Developing an electronic product is inherently complex. But when that product is designed to interact directly with the human brain, the rules change entirely. It’s no longer enough for it to simply work: it must be accurate, safe, clinically validated, and, above all, usable in a person’s daily life.
In this context, the case of Neuroelectrics is particularly interesting. This company has developed a device capable of reading and stimulating brain activity without the need for surgery, opening up new possibilities for the treatment of conditions such as epilepsy and depression.
However, beyond the technology itself, what’s truly valuable is understanding how a product like this is built—what goes into it, what decisions are made, and what challenges arise along the way. To that end, we combine technical analysis with excerpts from our conversation with the CEO, which help provide a better understanding of the actual process.
From science to product: the real starting point
One of the most important—and often overlooked—aspects is that these types of products don’t start out as products. They begin as research.
Before considering design, electronics, or user experience, there are years of scientific research underpinning the concept. In the case of Neuroelectrics, the foundation lies in the study of non-invasive brain stimulation and its impact on certain medical conditions.
As Ana Maiques, CEO of Neuroelectrics, explains during her interview on the Toque de Ingenio podcast.
“We didn’t start with a helmet. We started with laboratory research, verifying that brain stimulation could have a real effect.”
This nuance completely changes the approach. You’re not designing a device from scratch, but rather translating scientific knowledge into a tangible solution. And that shapes every subsequent decision.
Working with the Invisible: The Challenge of Electronic Engineering
If there is one area where much of the technical complexity lies, it is in the electronics.
The human brain operates using extremely weak electrical signals, on the order of microvolts. Detecting these signals reliably in an environment full of noise is a major engineering challenge.
During the interview, Maiques placed particular emphasis on this point:
The electrodes have to pick up very faint signals and filter out noise. They aren’t just simple wires; they are high-precision components.
This requires the design of highly specialized electronic systems, where every component counts. The architecture must incorporate extremely sensitive signal amplification, advanced analog filtering, and high-resolution digital conversion. Above all, however, it must minimize any type of interference.
This is where PCB design plays a critical role. It’s not just about connecting components, but about designing a system where signal integrity is maintained at all times. As mentioned earlier:
“Every layer of the PCB, every trace, is optimized to minimize noise. If you don’t get this right, the system won’t work.”
A real-time system: when hardware and firmware are inseparable
As the product develops, another key element emerges: the interaction between hardware and firmware. In this case, the device does more than just measure; it also takes action. It is capable of delivering electrical stimuli based on what it detects in brain activity, which means it operates in real time.
This requires precise coordination among all components of the system. The firmware is not an add-on, but rather the core that governs the product’s behavior: it manages data acquisition, controls stimulation, and ensures that everything occurs with the appropriate latency.
As explained in the Toque de Ingenio interview:
“The same electrodes that read signals can also stimulate them. It all depends on what the system detects at any given moment.”
This type of architecture eliminates the traditional separation between hardware and software. Both must be designed together from the outset.
Artificial intelligence as a decision-making layer
What really takes the product to the next level is the incorporation of artificial intelligence. The device not only collects data but also interprets it. Using deep learning algorithms, it is able to identify specific patterns in each patient’s brain activity and adjust the stimulation accordingly.
In the CEO’s words:
“The system learns each patient’s unique pattern and customizes the stimulation.”
This approach transforms the device into a dynamic, adaptive solution. It is no longer a static product, but rather a system that evolves with use. And this places new demands on development: data quality, model validation, and robust integration between the physical device and the digital layer.
Designing for Real-World Use: When Technology Depends on Experience
There is one aspect that often takes a back seat in high-tech projects, but which is crucial here: industrial design.
The device is intended for use by patients in their daily lives, over extended periods of time. This means that ergonomics, materials, and the user experience are critical factors.
During the interview, Ana Maiques described the situation in very straightforward terms:
“If the fit isn’t comfortable or it doesn’t look good, the patient won’t wear it. And then the treatment won’t work.”
This requires integrating industrial design from the earliest stages of development—not merely as an aesthetic element, but as a fundamental component of the product’s performance.
Iterate, fail, and improve: the role of prototyping
As the product takes shape, prototyping becomes the primary learning tool.
It is during this phase that we verify whether the design actually works under real-world conditions. And, as is often the case with most hardware projects, the first version is rarely the final one.
“We went through many iterations. The first headsets were uncomfortable, there was signal interference… all of that is being fixed.”
Development becomes an iterative process, in which each version helps identify issues and improve the system. This cycle is particularly lengthy for medical devices, where every change must be rigorously validated.
Regulation: the factor that sets the pace of the project
Unlike in other sectors of the medical field, regulation is not a final step. It is a structural element of development.
Compliance with regulatory bodies such as the FDA requires not only demonstrating that the product works, but also that it is safe, reproducible, and properly controlled at every stage.
This adds another layer: comprehensive documentation of clinical trials, traceability… Everything must be thoroughly documented.
As Maiques explained:
“It’s not just engineering. It involves validation, documentation, and regulatory compliance. And that takes years.”
One clear conclusion: integration is more important than innovation
After analyzing the case of Neuroelectrics, one idea stands out above the rest: Success does not lie in a single technology, but in the ability to integrate them all.
Electronics, firmware, artificial intelligence, industrial design, and regulation must be developed in a coordinated manner. Not as separate phases, but as parts of the same system.
Because, ultimately, developing a medical electronic product isn’t just about making something work.
It involves ensuring that it works properly at all times under real-world conditions, and that it is also user-friendly, scalable, and certifiable.
If you’re working on the development of an electronic product and facing challenges such as cross-disciplinary integration, technical complexity, or validation, having a team that understands the entire process can make the difference between a development project that drags on indefinitely and a product that actually makes it to market.
If you have a project in mind, contact us and we’ll help you turn it from concept into reality.
