A Multimodal, Adjustable Sensitivity, Digital 3-Axis Skin Sensor Module

Holgado, Alexis C.; Tomo, Tito Pradhono; Somlor, Sophon; Sugano, Shigeki

doi:10.3390/s20113128

Cited by 10 publications

(2 citation statements)

References 33 publications

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“…In this study, the ultrasound and inductive coupling-based WPT systems were classified as systems suitable to operate at frequencies less than 50MHz, whereas the microwave WPT systems were classified to operate at higher frequencies. A skin biosensor provided with a module having adjustable sensitivity was introduced in [17]. A certain technique was devised for the proposed biosensor to measure the changes in the position of a magnetic field generated by using an electromagnetic device located on a flexible material.…”

Section: A Literature Review Of Recent Workmentioning

confidence: 99%

Wireless Power and DATA Transfer to Deeply-Embedded Biosensors in Human Body

Obais¹

2022

IJETAE

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The process of transmitting power from one node to another via physical links without using wires is denoted as wireless power transfer (WPT). WPT plays an important role in medical applications for it offers the possibility of avoiding surgical operations during the replacement of embedded batteries in human body. In this paper, a WPT system for transferring power and DATA to deeply embedded biosensors is proposed. The system is designed such that it is capable of powering a biosensor simultaneously with DATA transmission from a transmitting coil located outside the human body at a distance of 100mm from the biosensor node. The simulation results have revealed the reception of a regulated DC voltage at the biosensor node of 1.2V, which is sufficient to charge a rechargeable embedded battery with an average DC current of 1.1mA. The results also reveal that the proposed system has succeeded in the extraction of the transmitted DATA at the biosensor side within a time of 30µs. The transmitter of the proposed WPT system is driven by a Class-E power source, which has accomplished a drain efficiency of 72% at an overall operating power of 6W. The proposed system is designed and verified on PSpice.

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Section: A Literature Review Of Recent Workmentioning

confidence: 99%

Wireless Power and DATA Transfer to Deeply-Embedded Biosensors in Human Body

Obais¹

2022

IJETAE

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“…The simplest approach can be found in [31], where e-skin touch calibration was performed based on a reference in the form of weights of known mass manually placed at selected locations on the e-skin surface. In [32], an XY table and a voice coil were used to exert the force. Linear, quadratic, and cubic polynomial models were fitted to data to calibrate the example sensor.…”

Section: Introductionmentioning

confidence: 99%

Robot-Based Calibration Procedure for Graphene Electronic Skin

Klimaszewski

Wildner

Ostaszewska-Liżewska

et al. 2022

Sensors

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The paper describes the semi-automatised calibration procedure of an electronic skin comprising screen-printed graphene-based sensors intended to be used for robotic applications. The variability of sensitivity and load characteristics among sensors makes the practical use of the e-skin extremely difficult. As the number of active elements forming the e-skin increases, this problem becomes more significant. The article describes the calibration procedure of multiple e-skin array sensors whose parameters are not homogeneous. We describe how an industrial robot equipped with a reference force sensor can be used to automatise the e-skin calibration procedure. The proposed methodology facilitates, speeds up, and increases the repeatability of the e-skin calibration. Finally, for the chosen example of a nonhomogeneous sensor matrix, we provide details of the data preprocessing, the sensor modelling process, and a discussion of the obtained results.

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NARX Recurrent Neural Network Model of the Graphene-Based Electronic Skin Sensors with Hysteretic Behaviour

Możaryn¹

2023

Lecture Notes in Networks and Systems

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The electronic skin described in the article comprises screen-printed graphene-based sensors, intended to be used for robotic applications. The precise mathematical model allowing the touch pressure estimation is required during its calibration. The article describes the recurrent neural network model for graphene-based electronic skin calibration, in which parameters are not homogeneous, and the touch force characteristics have visible hysteretic behaviour. The presented method provides a simple alternative to the models known in the literature.

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A Multimodal, Adjustable Sensitivity, Digital 3-Axis Skin Sensor Module

Cited by 10 publications

References 33 publications

Wireless Power and DATA Transfer to Deeply-Embedded Biosensors in Human Body

Wireless Power and DATA Transfer to Deeply-Embedded Biosensors in Human Body

Robot-Based Calibration Procedure for Graphene Electronic Skin

NARX Recurrent Neural Network Model of the Graphene-Based Electronic Skin Sensors with Hysteretic Behaviour

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