Detection of weak biological signal utilizing stochastic resonance in a GaAs-based nanowire FET and its parallel summing network

Imai, Yasuhiko; Sato, Masaki; Tanaka, Takayuki; Kasai, Seiya; Hagiwara, Yosuke; Ishizaki, Haruya; Kuwabara, Sumio; Arakawa, Takahiko

doi:10.7567/jjap.53.06je01

Cited by 7 publications

(4 citation statements)

References 48 publications

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“…The EMG signals can be obtained by detecting the electrical potential generated by muscle cells when the muscle was contracted, thereby providing the information of the movement in human body. 30) For this reason, the application of EMG sensors is practical for diagnosing the medical issues of nerves and muscles such as muscles damage and neuropathy. The inset of Fig.…”

Section: Experimental Methodsmentioning

confidence: 99%

Wearable carbon nanotube based dry-electrodes for electrophysiological sensors

Kang¹,

Ha²

2018

Jpn. J. Appl. Phys.

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In this paper, we demonstrate all-solution-processed carbon nanotube (CNT) dry-electrodes for the detection of electrophysiological signals such as electrocardiograms (ECG) and electromyograms (EMG). The key parameters of P, Q, R, S, and T peaks are successfully extracted by such CNT based dry-electrodes, which is comparable with conventional silver/chloride (Ag/AgCl) wet-electrodes with a conducting gel film for the ECG recording. Furthermore, the sensing performance of CNT based dry-electrodes is secured during the bending test of 200 cycles, which is essential for wearable electrophysiological sensors in a non-invasive method on human skin. We also investigate the application of wearable CNT based dry-electrodes directly attached to the human skins such as forearm for sensing the electrophysiological signals. The accurate and rapid sensing response can be achieved by CNT based dry-electrodes to supervise the health condition affected by excessive physical movements during the real-time measurements.

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Section: Experimental Methodsmentioning

confidence: 99%

Wearable carbon nanotube based dry-electrodes for electrophysiological sensors

Kang¹,

Ha²

2018

Jpn. J. Appl. Phys.

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“…There is an attempt to use stochastic resonance when detecting weak biological signals from the surface of the human body. By using a system of parallelized GaAs nanowire FETs, electromyography is obtained from the human upper arm via stochastic resonance phenomena with noise from living organisms [123]. It was reported that by utilizing biologically derived noise, signals with high SNR were succeeded in detection.…”

Section: Artificial System Using Noisementioning

confidence: 99%

Stochastic Resonance in Organic Electronic Devices

Suzuki

Asakawa

2022

Polymers

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Stochastic Resonance (SR) is a phenomenon in which noise improves the performance of a system. With the addition of noise, a weak input signal to a nonlinear system, which may exceed its threshold, is transformed into an output signal. In the other words, noise-driven signal transfer is achieved. SR has been observed in nonlinear response systems, such as biological and artificial systems, and this review will focus mainly on examples of previous studies of mathematical models and experimental realization of SR using poly(hexylthiophene)-based organic field-effect transistors (OFETs). This phenomenon may contribute to signal processing with low energy consumption. However, the generation of SR requires a noise source. Therefore, the focus is on OFETs using materials such as organic materials with unstable electrical properties and critical elements due to unidirectional signal transmission, such as neural synapses. It has been reported that SR can be observed in OFETs by application of external noise. However, SR does not occur under conditions where the input signal exceeds the OFET threshold without external noise. Here, we present an example of a study that analyzes the behavior of SR in OFET systems and explain how SR can be made observable. At the same time, the role of internal noise in OFETs will be explained.

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“…26) We already confirmed that the SRbased technique can achieve a higher SNR than the conventional technique. 27) The purpose of this study is to investigate a robust EMG signal detection technique by combining SR and a flexible multiple surface electrode array to achieve both the increase in sensitivity and elimination of contact fluctuation. We introduce the novel use of carbon nanotube composite paper (CNT-cp) as the surface electrode material, which is flexible and easy to handle.…”

Section: Introductionmentioning

confidence: 99%

Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

Shirata

Inden

Kasai

et al. 2016

Jpn. J. Appl. Phys.

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We investigated the robust detection of surface electromyogram (EMG) signals based on the stochastic resonance (SR) phenomenon, in which the response to weak signals is optimized by adding noise, combined with multiple surface electrodes.Flexible carbon nanotube composite paper (CNT-cp) was applied to the surface electrode, which showed good performance that is comparable to that of conventional Ag/AgCl electrodes. The SR-based EMG signal system integrating an 8-Schmitt-trigger network and the multiple-CNT-cp-electrode array successfully detected weak EMG signals even when the subject's body is in the motion, which was difficult to achieve using the conventional technique. The feasibility of the SR-based EMG detection technique was confirmed by demonstrating its applicability to robot hand control.2

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Detection of weak biological signal utilizing stochastic resonance in a GaAs-based nanowire FET and its parallel summing network

Cited by 7 publications

References 48 publications

Wearable carbon nanotube based dry-electrodes for electrophysiological sensors

Wearable carbon nanotube based dry-electrodes for electrophysiological sensors

Stochastic Resonance in Organic Electronic Devices

Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

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