Needless to say, when someone is having difficulty breathing it is a very serious condition that requires intensive treatment and monitoring. Billions of dollars are spent annually to treat respiratory diseases and infections. No small portion of these expenditures result from the continuous monitoring of the condition that needs to take place in an intensive care setting. This monitoring requires expensive equipment and the time of technicians and clinicians to operate that equipment and interpret the results. With the lung-related morbidities related to COVID-19 that have appeared in the past few years, this problem has grown larger than ever.
An innovation called the Pneumo.Vest that has recently been developed at the Fraunhofer Institute may lead to changes in the way that lung function is monitored in the future. They have developed a vest with integrated sensors that can continually monitor the lungs without the need for expensive equipment, trained professionals to operate it, or an inpatient setting. An individual being monitored only needs to put on the vest, then they can go about their normal, daily activities. Such a paradigm shift has the potential to reduce the burden on both patients and the healthcare system.
Pneumo.Vest has an array of piezoceramic acoustic sensors integrated into the front and back of its fabric that are capable of detecting even very faint sounds. Since the position of each sensor is fixed relative to one another, it is possible to pinpoint exactly where sounds are detected in the lungs. This allows for a detailed map of areas of concern to be generated, and that map can be built up over time, giving clinicians a picture of the status of the lungs over a period of time. Software that accompanies the vest is able to filter the data to, for example, remove the sound of heartbeats or other sources of noise.
Pneumo.Vest (📷: Fraunhofer Institute)
In theory, the software could analyze the data to detect potential problems, then report them via a wireless network so that clinicians can be notified immediately of any concerning developments. Fraunhofer researchers are presently working to develop machine learning algorithms that can classify the complex sound patterns into indicators of respiratory disease or distress. They also note that while Pneumo.Vest was created for respiratory monitoring applications, the same technology could be adapted for other uses, like in sleep laboratories, or as a training aid for young doctors learning auscultation techniques.
The team notes that Pneumo.Vest is not designed to replace trained medical professionals, but rather to give them more information to help with making diagnoses. The longitudinal data collected under natural conditions provides much more useful information than can be collected under clinical conditions, and the vest simultaneously improves the quality of life of patients. This win-win situation for patients and the healthcare system alike has us rooting for more technologies like this to be developed and validated for clinical use.