Can Microwaves Detect Floppy Baby Syndrome?

Who We Are and Why This Matters

We are a research team from the University of Łódź, Poland, and we are building something that could change how doctors diagnose one of the most common motor skill problems in newborns: muscular hypotonia, often called "floppy baby syndrome."

If you have ever held a newborn and noticed they felt unusually limp or had poor head control, that could be a sign of low muscle tone. It sounds like a niche problem, but it is not. Left untreated, hypotonia can lead to uneven body posture, skull deformities like plagiocephaly, and later in life, scoliosis and chronic postural issues. Early detection is everything, but the tools doctors currently have are surprisingly inadequate.

Our goal is to build a cheap, objective, non-invasive probe that measures muscle tone using microwave spectroscopy. No needles, no subjective scoring, no cooperation needed from the patient. Just place the sensor on the skin and get a reading.

The Problem: Why Current Methods Fall Short

Right now, doctors have a few options for assessing muscle tone:

• The Modified Ashworth Scale is the go-to method for children and adults. A doctor manually moves the patient's limb and subjectively rates the resistance. Two doctors examining the same patient can easily give different scores.

• The Apgar score is used right after birth. It checks the overall condition of the baby (heart rate, breathing, reflexes, colour, and muscle tone), but muscle tone is just one of five criteria. It is a rough screening tool, not a diagnostic one.

• Electromyography (EMG) measures the electrical activity of muscles and is quite accurate. However, it requires inserting needles or placing electrodes that need patient cooperation. Try getting a newborn to hold still for that.

Conclusion: there is no fast, cheap, objective way to measure muscle tone in newborns specifically. That gap is what our project aims to fill.

Our Approach: Microwave Spectroscopy Meets Muscle Tissue

The key insight behind our work is that muscle tone is linked to muscle impedance, meaning how muscle tissue responds to electromagnetic fields. A relaxed muscle and a tense muscle have different dielectric properties. If you can measure those properties accurately, you can quantify muscle tone objectively.

We designed a microstrip line probe that interacts closely with muscle tissue and measures its impedance in the gigahertz frequency range. Think of it as a tiny antenna that "listens" to how your muscles respond to microwave signals. The probe sends a signal into the tissue and measures what comes back (the S-parameters), which encode information about the tissue's dielectric properties. For that purpose, we conducted some simulations to determine electric field distribution

What We Have Achieved So Far

We are not starting from zero. Our team has experience in dielectric spectroscopy, which uses the same underlying physics: Why Microwaves?

Microwave frequencies (roughly 1–4 GHz for our purposes) are ideal because they penetrate soft tissue to a useful depth without causing any harm. The energy levels involved are extremely low, far below anything that would heat or damage tissue. Meanwhile, the dielectric response at these frequencies is sensitive enough to distinguish between different muscle states.

Development Process: Building the Prototype

The RS Student Fund is enabling us to move from a lab-bench concept to a self-contained prototype. Here is what we are building and how each component fits in:

Control and Data Processing

We are using an Arduino development board for low-level, real-time signal control and a Raspberry Pi for higher-level data processing. The Arduino handles the time-critical tasks like triggering measurements and reading sensor data, while the Raspberry Pi runs our signal analysis algorithms and manages communication. The long-term goal is to integrate both functions onto a single PCB, and having these development platforms lets us prototype the logic before committing to a custom board design.

Mechanical Prototyping

We are 3D printing probe housings, mounting brackets, and mechanical fixtures using PLA filament. Rapid prototyping lets us iterate on the physical design quickly. The housing needs to hold the electronics securely and ensure repeatable positioning of the probe against the skin surface, which is critical for consistent measurements.

RF Signal Path

For signal transmission between the probe and the processing electronics, we are using RF adapters and coaxial cables rated for GHz-range signals. At these frequencies, cable quality and connector integrity matter enormously. A poor connection can introduce reflections and losses that completely corrupt your S-parameter measurements. We also need standard cables for interfacing with the Arduino system.

Challenges and How We Are Tackling Them

Miniaturisation

Our lab prototype works, but it is bulky. Getting everything onto a single PCB means rethinking the layout, managing signal integrity in a much tighter space, and dealing with thermal constraints. The Arduino and Raspberry Pi platforms let us validate the system architecture before we commit to a custom PCB design.

Probe Geometry Optimisation

The geometric parameters of the microstrip line (width, length, substrate thickness, ground plane distance) all affect the measurement sensitivity and depth of tissue penetration. We are using electromagnetic simulation software to model different geometries before building them physically, which saves a lot of time and material.

Data Analysis Algorithms

Raw S-parameter data needs to be processed to extract meaningful information about muscle tone. We are developing signal analysis algorithms that can reliably distinguish between normal and abnormal muscle impedance patterns. The goal is fully automated detection, with no subjective interpretation required from the clinician.

Broader Impact

Who Could Benefit

Beyond newborn screening, the same technology could support diagnosis and monitoring of neurological conditions like stroke, brain injury, spinal cord injury, cerebral palsy, ALS, and Parkinson's disease. The potential user base spans rehabilitation doctors, physiotherapists, neurologists, neonatologists, paediatricians, orthopaedists, urologists, and gynaecologists.

Cost and Accessibility

One of the strongest arguments for our approach is cost. An EMG setup can cost thousands of euros. Our probe is built from standard, inexpensive components that can be fabricated on a single printed circuit board. This makes it realistic for widespread deployment, not just in well-funded hospitals but potentially in smaller clinics and even home-care settings.

Sustainability

We are designing for durability and repairability. Components are inexpensive and replaceable, and the housing is made from recyclable PLA. Most of our design iteration happens in simulation, minimising material waste. When physical prototypes are needed, 3D printing keeps waste low compared to subtractive manufacturing.

What Comes Next

Our immediate next steps are optimising the probe geometry through simulation and physical testing, refining the data analysis pipeline, and completing the miniaturised prototype. Ultimately, we want this technology to become standard equipment in hospitals and physiotherapy clinics.