Wound infections are a major problem worldwide, both for the healthcare system and for patients affected. Currently available diagnostic methods to determine the responsible germs are time-consuming and costly. Wound infections are mostly caused by various bacteria, which in turn produce volatile organic compounds. From clinical experience, we know that depending on the bacteria involved, a specific odor impression can be expected. For this reason, we hypothesized that electronic noses, i.e., non-invasive electronic sensors for the detection of volatile organic compounds, are applicable for diagnostic purposes. By providing a comprehensive overview of the state-of-research, we tested our hypothesis. In particular, we addressed three overarching questions: 1) which sensor technologies are suitable for the diagnosis of wound infections and why? 2) how must the (biological) sample be prepared and presented to the measurement system? 3) which machine learning methods and algorithms have already proven successful for the classification of microorganisms? The corresponding articles have critically been reviewed and are discussed particularly in the context of their potential for clinical diagnostics. In summary, it can already be stated today that the use of electronic noses for the detection of bacteria in wound infections is a very interesting, fast and non-invasive method. However, reliable clinical studies are still missing and further research is necessary.