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

Abstract

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

Single-trap phenomena stochastic switching for noise suppression in nanowire FET biosensors

“…g-factor) and fluctuations of this parameter are the noise. Therefore, the use of STP allows suppression of lowfrequency noise in an approach that is similar to the stochastic resonance effect [23][24][25][26][27] taking into account that RTS is a stochastic switching process that can be considered as a white noise below a cut-off frequency. The idea beyond this is the discrete nature of RTS noise generated by a bistable stochastically driven single trap in a nanosensor device.…”

Wearable carbon nanotube based dry-electrodes for electrophysiological sensors

“…For this reason, a non-invasive method such as surface electromyography using the surface electrodes for electrophysiological sensors has been extensively attracted. 16,17) However, the sensing accuracy is relatively low compared to the invasive method even though the non-invasive method can avoid the bleeding with pain.…”