Khatlako Mareka, an Electronics Engineering student at the National University of Lesotho (NUL), is doing what many thought only big hospitals in rich countries could do—design a small machine to see inside the human body. His work? A low-cost Electrical Impedance Tomography (EIT) system that can make 3D images of what’s hidden under your skin!
“Forget the expensive CT scans or MRI machines,” Khatlako, the student supervised by Dr Naleli Matjelo, says with a grin. “What we’re building here at NUL can fit on a small space, costs less than your phone, and uses simple tools.” It works more like and X-ray machine bit it’s not.
So what exactly is this EIT thing?
Let’s take a short science adventure.
Imagine you want to see inside an apple without cutting it open. How could you do that? Easy—you gently zap it with electricity and listen to how the signals change. Different parts of the apple—like its seeds, core, or skin—will affect the electricity in different ways. If you collect enough of these signals, you can figure out where the seeds are hiding—without slicing the fruit.
That, our friends, is what Electrical Impedance Tomography does. Only instead of apples, Khatlako is aiming at bodies, muscles, lungs—even babies’ chests in hospitals.
But here’s where it gets even cooler.
Most EIT systems you’ll hear about are huge, power-hungry, expensive machines found in rich labs in Europe or America. Khatlako built his in a Lesotho lab—with an Arduino Uno, some MOSFETs, jumper wires, and tiny voltage sensors.
And wait—it gets better.
Usually, medical imaging needs big heavy equipment that stays in one place. But Khatlako’s design is portable. “I wanted something that can work in rural clinics where people can’t afford to rush to Maseru and worse, Bloemfontein for a CT scan,” he explains. “Something you can carry, power with a small battery, and use right there in the village.”
And the secret to this magic? Simplicity.
Instead of the 32 or 64 fancy electrodes used by fancy hospitals, Khatlako used just four simple electrodes, arranged in a circle inside a tank of salty water. He sends a tiny, safe electric current into the tank through one pair of electrodes. Then the other two electrodes listen carefully for how the current changes. That tells the system what’s inside the tank—maybe a plastic object simulating a tumour, or maybe just water.
Next comes the brain of the machine—the little blue Arduino board, the kind you can buy for less than M200 at any electronics shop. It reads the tiny voltages from the electrodes and sends them to a computer. The computer runs clever maths equations (using a tool called EIDORS in MATLAB) to make a 3D image of what’s hiding in the tank.
And the results? Surprisingly good!
When the tank was empty, the system recorded steady, predictable voltages—what scientists call homogeneous data. But when Khatlako secretly dropped a resistive object (something that blocks electricity) into the tank, the numbers suddenly changed—what scientists call anomaly data. From this, his system could figure out where the object was, how big it was, and how much it resisted the flow of electricity.
Even better, when Khatlako reconstructed these signals into an image, it showed up on screen like a simple 3D map—the empty parts gray, the strange object darker or black depending on its properties. “We could actually see the ‘tumour’ sitting inside the tank!” he smiles.
But hold on—is this machine perfect? Not yet.
Because it only uses four electrodes and direct current (DC), the images are still blurry—not as crisp as an expensive CT scan. “To get hospital-quality images,” Khatlako admits, “you’d need more electrodes, AC currents, and better shielding from noise.” But for a prototype built on a student budget? It’s astonishing.
And here’s the exciting part—this is just the beginning.
With funding, this could be scaled up to 16 or even 32 electrodes. It could switch to safer and clearer alternating current. The images could get sharper, detailed enough to detect lung problems, brain injuries—even monitor newborn babies breathing in hospitals.
In fact, this technology could save lives in Lesotho’s far-flung clinics, where big machines are too costly or impossible to maintain.
And there’s more.
Khatlako’s system shows that Lesotho’s own young scientists can build world-class technology in local labs. “I hope this inspires other students,” he says. “If you can dream it, you can build it—even here.”
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Brought to you by NUL Innovation Hub, Where Academia Meets Industry


