Developing a real time sensing system to monitor bacteria in wound dressings

Infection control is a key aspect of wound management strategies. Infection results in chemical imbalances and inflammation in the wound and may lead to prolonged healing times and degradation of the wound surface. Frequent changing of wound dressings may result in damage to healing tissues and an increased risk of infection. This paper presents the first results from a monitoring system that is being developed to detect presence and growth of bacteria in real time. It is based on impedance sensors that could be placed at the wound-dressing interface and potentially monitor bacterial growth in real time. As wounds can produce large volumes of exudate, the initial system reported here was developed to test for the presence of bacteria in suspension. Impedance was measured using disposable silver-silver chloride electrodes. The bacteria Staphylococcus aureus were chosen for the study as a species commonly isolated from wounds. The growth of bacteria was confirmed by plate counting methods and the impedance data were analysed for discernible differences in the impedance profiles to distinguish the absence and/or presence of bacteria. The main findings were that the impedance profiles obtained by silver-silver chloride sensors in bacterial suspensions could detect the presence of high cell densities. However, the presence of the silver-silver chloride electrodes tended to inhibit the growth of bacteria. These results indicate that there is potential to create a real time infection monitor for wounds based upon impedance sensing

Monitoring Wound Healing with Contactless Measurements and Augmented Reality

Objective: This work presents a device for non-invasive wound parameters assessment, designed to overcome the drawbacks of traditional methods, which are mostly rough, inaccurate, and painful for the patient. The device estimates the morphological parameters of the wound and provides augmented reality (AR) visual feedback on the wound healing status by projecting the wound border acquired during the last examination, thus improving doctor-patient communication. Methods: An accurate 3D model of the wound is created by stereophotogrammetry and refined through self-organizing maps. The 3D model is used to estimate physical parameters for wound healing assessment and integrates AR functionalities based on a miniaturized projector. The physical parameter estimation functionalities are evaluated in terms of precision, accuracy, inter-operator variability, and repeatability, whereas AR wound border projection is evaluated in terms of accuracy on the same phantom. Results: The accuracy and precision of the device are respectively 2% and 1.2% for linear parameters, and 1.7% and 1.3% for area and volume. The AR projection shows an error distance <1 mm. No statistical difference was found between the measurements of different operators. Conclusion: The device has proven to be an objective and non-operator-dependent tool for assessing the morphological parameters of the wound. Comparison with non-contact devices shows improved accuracy, offering reliable and rigorous measurements. Clinical Impact: Chronic wounds represent a significant health problem with high recurrence rates due to the ageing of the population and diseases such as diabetes and obesity. The device presented in this work provides an easy-to-use non-invasive tool to obtain useful information for treatment

Sensor Systems for Impaired Healing Markers, Concepts and Applications for Objective Wound Assessment

In the pathological healing of chronic wounds the ordered sequence of tissue restoration is disturbed. As a consequence, chronic wounds fail to heal within months and pose a major impact on the patient by pain, odor, leakage, and the risk of infection and the health care system by its constant treatment. Introducing objective wound assessment by sensor technology into clinical routine would help to guide treatment procedures and improve the healing outcome. The aim of this research study was the development of simple and effective concepts to evaluate the wound status at the point of care. Requirements for point of care testing include a fast and flexible device use by untrained personal, reduced time and costs, as well as reliable and easy to interpret results. The complex nature of wounds can be divided into the different regimes of physical appearance, biochemical status and microbiological environment, which influence each other. Each regime is tackled separately in this work by identifying possible parameters for wound analysis from the literature and the design of sensor concepts to quantify these candidates. A miniaturized, wearable sensor system for the integration in a wound dressing was developed to collect healing relevant, physiological data. The sensor measures optical reflectance, heart rate, arterial oxigenation, surface pH, moisture and temperature. The function of the sensor system was verified in a porcine wound model. A combination of surface pH, reflected infrared, and red light showed to be the most significant parameter, associated with the healing progress. For the measurement of biochemical parameters a microfluidic platform for the preparation of biosensing hydrogels by in situ polymerization was designed. Introducing functional structures for gel patterning in the chip fabrication allows for rapid assay customization. Simple handling and functionality were illustrated by assays for matrix metalloproteinase, an important factor in chronic wound healing. In addition, the demonstrated assays for total protein concentration and cell counts indicate the possibilities for a wide range of fast and simple diagnostics. The last part of the thesis discusses microfluidic technologies for rapid analysis of bacteria. Preconcentration of bacteria by on-chip electrophoresis and detection by a simple optical setup are presented. Furthermore, devices for rapid and parallel growth-based bacterial identification and antibiotic testing in microfluidic cultures were designed. The presented results and demonstrated tools show that medical analysis can be improved by sensor technologies that are simple to operate and yield fast results at the point of care