Here, AZoSensors explores the impact noisy environments have on sensor technologies, as well as new research suggesting that noise could benefit sensors in healthcare applications.
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What is a Noisy Environment and How Can It Affect Equipment?
Sensor technology is becoming increasingly important. Sensors are vital for the functioning of our everyday gadgets, from smartphones and smartwatches to fitness trackers and smart home devices, as well as cutting-edge technologies for agriculture, healthcare, food and beverage, automotive and more. Sensor technology is developing alongside the evolution of the Internet of Things (IoT), which connects our world, helping us automate it and make it more efficient.
Sensors, however, are not immune to noise. This noise can come in many forms, depending on what the sensor is designed to measure. Overall, the concept of noise refers to random fluctuations in activity that disturb the data, adding in information that is not necessarily related to the thing that is being measured, thus making it more difficult to detect the true signal.
How Do External Factors Influence Sensor Systems?
Efforts to mitigate the impact of noise on sensors have mostly focussed on noise filtering or active noise cancellation. Scientists have discovered that noise, however, can be beneficial to sensors. Stochastic resonance is the name given to this phenomenon. It refers to the sensitivity of a system to a certain input signal being enhanced by the presence of noise.
A signal that is buried in noise can become easier to detect when more noise is added in. In essence, in these cases adding in noise cleans up the signal, making it easier to detect. Stochastic resonance impacts both natural and artificial systems, such as biological systems, electronic circuits, and mechanical devices.
Recently, a team of scientists at the University of Singapore has demonstrated how stochastic resonance can be induced to improve sensitivity in a mechanical sensor. They reported that to achieve this effect, it was vital to operate the device in close proximity to an exceptional point (EP), where the nonlinearity is strong.
Resonating systems that transfer and receive energy to and from their environment are capable of generating an EP. These systems tend to have resonant frequencies that they are inclined to vibrate at naturally, without the presence of a driving force. Two resonant frequencies may cross paths at the EP and can introduce nonlinear behavior. As a result, the system may seem to respond to a small signal.
The scientists at the University of Singapore showed that noise can induce EPs at random moments, temporarily increasing the sensitivity of the sensor. In these moments, an input signal that is usually too weak to be detected now produces an output signal. Their study, therefore, shows that noise can enhance the performance of a sensor by stochastic resonance.
To demonstrate this, the scientists devised an experiment using a movement sensor constructed of two pairs of patches with silver thread woven into the material. The first pair of sensors were placed on the skin, and the second pair was fixed onto a garment, overlaying the first. The patches behave as charged capacitor plates in an electrical circuit, also known as an LC resonator. When the person moves, the distance between the two resonators changes.
Small movements, even breathing, can trigger a change in coupling between the resonators. This change impacts the resonant frequency of the second pair of patches worn on the clothing. The scientists collected information for this second pair of patches, using it as the output signal.
When the wearer’s movements became more vigorous, the noise of the input increased. This generated stochastic EPs in the sensor and enchanted the sensitivity of the sensor, as predicted. As the noise increased, this caused the sensor’s signal-to-noise ratio to also rise until reaching a maximum. After this point, the signal-to-noise ratio declined again, thus forming the pattern synonymous with stochastic resonance. Therefore, the sensor could continue monitoring respiration despite the noise caused by walking.
How Could This New Development Help Sensor Systems Work Better in Noisy Environments?
The team at the University of Singapore believes that their study demonstrates how stochastic resonance could be exploited by healthcare monitoring. The method has the potential to be developed into systems that monitor various biological factors, such as heart rate, gait, and sweat production. Their system also has the potential to be developed into platforms that sense various environmental parameters such as pressure, humidity, and temperature.
Overall, the study shows how noise can be leveraged to improve the sensitivity of sensors. The methodology used in the experiment has the potential to be used in many real-world applications.
This research may lead to the development of more effective sensors for both healthcare and environmental monitoring. It also highlights the importance of exploring the phenomenon of stochastic resonance.
References and Further Reading
Environmental Noise Makes a Sensor More Sensitive [Online]. Physics. Available at: https://physics.aps.org/articles/v16/94#c1
Li, Z. et al. (2023) Stochastic exceptional points for noise-assisted sensing, Physical Review Letters, 130(22). doi:10.1103/physrevlett.130.227201.
McDonnell, M.D. and Abbott, D. (2009) What is stochastic resonance? definitions, misconceptions, debates, and its relevance to biology, PLoS Computational Biology, 5(5). https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000348