Honeywell has recently developed a new technology, Digital Holographic Microscopy, that uses artificial intelligence (AI) to help count and classify tiny particles or cells.

This technology has the potential to be used across many industries where timely analysis and simplified operations are critical.

Within the healthcare industry, for example, Digital Holographic Microscopy can be used to shorten treatment time for patients receiving at-home peritoneal dialysis. These patients are susceptible to abdominal lining infections – due to the time it takes to send the samples to a lab with specialized equipment, today it can take 1-2 days to diagnose these infections, during which time the patient’s condition can often worsen if not treated.

To help address this challenge, Digital Holographic Microscopy can capture images of the patient’s dialysis fluid at the point-of-care by using a portable device with a laser, imager sensor and disposable microscope slide. These images are analyzed by AI algorithms to rapidly determine if the number and type of white blood cells indicates an infection so patients can receive appropriate treatment more quickly and effectively.

“We are seeing a growing need for solutions that can provide results that are both rapid and precise, empowering healthcare professionals to make informed decisions quickly. We have invested in innovations like Digital Holographic Microscopy because of their power to make testing and analysis more accessible to patients while also improving patient care and efficiency across our healthcare system,” said Sarah Martin, President of Honeywell Sensing Solutions.

Beyond clinical care, Digital Holographic Microscopy can be used in environmental applications to analyze types and amounts of various air pollutants to help achieve safer indoor air levels. It can also monitor cells and other organisms in liquid samples for quality and safety.

Digital Holographic Microscopy produces high-resolution images without the need for expensive and complex lenses and opto-mechanical systems found in a traditional microscope. Instead, this technology uses light passing through a sample to generate unfocused hologram images, which are then processed by computational algorithms so they can be interpreted.

This novel technology has advantages over conventional microscopy, particularly because it allows for simple and portable instrument design, which facilitates testing and analysis at the point-of-use rather than requiring samples to be sent to a lab.

By using machine learning algorithms to differentiate between types of cells, it also eliminates the need for staining, which simplifies biological sample preparation. In addition, it can replace or supplement sample analysis, enabling faster results with a simplified workflow.