Bioimpedance measurement based evaluation of wound healing

Comparative analysis of electrochemical and optical sensors for detection of chronic wounds biomarkers: A review

Chronic wounds (CW) present a significant healthcare challenge due to their prolonged healing time and associated complications. To effectively treat these wounds and prevent further deterioration, monitoring their healing progress is crucial. Traditional wound assessment methods relying on visual inspection and subjective evaluation are prone to inter-observer variability. Biomarkers play a critical role in objectively evaluating wound status and predicting healing outcomes, providing quantitative measures of wound healing progress, inflammation, infection, and tissue regeneration. Recent attention has been devoted to identifying and validating CW biomarkers. Various studies have investigated potential biomarkers, including growth factors, cytokines, proteases, and extracellular matrix components, shedding light on the complex molecular and cellular processes within CW. This knowledge enables a more targeted and personalized approach to wound management. Accurate and sensitive techniques are necessary for detecting CW biomarkers. Thus, this review compares and discusses the use of electrochemical and optical sensors for biomarker determination. The advantages and disadvantages of these sensors are highlighted. Differences in detection capabilities and characteristics such as non-invasiveness, portability, high sensitivity, specificity, simplicity, cost-effectiveness, compatibility with point-of-care applications, and real-time monitoring of wound biomarkers will be pointed out and compared. In summary, this work provides an overview of CW, explores the emerging field of CW biomarkers, and discusses methods for detecting these biomarkers, with a specific focus on optical and electrochemical sensors. The potential of further research and development in this field for advancing wound care and improving patient outcomes will also be noted.

Differences of bioelectrical impedance in the development and healing phase of pressure ulcers and erythema in mouse model

Pressure ulcers (PUs) are economically burdensome medical conditions. Early changes in pressure ulcers are associated with erythema. In this study, bioelectrical impedance was used to measure the differences between PUs and blanchable erythema. We divided 21 ICR mice into three groups: control, 1000 mmHg-1h, and 1000 mmHg-6h. Healthy skin, blanchable erythema, and PUs were induced on the dorsal skin. The results indicated an immediate increase in impedance, resistance, and reactance values in the pressure group after release, followed by a subsequent decrease until two days after release. Compared with the control group, impedance and reactance significantly increased by 30.9% (p < 0.05) and 30.1% (p < 0.01), respectively, in the 6 h-loading group immediately after release. One and two days after release, the 1 h-loading and 6 h-loading groups exhibited significantly different degrees of decline. One day after release, impedance and resistance decreased by 30.2% (p < 0.05) and 19.8% (p < 0.05), respectively, in the 1 h-loading group; while impedance, resistance, and reactance decreased by 39.2% (p < 0.01), 26.8% (p < 0.01), and 45.7% (p < 0.05), respectively, in the 6 h-loading group. Two days after release, in the 1 h-loading group, impedance and resistance decreased by 28.3% (p < 0.05) and 21.7% (p < 0.05), respectively; while in the 6 h-loading group, impedance, resistance, and reactance decreased by 49.8% (p < 0.001), 34.2% (p < 0.001), and 59.8% (p < 0.01), respectively. One and two days after release the pressure group reductions were significantly greater than those in the control group. Additionally, we monitored changes during wound healing. Distinguishing early PUs from blanchable erythema by noninvasive bioelectrical impedance technology may have applications value in early assessment of PUs.

Wound drainage measurements: a narrative review

Drainage from chronic wounds can significantly negatively impact a patient's quality of life. Change in severity of wound drainage is an important measure of treatment efficacy for wounds. This study reviews existing tools used to assess wound drainage. Qualitative drainage tools are overall less burdensome, and however, differences in user interpretation may reduce inter-rater reliability. Quantitative drainage tools enable more reliable comparisons of drainage severity and treatment response between patients but sometimes require equipment to administer, increasing responder burden. Gaps in the current wound drainage measurement landscape are highlighted. Many of the existing scales have not been validated in robust studies. There is also a lack of validated global drainage measurement tools for patients with chronic inflammatory skin disorders with drainage, such as hidradenitis suppurativa or pyoderma gangrenosum. Development of a succinct drainage measurement tool for inflammatory skin diseases where drainage is a prominent symptom will improve monitoring of meaningful treatment response.

Biomimetic Flexible Sensors and Their Applications in Human Health Detection

Bionic flexible sensors are a new type of biosensor with high sensitivity, selectivity, stability, and reliability to achieve detection in complex natural and physiological environments. They provide efficient, energy-saving and convenient applications in medical monitoring and diagnosis, environmental monitoring, and detection and identification. Combining sensor devices with flexible substrates to imitate flexible structures in living organisms, thus enabling the detection of various physiological signals, has become a hot topic of interest. In the field of human health detection, the application of bionic flexible sensors is flourishing and will evolve into patient-centric diagnosis and treatment in the future of healthcare. In this review, we provide an up-to-date overview of bionic flexible devices for human health detection applications and a comprehensive summary of the research progress and potential of flexible sensors. First, we evaluate the working mechanisms of different classes of bionic flexible sensors, describing the selection and fabrication of bionic flexible materials and their excellent electrochemical properties; then, we introduce some interesting applications for monitoring physical, electrophysiological, chemical, and biological signals according to more segmented health fields (e.g., medical diagnosis, rehabilitation assistance, and sports monitoring). We conclude with a summary of the advantages of current results and the challenges and possible future developments.

Identifying ex vivo acute ischemic stroke thrombus composition using electrochemical impedance spectroscopy

BACKGROUND

Intra-procedural characterization of stroke thromboemboli might guide mechanical thrombectomy (MT) device choice to improve recanalization rates. Electrochemical impedance spectroscopy (EIS) has been used to characterize various biological tissues in real time but has not been used in thrombus.

OBJECTIVE

To perform a feasibility study of EIS analysis of thrombi retrieved by MT to evaluate: (1) the ability of EIS and machine learning to predict red blood cell (RBC) percentage content of thrombi and (2) to classify the thrombi as "RBC-rich" or "RBC-poor" based on a range of cutoff values of RBC.

METHODS

ClotbasePilot was a multicentric, international, prospective feasibility study. Retrieved thrombi underwent histological analysis to identify proportions of RBC and other components. EIS results were analyzed with machine learning. Linear regression was used to evaluate the correlation between the histology and EIS. Sensitivity and specificity of the model to classify the thrombus as RBC-rich or RBC-poor were also evaluated.

RESULTS

Among 514 MT,179 thrombi were included for EIS and histological analysis. The mean composition in RBC of the thrombi was 36% ± 24. Good correlation between the impedance-based prediction and histology was achieved (slope of 0.9, R²  =  0.53, Pearson coefficient  =  0.72). Depending on the chosen cutoff, ranging from 20 to 60% of RBC, the calculated sensitivity for classification of thrombi ranged from 77 to 85% and the specificity from 72 to 88%.

CONCLUSION

Combination of EIS and machine learning can reliably predict the RBC composition of retrieved ex vivo AIS thrombi and then classify them into groups according to their RBC composition with good sensitivity and specificity.

Electrical Bioimpedance Analysis for Evaluating the Effect of Pelotherapy on the Human Skin: Methodology and Experiments

BACKGROUND

Pelotherapy is the traditional procedure of applying curative muds on the skin's surface-shown to have a positive effect on the human body and cure illnesses. The effect of pelotherapy is complex, functioning through several mechanisms, and depends on the skin's functional condition. The current research objective was to develop a methodology and electrodes to assess the passage of the chemical and biologically active compounds of curative mud through human skin by performing electrical bioimpedance (EBI) analysis.

METHODS

The methodology included local area mud pack and simultaneous tap water compress application on the forearms with the comparison to the measurements of the dry skin. A custom-designed small-area gold-plated electrode on a rigid printed circuit board, in a tetrapolar configuration, was designed. A pilot study experiment with ten volunteers was performed.

RESULTS

Our results indicated the presence of an effect of pelotherapy, manifested by the varying electrical properties of the skin. Distinguishable difference in the measured real part of impedance (R) emerged, showing a very strong correlation between the dry and tap-water-treated skin (r = 0.941), while a poor correlation between the dry and mud-pack-treated skin (r = 0.166) appeared. The findings emerged exclusively in the frequency interval of 10 kHz …1 MHz and only for R.

CONCLUSIONS

EBI provides a promising tool for monitoring the variations in the electrical properties of the skin, including the skin barrier. We foresee developing smart devices for promoting the exploitation of spa therapies.

Impedance-based sensors discriminate among different types of blood thrombi with very high specificity and sensitivity

BACKGROUND

Intracranial occlusion recanalization fails in 20% of endovascular thrombectomy procedures, and thrombus composition is likely to be an important factor. In this study, we demonstrate that the combination of electrical impedance spectroscopy (EIS) and machine learning constitutes a novel and highly accurate method for the identification of different human thrombus types.

METHODS

134 samples, subdivided into four categories, were analyzed by EIS: 29 'White', 26 'Mixed', 12 'Red' thrombi, and 67 liquid 'Blood' samples. Thrombi were generated in vitro using citrated human blood from five healthy volunteers. Histological analysis was performed to validate the thrombus categorization based on red blood cell content. A machine learning prediction model was trained on impedance data to differentiate blood samples from any type of thrombus and in between the four sample categories.

RESULTS

Histological analysis confirmed the similarity between the composition of in vitro generated thrombi and retrieved human thrombi. The prediction model yielded a sensitivity/specificity of 90%/99% for distinguishing blood samples from thrombi and a global accuracy of 88% for differentiating among the four sample categories.

CONCLUSIONS

Combining EIS measurements with machine learning provides a highly effective approach for discriminating among different thrombus types and liquid blood. These findings raise the possibility of developing a probe-like device (eg, a neurovascular guidewire) integrating an impedance-based sensor. This sensor, placed in the distal part of the smart device, would allow the characterization of the probed thrombus on contact. The information could help physicians identify optimal thrombectomy strategies to improve outcomes for stroke patients.

Non-Invasive Cardiac and Respiratory Activity Assessment From Various Human Body Locations Using Bioimpedance

Objective: Bioimpedance sensing is a powerful technique that measures the tissue impedance and captures important physiological parameters including blood flow, lung movements, muscle contractions, body fluid shifts, and other cardiovascular parameters. This paper presents a comprehensive analysis of the modality at different arterial (ulnar, radial, tibial, and carotid arteries) and thoracic (side-rib cage and top thoracolumbar fascia) body regions and offers insights into the effectiveness of capturing various cardiac and respiratory activities. Methods: We assess the bioimpedance performance in estimating inter-beat (IBI) and inter -breath intervals (IBrI) on six-hours of data acquired in a pilot-study from five healthy participants at rest. Results: Overall, we achieve mean errors as low as 0.003 ± 0.002 and 0.67 ± 0.28 seconds for IBI and IBrI estimations, respectively. Conclusions: The results show that bioimpedance can be effectively used to monitor cardiac and respiratory activities both at limbs and upper body and demonstrate a strong potential to be adopted by wearables that aim to provide high-fidelity physiological sensing to address precision medicine needs.

Tissue-like skin-device interface for wearable bioelectronics by using ultrasoft, mass-permeable, and low-impedance hydrogels

Hydrogels consist of a cross-linked porous polymer network and water molecules occupying the interspace between the polymer chains. Therefore, hydrogels are soft and moisturized, with mechanical structures and physical properties similar to those of human tissue. Such hydrogels have a potential to turn the microscale gap between wearable devices and human skin into a tissue-like space. Here, we present material and device strategies to form a tissue-like, quasi-solid interface between wearable bioelectronics and human skin. The key material is an ultrathin type of functionalized hydrogel that shows unusual features of high mass-permeability and low impedance. The functionalized hydrogel acted as a liquid electrolyte on the skin and formed an extremely conformal and low-impedance interface for wearable electrochemical biosensors and electrical stimulators. Furthermore, its porous structure and ultrathin thickness facilitated the efficient transport of target molecules through the interface. Therefore, this functionalized hydrogel can maximize the performance of various wearable bioelectronics.

Comparison of silver-plated nylon (Ag/PA66) e-textile and Ag/AgCl electrodes for bioelectrical impedance analysis (BIA)

Recently, researchers have adapted Bioelectrical Impedance Analysis (BIA) as a new approach to objectively monitor wounds. They have indicated various BIA parameters associated to specific wound types can be linked to wound healing through trend analysis relative to time. However, these studies are conducted using wet electrodes which have been identified as possessing several shortcomings, such as unstable measurements. Thus, the adaption of e-textile electrodes has become an area of interest in measuring biosignals. E-textile electrodes are known to possess a significantly large polarization impedance (Z_p) that potentially influences these biosignal measurements. In this study we aim to identify the suitability of e-textile electrodes to monitor wounds using BIA methodologies. By adapting suggested methodologies conducted in-vivo from previous studies, we used an ex-vivo model to observe the behaviour of e-textile electrodes relative to time. This was compared to common clinical wet electrodes, specifically Ag/AgCl. The objective of this study was to identify the BIA parameters that can be used to monitor wounds with e-textile electrodes. By analysing the BIA parameters relative to time, we observed the influence ofZ_pon these parameters.

Bioimpedance method for monitoring venous ulcers: Clinical proof-of-concept study

Evaluation of wound status is typically based on means which require the removal of dressings. These procedures are often also subjective and prone to inter-observer bias. To overcome aforementioned issues a bioimpedance measurement-based method and measurement system has been developed to evaluate the state of wound healing. The measurement system incorporated a purpose-built bioimpedance device, a measurement software and a screen-printed electrode array. The feasibility and the performance of the system and method were assessed in an open non-randomized follow-up study of seven venous ulcers. Healing of ulcers was monitored until the complete re-epithelialization was achieved. The duration of follow-up was from 19 to 106 days (mean 55.8 ± 25.2 days). A variable designated as the Wound Status Index (WSI), derived from the bioimpedance data, was used for describing the state of wound healing. The wound surface area was measured using acetate tracing for the reference. A strong correlation was found between the WSI and the acetate tracing data, r(93) = - 0.84, p < 0.001. The results indicate that the bioimpedance measurement-based method is a promising quantitative tool for the evaluation of the status of venous ulcers.

INSA Wound Mapping System: II. Preliminary Porcine Results

In the first paper, a versatile wound monitoring system, capable of mapping the extent of a wound and characterizing the tissues involved without removing the dressing, was presented. This was achieved through electrical impedance measurements, made via an electrode matrix embedded within the wound dressing.In this second paper, we present early mapping results obtained on porcine models. It was found that there was a good correlation between wound areas derived using digital image planimetry and those using a 49-electrode impedimetric electrode array.

Bioimpedance Sensor Array for Long-Term Monitoring of Wound Healing from Beneath the Primary Dressings and Controlled Formation of H2O2 Using Low-Intensity Direct Current

Chronic wounds impose a significant financial burden for the healthcare system. Currently, assessment and monitoring of hard-to-heal wounds are often based on visual means and measuring the size of the wound. The primary wound dressings must be removed before assessment can be done. We have developed a quasi-monopolar bioimpedance-measurement-based method and a measurement system to determine the status of wound healing. The objective of this study was to demonstrate that with an appropriate setup, long-term monitoring of wound healing from beneath the primary dressings is feasible. The developed multielectrode sensor array was applied on the wound area and left under the primary dressings for 142 h. The impedance of the wounds and the surrounding intact skin area was measured regularly during the study at 150 Hz, 300 Hz, 1 kHz, and 5 kHz frequencies. At the end of the follow-up period, the wound impedance had reached the impedance of the intact skin at the higher frequencies and increased significantly at the lowest frequencies. The measurement frequency affected the measurement sensitivity in wound monitoring. The skin impedance remained stable over the measurement period. The sensor array also enabled the administration of periodical low-intensity direct current (LIDC) stimulation in order to create an antimicrobial environment across the wound area via the controlled formation of hydrogen peroxide (H₂O₂).

In vivo expansion and regeneration of full-thickness functional skin with an autologous homologous skin construct: Clinical proof of concept for chronic wound healing

A new cell‐tissue technology uses a patient's skin to create an in vivo expanding and self‐organising full‐thickness skin autograft derived from potent cutaneous appendages. This autologous homologous skin construct (AHSC) is manufactured from a small full‐thickness skin harvest obtained from an uninjured area of the patient. All the harvested tissue is incorporated into the AHSC including the endogenous regenerative cellular populations responsible for skin maintenance and repair, which are activated during the manufacturing process. Without any exogenous supplementation or culturing, the AHSC is swiftly returned to the patient's wound bed, where it expands and closes the defect from the inside out with full‐thickness fully functional skin. AHSC was applied to a greater than two‐year old large (200 cm²) chronic wound refractory to multiple failed split‐thickness skin grafts. Complete epithelial coverage was achieved in 8 weeks, and complete wound coverage with full‐thickness functional skin occurred in 12 weeks. At 6‐month follow‐up, the wound remained covered with full‐thickness skin, grossly equivalent to surrounding native skin qualitatively and quantitatively equivalent across multiple functions and characteristics, including sensation, hair follicle morphology, bio‐impedance and composition, pigment regeneration, and gland production.

Possibilities in the Application of Machine Learning on Bioimpedance Time-series

The relation between a biological process and the changes in passive electrical properties of the tissue is often non-linear, in which developing prediction models based on bioimpedance spectra is not trivial. Relevant information on tissue status may also lie in characteristic developments in the bioimpedance spectra over time, often neglected by conventional methods. The aim of this study was to explore possibilities in machine learning methods for time series of bioimpedance spectra, where we used organ ischemia as an example. Based on published data on the development of the bioimpedance spectrum during liver ischemia, a simulation model was made and used to generate sets of synthetic data with different levels of organ-to-organ variation, measurement noise and drift. Three types of artificial neural networks were employed in learning to predict the ischemic duration, based on the simulated datasets. The simulated prediction performance was very dependent on the amount of training examples, the organ-to-organ variation and the selection of input variables from the bioimpedance spectrum. The performance was also affected by noise and drift in the measurement, but a recurrent neural network with long short-term memory units could obtain good predictions even on noisy and drifting measurements. This approach may be relevant for further exploration on several applications of bioimpedance having the purpose of predicting a biological state based on spectra measured over time.