• Physics 16, 94
By exploiting a phenomenon called stochastic resonance, sensors can perform better in a noisy environment than in a noise-free environment.
Sensors of all kinds, from accelerometers to thermometers, can be hampered by random fluctuations (noise) in the environment, which can swamp the signals they aim to detect. But a new study shows how noise could actually be used to improve the sensitivity of sensors . In experiments using a wearable wireless sensor that monitors a person’s breathing during exercise, researchers have shown that the sensor’s ability to detect weak signals is greatest not when the input is noise-free, but when it includes a modest amount of noise.
Most attempts to address the harmful effects of noise in tracking focus on reducing or removing it, for example by using filtering or active noise cancellation. However, it has long been known that some nonlinear systems, where the output signal is not simply proportional to the input, can take advantage of noise through an effect called stochastic resonance. . This phenomenon, where a modest amount of noise actually increases output, is exploited by some biological systems, such as the organs in shrimp that detect movement . Stochastic resonance has also been reported in various specialized electronic circuits and mechanical devices.
Now a team in Singapore and China, led by electrical engineer John Ho of the National University of Singapore, has shown how to induce stochastic resonance to improve sensitivity in a mechanical sensor. The key is to operate the device near a so-called exceptional point (EP), where nonlinearity is particularly strong.
EPs occur in resonant systems that can exchange energy with their environments. Such systems may have resonant frequencies at which they naturally vibrate in the absence of a periodic driving force, such as a bridge vibrating in response to wind. Two of these resonant frequencies (called natural frequencies) can coincide when some other property of the system reaches a certain value. This coalescence occurs in an EP and can induce highly non-linear behavior, such that the system can exhibit a pronounced response to a small signal.
In their latest research, Ho and colleagues study a resonant sensor that produces an output when the amplitude of the input signal exceeds a certain threshold. They theoretically show that noise in the input can induce EP at random times, whereupon the sensor becomes temporarily more sensitive: an input signal initially too weak to induce an output signal now can. In this way, noise increases the overall performance of the sensor by stochastic resonance: the maximum signal-to-noise ratio is not at zero noise but at a particular noise amplitude.
To test the idea experimentally, the researchers used a motion sensor made of two pairs of overlapping oval blobs of silver thread woven into a fabric. One pair is worn next to the skin and the other on a garment placed over the first. Electrically conductive patches can act as charged plates of capacitors in electrical circuits known as LC resonators. When the distance between the two resonators changes due to the wearer’s movements, for example due to breathing, the coupling between them also changes. This modification alters the resonant frequency of the patches on clothing, the resonance of which is monitored wirelessly and used as an output signal. Such a device can detect breathing.
In the experiments, as the wearer’s movement became more vigorous, from standing to walking and running, the loudness of the input increased, inducing stochastic EPs in the sensor, which then created the expected improvement in sensitivity. The signal-to-noise ratio of the sensor initially increased as the noise level increased, reaching a maximum before decreasing again as noise engulfed the signal – the characteristic signature of stochastic resonance. As a result, the sensor continued to work well for monitoring respiratory rate during walking, whereas without the stochastic resonance boost it could only detect rate cleanly when the subject was stationary.
Ho and colleagues say this effect could be exploited to improve health monitoring, being adaptable to sensors for heart rate, gait and sweat production, for example. They say it could also improve the detection of environmental parameters such as pressure, temperature or humidity.
“I’m really impressed with this [Ho and colleagues] demonstrated this clever idea in a real-world application,” says Liang Jiang, a quantum sensing expert at the University of Chicago. “It’s a really nice demonstration.” Condensed matter physicist Mark Dykman of Michigan State University says exploring the behavior around exceptional points in the presence of noise is invaluable.”This is a new element in the long list of ‘unconventional’ stochastic resonance phenomena,” he says.
Philip Ball is a freelance science writer in London. His latest book isThe modern myths (University of Chicago Press, 2021).
- Z.Li et al.stochastic outstanding points for noise-assisted sensing, Phys. Rev. Lett. 130227201 (2023).
- L. Gammaitones et al.stochastic resonance, Rev.mod. Phys. 70223 (1998).
- JK Douglass et al.Noise enhancement of information transfer in shrimp mechanoreceptors by stochastic resonance, Nature 365337 (1993).
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