Development of an intelligent surgical dressing using integrated sensors to monitor rehabilitation and risk factors for infection remotely in patients undergoing total knee arthroplasty.

Knee replacement is a successful intervention used to treat patients with painful bone-on-bone osteoarthritis of the knee. Over 100,000 knee replacements are carried out in England and Wales annually. The number of people suffering knee arthritis continues to grow with the worldwide demand for knee replacements expected to reach 1.25 million procedures per year by 2030. Knee replacement is effective in relieving pain and improving function, but unfortunately significant risks are still associated with this operation. In the first few weeks after surgery, wound infection and joint stiffness are among the most common. Timely diagnosis of both is important as early intervention has a better chance of success. Failure to intervene early often results in one or more major surgeries (often with poor results), and significant burden to the patient and healthcare system. Early diagnosis is key to avoiding potential complications; however, with increasing pressure on resources and a shift to reducing hospital stays means the face-to-face contact with the experienced staff often needed to make a diagnosis are at a premium and limited preventing timely assessment. After knee replacement surgery, a dressing is placed over the wound for the first two to three weeks to protect the wound from exposure to the outside environment. The dressing also absorbs fluid leaking from the wound to keep the surrounding area dry. However, when too much fluid is in the dressing, it creates a moist environment in which bacteria can grow. Patients often go home on the day of surgery or the following day, requiring them to self-monitor their wound. Additionally, when being discharged patients are given rehabilitation exercises to help with movement and strengthening to prevent stiffness. People undergoing knee surgery therefore have a complex task of monitoring their recovery with limited expertise or training. Indeed, many are unaware of the early warning signs of post-operative complications. This project aims to develop an intelligent wound dressing to help patients monitor the risk of wound leakage and stiffness, and to actively decrease bacterial growth around the wound. So far, we have identified and conducted initial experiments identifying the necessary sensors for developing an “intelligent” wound dressing to help patients with timely diagnosis. We will use the requested funds to progress the technology to a flexible film incorporating the sensors and electronics with a “warning system” that can detect potential problems and limit the risk of infection in a wound dressing. We will then test the performance of the prototype device and demonstrate its function in 1) detecting wound leakage, 2) preventing bacterial growth, 3) monitoring activity and movement, 4) communicating risk levels to the user. The conclusion of this project will be to have a demonstrable prototype which will place us in a strong position to secure further funding. The overarching goal being to bring this technology to patients to help improve their outcomes after surgery is dependent on successfully engaging industry partners to incorporate this technology in their portfolios.