Neural sensor translation

2019 ◽  
Author(s):  
Md Abu Sayeed Mondol ◽  
John A. Stankovic
Keyword(s):  
Neural Sensor

scholarly journals A Programmable Multi-Biomarker Neural Sensor for Closed-Loop DBS

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 230-244 ◽  
Author(s):  
Mahboubeh Parastarfeizabadi ◽  
Abbas Z. Kouzani ◽  
Jaclyn Beckinghausen ◽  
Tao Lin ◽  
Roy V. Sillitoe
Keyword(s):  
Closed Loop ◽  
Neural Sensor

A highly stretchable and deformation-insensitive bionic electronic exteroceptive neural sensor for human-machine interfaces

Nano Energy ◽  
2021 ◽  
Vol 80 ◽  
pp. 105548
Author(s):  
Xinqin Liao ◽  
Wensong Wang ◽  
Liang Wang ◽  
Haoran Jin ◽  
Lin Shu ◽  
...  
Keyword(s):  
Human Machine Interfaces ◽  
Highly Stretchable ◽  
Neural Sensor

Integrated Double-Sided Neural Sensor With Dry-Etch BCB

2010 ◽  
Vol 1 (2) ◽  
Author(s):  
Bruce Kim ◽  
Haixin Zhu ◽  
Jiping He
Keyword(s):  
Neural Recording ◽  
Packaging Material ◽  
Channel Number ◽  
Test Results ◽  
Surface Micromachining ◽  
Electrode Structure ◽  
Novel Structure ◽  
Neural Sensor ◽  
Dry Etch

This paper presents a novel structure for a neural sensor using a surface micromachining technique with dry-etch benzocyclobutene selected as the substrate and packaging material. The finished device has intracortical recording sites on both sides and epidural recording sites on the front. The design doubled the total channel number of recording sites compared with the conventional single-sided electrode structure. The developed process shows reliable, high fabrication yield, and preliminary fabrication and impedance test results suggest that this newly developed neural sensor could improve the performance and efficiency of neural recording.

A fully-integrated 10.5µW miniaturized (0.125mm2) wireless neural sensor

2012 ◽  
Author(s):  
D. Yeager ◽  
W. Biederman ◽  
N. Narevsky ◽  
E. Alon ◽  
J. Rabaey
Keyword(s):  
Fully Integrated ◽  
Neural Sensor

Neural sensor fusion for spatial visualization on a mobile robot

1998 ◽  
Author(s):  
Siegfried Martens ◽  
Gail A. Carpenter ◽  
Paolo Gaudiano
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Spatial Visualization ◽  
Neural Sensor

Surface modification of a neural sensor using graphene

2013 ◽  
Vol 94 ◽  
pp. 42-48 ◽  
Author(s):  
ChengWei Chiu ◽  
Xingliang He ◽  
Hong Liang
Keyword(s):  
Surface Modification ◽  
Neural Sensor

scholarly journals Research on Navigation and Positioning Technology of Intelligent Accompanying Tool Car in Dispatching Automation Computer Room

2021 ◽  
Vol 261 ◽  
pp. 01032
Author(s):  
Yufei Song ◽  
Yu Shi ◽  
Tianquan Li ◽  
Xudong Cao ◽  
Xiaohang Liu ◽  
...  
Keyword(s):  
Experimental Test ◽  
Experimental Results ◽  
Vector Map ◽  
Machine Room ◽  
Neural Sensor ◽  
Navigation Method ◽  
Working Point

In view of the wide variety of equipment in the dispatch automation machine room and the dense arrangement of cabinets, a navigation technology suitable for the dispatch automation machine room is proposed on the intelligent companion tool cart. In this paper, three sensors of ultrasonic, infrared and lidar are designed to form an intelligent neural sensor, and the information received by the intelligent neural sensor is calculated to generate a vector map through a software algorithm. At the same time, a plane coordinate network is established. The grid coordinate unit accuracy is 0.1cm. At the same time, the concept of “virtual fence” was put forward to fix the workers at the working point, which increased the safety of work. Subsequently, an experimental test of positioning and navigation of the tool cart was carried out. The experimental results showed that the tool cart can accurately locate and generate a vector map with an accuracy error of less than 10cm. The navigation method has a good application effect and has a good promotion value.

scholarly journals Simulating Displacement and Velocity Signals by Piezoelectric Sensor in Vibration Control Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
G. J. Sheu ◽  
S. M. Yang ◽  
W. L. Huang
Keyword(s):  
Vibration Control ◽  
Vibration Suppression ◽  
Piezoelectric Sensor ◽  
Smart Structure ◽  
Velocity Signal ◽  
Active Mass ◽  
Mass Damper ◽  
Active Mass Damper ◽  
Physical Geometry ◽  
Neural Sensor

Intelligent structures with built-in piezoelectric sensor and actuator that can actively change their physical geometry and/or properties have been known preferable in vibration control. However, it is often arguable to determine if measurement of piezoelectric sensor is strain rate, displacement, or velocity signal. This paper presents a neural sensor design to simulate the sensor dynamics. An artificial neural network with error backpropagation algorithm is developed such that the embedded and attached piezoelectric sensor can faithfully measure the displacement and velocity without any signal conditioning circuitry. Experimental verification shows that the neural sensor is effective to vibration suppression of a smart structure by embedded sensor/actuator and a building structure by surface-attached piezoelectric sensor and active mass damper.

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