Brain-machine interface (BMI) is a device that translates neuronal information into commands, which is capable of controlling external software or hardware, such as a computer or robotic arm. In consequence, the electrodes with desirable electrical and mechanical properties for direct interacting between neural tissues and machines serves as the crucial and critical part of BMI technology. Nowadays, the development of material science provides many advanced electrodes for neural stimulating and recording. Particularly, the widespread applications of nanotechnologies have innovatively introduced biocompatible electrode that can have similar characteristics with neural tissue. This paper reviews the existing problems and discusses the latest development of electrode materials for BMI, including conducting polymers, silicon, carbon nanowires, graphene, and hybrid organic-inorganic nanomaterials. In addition, we will inspect at the technical and scientific challenges in the development of neural electrode for a broad application of BMI with focus on the biocompatibility, mechanical mismatch, and electrical performance of electrode materials.
In anisotropic conductive adhesive (ACA) interconnections, the particles are electrical conductors providing current paths in the fine pitch electronic packaging as well as physical parts connecting with the chip bumps and the substrate pads through the mechanical deformation interfaces. The primary object of this fundamental research is to reveal the electrical conductive characteristics of Ni/Au coated resin particles. Such an ACA particle resistance is resulted from two metal coated layers, which are two parallel resistors in the circuit determined by the particle transformation degree. In order to investigate the effect of the particle transformation degree upon the particle resistance, the particle transformation factor is defined. The mathematical electrical resistance function of an ACA particle, an integral function of the transformation factor and the particle geometries, resin diameter, nickel layer thickness, and gold layer thickness, is worked out from the physical model of an ACA particle. To carry out the solutions of the function, MathCAD software is applied. According to the numerical solutions, the deeper the particle transformation, the thicker the metal coated layer thicknesses and the longer the resin diameter are, the lower the particle resistance is. In conclusion, it is stated that the ACA particle resistance is determined by the particle transformation and the particle geometries, however, the transformation and the nickel layer thickness are more sensitive than the resin diameter and the gold layer thickness. Finally, the resistance function will explain the conductive mechanism of the deformed ACA particle.
We demonstrate a microseismometer with a 2ng/rtHz noise floor capable of autonomous operation over a wide range of tilts. This represents the highest performance yet achieved by a silicon-based vibration sensor. The microseismometer builds on previous development of a shortperiod seismometer for NASA's 2016 InSight mission to Mars . The deep-reactive-ion-etched sensor element is unique in that it uses a spring-mass system with a proof mass that moves laterally. This minimizes the damping of the spring mass systems without the need for vacuum encapsulation. The proof-mass position is sensed by a periodic linear capacitive array transducer allowing highly sensitive position detection combined with feedback control at multiple null points. Operation at any of these points enables the sensor to function over a large tilt range without compromising the noise performance. As well as the capacitive sensing elements, the proof mass has planar coils on the surface to electromagnetic actuator when placed in a static magnetic field. The MEMS sensor element is connected to an electronics feedback circuit similar to those used in broad-band seismometers allowing the sensor to act as a velocity output force balance transducer.
Device–body interface is significant for acquiring high quality bio‐signals, preventing skin‐irritation, and minimizing the motion artifacts. However, low breathability of the typical substrate used in a flexible electronic device usually deteriorates the stability of device–body interface, which is imperative for long‐term application but commonly disregarded. In paper, a directional sweat transport and breathable electrode with three‐layer sandwiched structure is reported. The top hydrophilic hydrolyzed‐polyacrylonitrile (HPAN) layer and middle hydrophobic thermoplastic‐polyurethane (TPU) layer form Janus structure; and the bottom layer is an electrode layer of Ag nanowires (AgNWs). This dedicatedly designed electrode can transport sweat from skin to the top HPAN layer, while keeping low noise electrocardiogram (ECG) signal detection. In the trial of ECG monitoring, the results show that the electrode can achieve reliable recording with high signal noise rate (SNR) both in calm state (10.5 dB) and sweaty state (10.1 dB) with sweat tolerance. No allergy or obvious SNR degeneration is observed when utilizing the electrode owing to the effective sweat transport away from the device–body interface rather than accumulation. Finally, the application of the anti‐sweat accumulating electrode in wearable electronics is demonstrated.
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