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Researchers have demonstrated a new way to capture a far wider range of sound without using more bits, challenging a nearly 90-year-old convention in digitisation and opening possibilities for healthcare, environmental sensing and AI.

What does a faint heartbeat have in common with a thunderous concert? Both present a challenge for digital technology: capturing the quietest details without losing the loudest sounds.

For nearly 90 years, engineers have managed this trade-off by balancing the loudness of sound a device can capture against the number of bits used to represent them.

“Reeves and Shannon established the ideas that made digital communication possible... What has changed is that modern computation allows us to ask whether the analogue signal must still be presented to the converter in the same way.” Dr Ruiming Guo Department of Electrical and Electronic Engineering

Now, researchers at Imperiahave demonstrated a radically different approach called . Rather than allowing loud signals to be clipped, their system deliberately folds them into a smaller range before digitisation. Although the resulting waveform can look or sound scrambled, its mathematical structure allows the original sound to be reconstructed.

The approach, known as Unlimited Sensing, changes what digital bits represent, rather than simply adding more of them. 

In experiments using just six bits per sample, the prototype achieved at least 18 dB greater dynamic range than a conventional six-bit converter. A listening study involving 52 participants also found that reconstructed audio received higher quality ratings than conventional recordings at the same bit depth.   

The implications extend beyond music. From digital stethoscopes and environmental sensors to future AI systems that interpret the physical world, the technology opens new possibilities for capturing information that conventional digitisation can lose.

Breaking a 90-year-old trade-off

The breakthrough builds on nearly 90 years of digitisation research, dating back to Imperiaalumnus Dr Alec Reeves CBE, who invented pulse-code modulation in 1937, and Claude Shannon, whose work laid the mathematical foundations of modern digital communications. 

Conventional analogue-to-digital converters face a fundamental trade-off: with a fixed number of bits, accommodating a wider range of signals comes at the expense of resolving finer details. Signals that exceed the converter's range are clipped, losing information that software can only attempt to repair afterwards.

The Imperiateam's solution turns this conventional thinking on its head. Imagine the hands of a clock wrapping around after completing a revolution, rather than stopping. Unlimited Sensing uses a similar principle to represent large signal amplitudes within a smaller range. Crucially, the folds follow a mathematical structure, allowing the original signal to be recovered from the sequence of measurements.

Researchers Dr Ruiming Guo, Yuliang Zhu and Dr Ayush Bhandari combined mathematical recovery theory, scalable audio algorithms and a complete microphone-to-digital hardware implementation. Their custom converter was built using off-the-shelf electronic components, demonstrating how a mathematical idea can be translated into working technology.

, lead author and Research Associate in ��������'s Department of Electrical and Electronic Engineering, said: “Reeves and Shannon established the ideas that made digital communication possible. Those ideas are not wrong. What has changed is that modern computation allows us to ask whether the analogue signal must still be presented to the converter in the same way.”

USF-Audio hardware from Ayush Bhandari's research team

Can listeners hear the difference?

The researchers tested their technology using real acoustic recordings, including speech, music, heart sounds and animal calls.

The improvement of at least 18 dB in dynamic range corresponds to approximately an eightfold increase in the range of signal amplitudes the converter can accommodate, without increasing its bit depth. But could listeners actually hear the difference?

“Great music lives in its contrasts — from the faintest whisper to the loudest crescendo. Yet conventional digital recording forces compromises between capturing these extremes." Dr Ayush Bhandari Department of Electrical and Electronic Engineering

In controlled listening experiments, participants rated audio reconstructed using Unlimited Sensing more highly than conventional six-bit recordings and recordings affected by clipping. 

The findings demonstrate that the benefits are not confined to mathematical theory or laboratory measurements. Changing how sound is represented digitally can produce improvements that people can hear. 

, Associate Professor in ��������'s Department of Electrical and Electronic Engineering and co-author of the study, said: “Great music lives in its contrasts — from the faintest whisper to the loudest crescendo. Yet conventional digital recording forces compromises between capturing these extremes. 

“We asked a radically different question: what if we changed what the bits represent, rather than simply adding more of them? That is the idea behind Unlimited Sensing — capturing a far wider range of sound without increasing digital resolution.”

Beyond human hearing: A new frontier for sensing and AI

The potential reaches well beyond audio.  A digital stethoscope must detect faint biological sounds, while an environmental sensor may need to distinguish subtle animal calls from much louder surroundings. Both illustrate the challenge of preserving weak signals alongside strong ones.

Unlimited Sensing offers a new approach to this problem, opening possibilities for more sensitive medical devices, environmental monitoring systems and other sensing technologies.

The opportunity becomes particularly significant as artificial intelligence increasingly learns to interpret the physical world. 

The sensors feeding AI systems are just as important as the algorithms themselves. Information lost during digitisation cannot always be recovered through computation, no matter how powerful the AI is.  Unlimited Sensing takes a different starting point: preserving information through a new digital representation rather than attempting to reconstruct what conventional sensors have discarded.

There may also be important implications for energy efficiency. Conventional converters often require additional digital resolution to accommodate a wider range of signals while preserving fine details. By extending dynamic range without increasing bit depth, Unlimited Sensing offers a potential route towards smaller, more energy-efficient sensing hardware. 

Although further engineering is needed to establish these benefits in practical devices, the researchers envision applications ranging from wearable health monitors to autonomous environmental sensing networks. The present study demonstrates the approach in audio hardware, providing a foundation for investigating these wider possibilities. 

The broader message is that the limits of digital sensing are shaped not only by how many bits are available, but also by what those bits are designed to represent. 

The study, ‘’, is published in IEEE Transactions on Audio, Speech and Language Processing.

The research was supported by the European Research Council Starting Grant CoSI-Fold (101166158).