Building ECG into Consumer Devices – What You Need To Know

ECG has moved quickly from a differentiator to a baseline expectation in consumer wearables.

If you are building a smartwatch, smart ring or band in 2026, to be competitive ECG is no
longer optional. It is a core feature, driven by demand for proactive health monitoring and capabilities such as AFib detection.

The opportunity is clear.

But so is the gap between adding ECG and delivering it well.

Adding ECG is straightforward. Delivering it reliably is not.

Single-lead ECG in a consumer device sounds simple. However, in practice, it’s a tightly
coupled system problem.

You are trying to deliver clinically meaningful signals from a device that must work:

• Across highly variable skin types and conditions
• During real-world use, including motion, temperature changes and hydration shifts
• Within strict industrial design constraints
• With a fast, intuitive user interaction model

All of that sits on top of a signal chain where small decisions compound.
This is where many programmes begin to diverge, not because teams lack capability, but
because ECG performance is rarely engineered as a fully characterised system early
enough.

Where programmes actually fail

In theory, teams understand the challenges. But, in practice, issues tend to surface late,
during validation or pre-launch testing.

Common failure modes include:

• Inconsistent signal-to-noise ratios across users
• Poor repeatability in AFib detection conditions
• Edge-case failures under motion or low contact pressure

At that point, options are limited and expensive.

Teams are often facing:

• Redesign cycles that delay launch timelines by months
• Increased regulatory burden due to inconsistent signal quality
• Escalating engineering cost without clear root cause visibility

This is not a signal processing problem alone, but a system characterisation problem.

Why the electrode is the critical entry point

The electrode isn’t just another component. Rather, it defines the quality of the signal
entering your entire system.

If the signal is degraded at the skin interface, everything downstream is compensating –
filtering, algorithms and post-processing can only go so far.

In consumer wearables, this challenge is amplified:

• In smart rings, limited surface area and constrained contact conditions increase
variability
• In smartwatches, motion, strap tightness and wrist anatomy introduce instability

The electrode is the entry point into the signal chain, but it can’t be treated in isolation.

The reality of dry electrodes in wearable devices

Dry electrodes are essential for usability but they are also inherently unstable.

You’re dealing with a high-impedance, biologically variable interface:

• Impedance can vary significantly between users
• Contact impedance shifts with micro-movement and pressure
• Sweat creates a dynamic, non-uniform conductive pathway

This directly impacts signal amplitude, baseline wander and noise characteristics.

Designing for “typical” conditions isn’t sufficient – you need to engineer against worst-case
distributions.

Material selection is an electrochemical problem

A common mistake is equating conductivity with performance.

ECG electrode behaviour is governed by electrochemical properties including impedance
across frequency, polarisation effects at the interface, and stability of coatings over time and
environmental exposure.

Materials that appear viable in early prototypes often fail under extended or real-world
testing.

Without proper electrochemical characterisation, decisions are being made with incomplete
data.

Mechanical design directly shapes signal quality

Electrode geometry, surface finish and placement all influence contact mechanics and signal
integrity.

Small design changes can materially affect:

• Motion artefact susceptibility
• Contact consistency and settling time
• Effective impedance seen by the AFE

In compact form factors like rings, these effects are amplified. At the same time, you are
balancing comfort and aesthetics, which is where performance often degrades quietly.

Where most teams underinvest: Characterisation

A recurring pattern we see is insufficient characterisation early in development.
Teams move forward based on prototype behaviour, rather than quantified performance
across conditions.

Proper characterisation, particularly using electrochemical impedance spectroscopy and
system-level noise analysis, allows you to:

• Map impedance behaviour across users and environments
• Validate materials and coatings before scaling
• Understand settling behaviour and transient response
• Quantify noise sources relative to your AFE and signal chain

Proper characterisation is what turns trial-and-error into engineering.

This is a system problem, not a component problem

Even though electrodes are foundational, ECG performance is defined at the system level.
Electrode impedance interacts directly with:

• AFE input impedance and configuration
• PCB layout and grounding strategy
• Filtering and signal conditioning
• Algorithm robustness, particularly for arrhythmia detection

When these elements are developed independently, mismatches emerge. Often late, when
they are harder and more costly to resolve.

The highest-performing devices treat ECG as a fully integrated signal pathway from the
outset.

Why this matters commercially

ECG is one of the few features that can genuinely elevate a device beyond fitness tracking.
When implemented well, it delivers clinically relevant insights such as AFib detection,
strengthens premium positioning, and builds user trust and engagement.

However, when it’s not engineered properly, it introduces real risk. You can end up with false
positives or missed detections, increased regulatory complexity or delays, and ultimately
higher return rates driven by reduced user confidence. In a feature this visible, that also
translates directly into brand impact.

This isn’t something you can afford to iterate into after launch.

Where most teams get stuck

Most teams already have strong internal engineering capability.

What they often lack, however, is clear, quantified visibility into ECG performance early
enough to act on it, particularly at the intersection of electrode behaviour and system design.

How ABEL addresses this

ABEL, B-Secur’s Advanced Biosensing Engineering Lab, is designed to bring structure and
measurable rigour into ECG development before those risks become embedded.
Rather than optimising components in isolation, ABEL focuses on the entire signal pathway,
from electrode interface through to full-system performance.

Through a structured, time-bound engineering programme, ABEL enables teams to:

• Quantify electrode behaviour using electrochemical impedance testing
• Evaluate materials and coatings against real-world performance criteria
• Diagnose system noise and identify dominant sources across the signal chain
• Align electrode design, AFE configuration and algorithms as a single system
• Benchmark performance against reference ECG devices using defined metrics

By the end of the programme, teams have:

• A device design optimised for high-quality ECG acquisition
• Quantified evidence of signal performance, including SNR and usable beats
• Clear understanding of performance margins and limitations
• A validated path towards production-ready ECG capability

This is not about adding more testing but about replacing uncertainty with data.

The bottom line

ECG is no longer a feature you can afford to “get close enough” on. In a market where signal
quality directly impacts user trust, regulatory outcomes and brand perception, performance
needs to be engineered deliberately, not validated late.

The teams that succeed are not the ones who add ECG first but the ones who quantify and
control it early.

If you are building a wearable device with ECG, the question is not whether you need this
level of rigour but, critically, when you apply it.