statistics included total error (TE) and standard error of the estimate (SEE) to examine prediction error between methods.

For the total sample, prediction error was the highest for %fat (TE = 4.2%; SEE = 3.9%) followed by FM (TE = 2.4 kg; SEE = 2.2 kg) and FFM (TE = 2.4 kg; SEE = 2.2 kg). In men, %fat (TE = 2.5%; SEE = 2.2%) and FM (TE = 1.9 kg; SEE = 1.6 kg) were ideal; FFM was similar to FM (TE = 1.9 kg; SEE = 1.6 kg). In women, %fat (TE = 4.7%; SEE = 4.4%) ranged from good to fairly good, and FM was very good to excellent (TE = 2.6 kg; SEE = 2.4 kg); FFM was similar to FM (TE = 2.6 kg; SEE = 2.3 kg).

Stand-up MF-BIA may overestimate %fat and FM, and underestimate FFM compared to a 4C model. FM and FFM estimates from MF-BIA demonstrate good agreement to a 4C model and may be a practical measure of body composition in normal-weight adults. The highest error was seen in %fat for both sexes, with greater error in women.

The kidney is central for maintaining water balance. As a corollary, patients with impaired kidney function are prone to pathological fluid volumes. Total body water (TBW) is distributed between the extracellular (ECW) and intracellular fluid compartments (ICW). In clinical practice, the judgment of hydration status does not allow to distinguish between ECW and ICW. Here, we evaluate the hydration status in children with chronic kidney disease by analyzing TBW, ECW, and ICW.

Hydration was quantified using whole-body bioimpedance spectroscopy (BCM) in 128 outpatients (1-25 years, 52 girls). Forty-two were transplanted (TPL), 43 suffered from chronic kidney disease without kidney replacement therapy (CKD), 21 were on peritoneal dialysis (PD), and 22 on hemodialysis (HD). HD patients were investigated before, after, and sequentially during dialysis.

The ECW and ICW values obtained by BCM were of the same magnitude as those from the literature using isotope dilution. When compared with a healthy control group, TBW was increased in 9 TPL, 9 CKD, 1 PD, and 11 HD patients before but in none after dialysis. The decline of overhydration during dialysis (p < 0.001, n = 22) correlated with the change in body weight (R² = 0.62). The kinetics of fluid compartment changes assessed twice in six HD patients revealed a reproducible linear decay of the ECW/ICW ratio due to an increase of ICW and a decrease of ECW.

BCM quantifies TBW and acute changes of ECW and ICW in children with chronic kidney failure. The clinical utility of measuring TBW, ECW, and ICW should be defined in the future.

Body composition assessment has large variability. A dual-energy x-ray absorptiometry (DXA) derived four compartment (4C) method has been developed as an accurate and reliable method for assessing body composition in overweight/obese adults. This investigation was aimed at understanding the validity of the DXA-derived 4C equation for use in normal weight individuals, stratified by sex, and with varied levels of lean mass. Values were also compared against DXA alone.

78 men and women (68% female; Mean ± SD; Age: 19.2 ± 1.2 yrs; Ht: 168.8 ± 9.1 cm; Wt: 62.8 ± kg) completed a traditional 4C body composition reference assessment. Body composition was also assessed using a DXA-4C model. Validity was evaluated from total error (TE), constant error, and standard error of the estimate (SEE). Proportional bias was identified with Bland Altman plots.

Although significantly different (p < 0.05) the DXA-4C model produced ideal TE and SEE compared to the 4C criterion for all body composition outcomes of fat mass (TE: 2.1 kg; SEE: 1.9 kg), lean mass (TE: 2.1 kg; SEE: 1.8 kg), and percent body fat (TE: 3.6%; SEE: 3.4%). Validity results did not differ for men vs. women. DXA-4C estimates were slightly better in individuals with higher lean mass. DXA alone resulted in significantly greater error than DXA-4C (p < 0.05).

Body composition assessed from DXA-4C is an accurate approach, particularly in those with high levels of lean mass. This model appears to be more accurate than DXA alone.

This study reports the validity of body fat percentage (BF%) estimates from several commonly employed techniques as compared with a five-component (5C) model criterion. Healthy adults (n 170) were assessed by dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), multiple bioimpedance techniques and optical scanning. Output was also used to produce a criterion 5C model, multiple variants of three- and four-component models (3C; 4C) and anthropometry-based BF% estimates. Linear regression, Bland-Altman analysis and equivalence testing were performed alongside evaluation of the constant error (CE), total error (TE), se of the estimate (SEE) and coefficient of determination (R2). The major findings were (1) differences between 5C, 4C and 3C models utilising the same body volume (BV) and total body water (TBW) estimates are negligible (CE ≤ 0·2 %; SEE < 0·5 %; TE ≤ 0·5 %; R2 1·00; 95 % limits of agreement (LOA) ≤ 0·9 %); (2) moderate errors from alternate TBW or BV estimates in multi-component models were observed (CE ≤ 1·3 %; SEE ≤ 2·1 %; TE ≤ 2·2 %; R2 ≥ 0·95; 95 % LOA ≤ 4·2 %); (3) small differences between alternate DXA (i.e. tissue v. region) and ADP (i.e. Siri v. Brozek equations) estimates were observed, and both techniques generally performed well (CE < 3·0 %; SEE ≤ 2·3 %; TE ≤ 3·6 %; R2 ≥ 0·88; 95 % LOA ≤ 4·8 %); (4) bioimpedance technologies performed well but exhibited larger individual-level errors (CE < 1·0 %; SEE ≤ 3·1 %; TE ≤ 3·3 %; R2 ≥ 0·94; 95 % LOA ≤ 6·2 %) and (5) anthropometric equations generally performed poorly (CE 0·6- 5·7 %; SEE ≤ 5·1 %; TE ≤ 7·4 %; R2 ≥ 0·67; 95 % LOA ≤ 10·6 %). Collectively, the data presented in this manuscript can aid researchers and clinicians in selecting an appropriate body composition assessment method and understanding the associated errors when compared with a reference multi-component model.

(1) Background: millions of people, from children to the elderly, suffer from bladder dysfunctions all over the world. Monitoring bladder fullness with appropriate miniaturized textile devices can improve, significantly, their daily life quality, or even cure them. Amongst the existing bladder sensing technologies, bioimpedance spectroscopy seems to be the most appropriate one to be integrated into textiles. (2) Methods: to assess the feasibility of monitoring the bladder fullness with textile-based bioimpedance spectroscopy; an innovative lab-bench has been designed and fabricated. As a step towards obtaining a more realistic pelvic phantom, ex vivo pig's bladder and skin were used. The electrical properties of the fabricated pelvic phantom have been compared to those of two individuals with tetrapolar impedance measurements. The measurements' reproducibility on the lab bench has been evaluated and discussed. Moreover, its suitability for the continuous monitoring of the bladder filling has been investigated. (3) Results: although the pelvic phantom failed in reproducing the frequency-dependent electrical properties of human tissues, it was found to be suitable at 5 kHz to record bladder volume change. The resistance variations recorded are proportional to the conductivity of the liquid filling the bladder. A 350 mL filling with artificial urine corresponds to a decrease in resistance of 7.2%, which was found to be in the same range as in humans. (4) Conclusions: based on that resistance variation; the instantaneous bladder fullness can be extrapolated. The presented lab-bench will be used to evaluate the ability of textiles electrodes to unobtrusively monitor the bladder volume.

To evaluate the performance of five different types of textiles as band electrodes for calf bioimpedance measurements in comparison with conventional spot Ag/AgCl electrodes.

Calf bioimpedance measurements were performed in 10 healthy volunteers with five different textile materials cut into bands and Ag/AgCl spot electrodes as a baseline. Collected bioimpedance data were analyzed in terms of precision, fit error and presence of measurement artifacts. Each textile material was also evaluated for participant comfort.

Bioimpedance values for spot electrodes were higher at low frequencies as compared with band electrodes but not at high frequencies. This suggests that spot electrodes have frequency dependent current distributions that adversely impact their use for volume measurements and band electrodes are preferable. The SMP130T-B fabric had the highest precision and the lowest best fit error to the Cole model of the tested textile materials. However, it was the least comfortable textile and most expensive. The Stretch material performed slightly worse than the SMP130T-B fabric, but was half the cost and the most comfortable.

These results suggest that there are suitable textile materials for use as dry, band electrodes for calf bioimpedance measurements and that these band electrodes enable greater current uniformity. These textiles could be integrated into a compression sock for remote monitoring of diseases such as Congestive Heart Failure.

Although the need to assess hydration is well recognized, laboratory tests and clinical impressions are impractical and lack sensitivity, respectively, to be clinically meaningful. Different approaches use bioelectrical impedance measurements to overcome some of these limitations and aid in the classification of hydration status. One indirect approach utilizes single or multiple frequency bioimpedance in regression equations and theoretical models, respectively, with anthropometric measurements to predict fluid volumes (bioelectrical impedance spectroscopy-BIS) and estimate fluid overload based on the deviation of calculated to reference extracellular fluid volume. Alternatively, bioimpedance vector analysis (BIVA) uses direct phase-sensitive measurements of resistance and reactance, measured at 50 kHz, normalized for standing height, then plotted on a bivariate graph, resulting in a vector with length related to fluid content, and direction with phase angle that indexes hydration status. Comparison with healthy population norms enables BIVA to classify (normal, under-, and over-) and rank (change relative to pre-treatment) hydration independent of body weight. Each approach has wide-ranging uses in evaluation and management of clinical groups with over-hydration with an evolving emphasis on prognosis. This review discusses the advantages and limitations of BIS and BIVA for hydration assessment with comments on future applications.

Chronic volume overload is associated with left ventricular hypertrophy and high cardiovascular mortality in patients undergoing dialysis. Therefore, estimating body fluid status is important in these patients. However, most dry-weight assessments are still performed clinically, while attempts have been made to measure the volume status and dry weight of patients undergoing dialysis using bioimpedance analysis (BIA). BIA uses the electrical properties of the human body to alternate current flow and measures resistance values to estimate body water content and composition. BIA is divided into single-frequency BIA, multi-frequency BIA, and bioimpedance spectroscopy (BIS) according to the number of frequencies used, and into whole-body and segmental BIA according to whether or not the whole body is divided into segments. Extracellular water (ECW), intracellular water, and total body water (TBW) contents can be measured with BIA. Dry weight can be estimated by measuring the volume overload of the patient through the ECW/TBW and ECW-to-body weight ratios. Other estimation methods include the normovolemia/hypervolemia slope method, a resistance-reactance (RXc) graph, overhydration measurements using a body composition monitor, and calf BIS. In this review, we will examine the principles of BIA, introduce various volume status measurement methods, and identify the optimal method for patients undergoing dialysis.

The regulation of body fluid balance is a key concern in health and disease and comprises three concepts. The first concept pertains to the relationship between total body water (TBW) and total effective solute and is expressed in terms of the tonicity of the body fluids. Disturbances in tonicity are the main factor responsible for changes in cell volume, which can critically affect brain cell function and survival. Solutes distributed almost exclusively in the extracellular compartment (mainly sodium salts) and in the intracellular compartment (mainly potassium salts) contribute to tonicity, while solutes distributed in TBW have no effect on tonicity. The second body fluid balance concept relates to the regulation and measurement of abnormalities of sodium salt balance and extracellular volume. Estimation of extracellular volume is more complex and error prone than measurement of TBW. A key function of extracellular volume, which is defined as the effective arterial blood volume (EABV), is to ensure adequate perfusion of cells and organs. Other factors, including cardiac output, total and regional capacity of both arteries and veins, Starling forces in the capillaries, and gravity also affect the EABV. Collectively, these factors interact closely with extracellular volume and some of them undergo substantial changes in certain acute and chronic severe illnesses. Their changes result not only in extracellular volume expansion, but in the need for a larger extracellular volume compared with that of healthy individuals. Assessing extracellular volume in severe illness is challenging because the estimates of this volume by commonly used methods are prone to large errors in many illnesses. In addition, the optimal extracellular volume may vary from illness to illness, is only partially based on volume measurements by traditional methods, and has not been determined for each illness. Further research is needed to determine optimal extracellular volume levels in several illnesses. For these reasons, extracellular volume in severe illness merits a separate third concept of body fluid balance.

In recent years, many efforts have been made to promote a healthcare paradigm shift from the traditional reactive hospital-centered healthcare approach towards a proactive, patient-oriented, and self-managed approach that could improve service quality and help reduce costs while contributing to sustainability. Managing and caring for patients with chronic diseases accounts over 75% of healthcare costs in developed countries. One of the most resource demanding diseases is chronic kidney disease (CKD), which often leads to a gradual and irreparable loss of renal function, with up to 12% of the population showing signs of different stages of this disease. Peritoneal dialysis and home haemodialysis are life-saving home-based renal replacement treatments that, compared to conventional in-center hemodialysis, provide similar long-term patient survival, less restrictions of life-style, such as a more flexible diet, and better flexibility in terms of treatment options and locations. Bioimpedance has been largely used clinically for decades in nutrition for assessing body fluid distributions. Moreover, bioimpedance methods are used to assess the overhydratation state of CKD patients, allowing clinicians to estimate the amount of fluid that should be removed by ultrafiltration. In this work, the initial validation of a handheld bioimpedance system for the assessment of body fluid status that could be used to assist the patient in home-based CKD treatments is presented. The body fluid monitoring system comprises a custom-made handheld tetrapolar bioimpedance spectrometer and a textile-based electrode garment for total body fluid assessment. The system performance was evaluated against the same measurements acquired using a commercial bioimpedance spectrometer for medical use on several voluntary subjects. The analysis of the measurement results and the comparison of the fluid estimations indicated that both devices are equivalent from a measurement performance perspective, allowing for its use on ubiquitous e-healthcare dialysis solutions.