Development of a Uroflow Generator to Help Verify Sound-Based Flow Test Applications

Overview

Benign Prostatic Hyperplasia is a non-cancerous enlargement of the prostate that presses up against the urethra and thickens the walls of the bladder leading to trouble urinating and emptying the bladder. This is a condition that occurs in a significant number of older men. A major diagnostic tool used in this condition is a urine flow test called uroflowmetry. In this test, a patient must come into a clinical setting with a full bladder and then urinate into a uroflow machine which will generate a flow rate curve for the urine flow. This data will give the total voided volume, average flow rate, and max flow rate. A recent improvement in this field is sound-based uroflowmetry. This is done through apps that claim they can use the sound of urine hitting water in the toilet to generate a flow curve for the patient. The largest question surrounding these apps is whether they are accurate enough to replace the current gold standard uroflow machines in a clinical setting. To address this problem, we attempted to create a machine that can mimic urine flow. This machine will then be used to compare flow curves from a sound-based uroflowmetry and traditional uroflowmetry and determine if the sound-based technology is accurate.

Objectives

• Develop a machine to mimic male urine flow accurately.
• Use a uroflow machine to confirm the mimicked flow matches real flow properties.
• Validate claims of sound-based urine flow apps by comparing their output with the machine’s mimicked flow.
• Be able to draw a specified flow curve.
• Mimic urine flow at a specified rate consistently.
• Aids research and diagnoses at Penn State Hershey Medical Center, enabling exploration of alternative flow testing methods for urinary conditions.

Approach

• Gathered our customer needs directly through our sponsor, Dr. Joseph Clark.
• Reviewed the market of variable-output water pumps and methods of controlling the output of water pumps.
• Keeping our budget in mind, we chose to approach the issue from the angle of controlling the water pump through a combination of hardware and coding languages.
• Using an Arduino Uno REV3 microcontroller board we were successfully able to run a small water pump through the use of the associated C++ coding language the hardware runs off of.
• Achieving variable speeds required the use of a L298N motor driver that could successfully vary the voltage going to the pump over a given time frame, which allowed us to vary the speed of the pump.
• Initially, used a 9V battery to power the system, but that limited the power going into our system, so we changed our power supply to a DC power supply to help us experiment at different voltages.
• Creating our custom flow inputs required the use of a separate coding language MATLAB to draw the curve any specification our sponsor wants.
• By incorporating a microSD card into the circuit, we were able to read and transmit the custom curve data to the pump through our Arduino C++ code.
• Once we were able to successfully create curves, we built a box housing to have a place to set a laptop on top of and a barrier between our circuitry and possible outside elements that could affect it.
• Using SOLIDWORKS we modeled brackets for our electronics to be held in place and housing for our pump to protect the electronics from potential leaks.
• Achieving proper control over the pump’s speed required us to visit Hershey Medical Center and use one of their clinical Uroflowmeters to find the precise correlation between voltage and pump speed.
• During calibration we discovered the minimum speed of the pump was 10 ml/sec which resulted in us being unable to create precise curves at that small of a speed.

Outcomes

• We were able to accurately mimic real Uroflow patterns above 10 ml/sec.
• Users can customize the input curve to their liking.
• Able to be easily used with the in-house clinical Uroflowmeter at Hershey.
• Our sponsor will be able to test the ability of sound-based apps to monitor maximum flow rate, average flow rate, and total voided volume by comparing the output of the app to that of what our machine outputs.