How can a design for a mobile app simplify and enhance the identification and quantification of microorganisms, analysts need in microbiology labs?
The inspiration behind this project comes from having established a career within microbiology for 6 years, and during that time I recognized a need for a more efficient and reliable assistive solution when it came to identifying and quantifying microorganisms!
Microbiology lab analysts use various methods to quantify microorganisms, and one of those methods is Direct macroscopic or microscopic observation. After a sample is cultured on an agar plate, microorganisms will grow and form colonies that can be seen with the naked eye or a microscope. Analysts can then observe the size, shape, color, and texture of the colonies to make preliminary identifications of the microorganisms present.
The process of identifying and quantifying microorganisms can be time-consuming, complex, and still prone to error, while also requiring manual data entry, interpretation of results, and cross referencing of multiple sources or alternative methods. This can often lead to inconsistencies, inaccuracies and delays in delivering results.
If there were a laboratory assistive solution, incorporating AI and machine learning in order to identify and quantify microorganisms, I thought this would be worth exploring..
The impact of proper identification and quantification of microorganisms is critical in many fields, including healthcare, food safety, and environmental monitoring.
Of all infections in health care require microbiological testing for diagnosis. (Journal Clinical Microbiology reviews)
People, each year in the United States get sick from contaminated food, and microbiological testing is a critical tool for preventing these illnesses. (CDC)
Of U.S public water systems reported meeting all microbiological standards, ensuring safe drinking water. (EPA 2019)
I thought to myself how can I address this problem using UX Design/ Research?
How could I implement the possibility of merging technology such as AI and machine learning to assist in identifying and quantifying microorganisms into a digital solution.
From understanding the importance of avoiding the introduction of contamination into the lab, I knew the digital solution would have to be in the form of an application on a designated Laboratory device like a (phone or tablet) that could streamline the process and provide real-time data analysis.
I began by reaching out to some of my past coworkers in order to identify their behaviors, pain-points, and motivations throughout their daily duties...
From synthesizing their responses, I was able to visually consolidate the most important aspects that the digital solution needed to focus on.
The overarching theme from my user interviews came to be that lab analysts needed a design that could assist them with completing the analysis of plates both accurately and quickly.
By designing an application that microbiology lab analysts can use to assist them in completing a portion of their work faster, then this will increase their overall efficiency & productivity having the lab's customers pleased.
From here, I was able to form a persona that would be the likely user for my application.
Meet John Michael, the young technologist in training
I Developed an Epic followed by a User story to give me clear direction of what the purpose of the application design will be and how it would help the user.
Now it was time for me to dig into what already existed in either the lab testing industry or digital/tech market that might be aiming to assist lab analysts.
From analyzing the user interviews & competitive analysis, I now had a good idea of the features that the users wanted and made the design more competitive, therefore I could now plan out how the user task flow would look like.
The user flow I decided to focus on was the process of
Identifying & numerating microorganisms in order to upload results.
Following the user task flow, I then sketched out how I envisioned each screen to look like.
The most important aspect of my design aiming to be the
* Camera integration,
* Identification and quantification screens
* Upload feature screen.
I decided to go with these sketches as they incorporated an MVP of what I needed and nothing more.
My low fidelity wire frames now served as inspiration to guide my design into the 1st iteration of high-fidelity prototypes.
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Now it was time to see what the potential user's thought, I needed feedback that could allow me to iterate on what didn't serve their needs.
Tasks
Users were told to complete the following tasks,
1. Scan a microorganism plate.
2. Select what organism they are attempting to identify and quantify, + select the type of media that the microorganism is cultured on.
3. Analyze the image
4. Upload the image
Goals
1. Identify accessibility & navigation problems.
2. Determine additional features wanted or needed.
3. Address any UI confusions in order to make wording, layout and hierarchy clearly defined.
Some of my user feedback,
"I like the color scheme, however the home menu layout seems a little gamey, and not so serious as I would expect from an app that I will be relying on to give me accurate results."
"The bottom navigation bar is hard to distinguish from the background color."
"On the upload screen there should be a way to search for past images you may want to re-upload or send."
Taking the feedback into consideration, I made changes to the 1st iteration. Below is the before and after highlighting how I got to the 2nd iteration and final prototype.
Here is a closer look a the final prototype mockups.
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Since this was just a conceptual project, there was no way of receiving quantitative data. However, these metrics would hypothetically measure the success of Minumeri.
Although at the very start, I knew this would be a hypothetical case study considering the current limitations in technology, I still wanted to explore the idea of integrating (AI, computer vision & machine learning) into the concept of the app design, in order to be able to think past the current limitations and envision the future possibilities of technology.
Minumeri would need AI and machine learning to be at an advanced state where it could identify a microorganism down to the genus or species level just by the picture regardless of cultured media or organism type.
When iterating, it was necessary to envision the scenarios that might leave the user without options or viable pathways to their end destination, in order to avoid these from the start, conducting some concept testing with the potential users is as valuable.
Conducting a comparative analysis of similar projects or solutions can help validate the success of the project. By comparing the design solution to existing solutions I was able to identify any gaps or opportunities for improvement.