3D Printed sensors and bio-electronics for robotic applications

Martijn Schouten

Research output: ThesisPhD Thesis - Research UT, graduation UT

147 Downloads (Pure)

Abstract

When using an exoskeleton, it is important to measure the interaction force and user intention. To accomplish this, force and surface electromyography (sEMG) sensors often are integrated into the exoskeleton. However, this requires complex parts and exoskeletons are often made in low quantities. Therefore, 3D printing these exoskeleton parts with integrated sensors is of potential interest. In order to do that, three things need to be researched.

The first research topic is a multi-material fabrication process that is able to print sensors and the embedding parts in one go. Therefore an overview of the currently available techniques for extrusion-based printing and the remaining challenges is given. Next, some remaining challenges will be addressed. These are: the calibration of multiple printheads relative to each other and how to check the quality of layers of 3D printed conductors.

The second research topic is a way to 3D print usable force sensors. There are two common ways to do this; one is to make a resistive sensor and the other is to make a capacitive sensor. Resistive sensors are easy to print but are often non-linear and have large hysteresis. A way to linearize these sensors by using differential measurements and a way to reduce the hysteresis by using a model are presented. Another way to make more linear sensors is to fabricate capacitive sensors. In this work, it is shown that with a flexible dielectric and a simple parallel plate structure sub-newton sensitivities can be achieved. Subsequently four of these sensors are combined to form a sensor that can measure both shear and normal forces. It was also noted that these sensors have a position-dependent response at high frequencies because of the high electrode resistance. This allowed the measurement of not only the force but also the position of the force by looking at the real and imaginary parts of the impedance of the sensors.

The third research topic is a way to print, connect and read out sEMG electrodes. Printing the electrodes is relatively straightforward. However, they form a dry electrode-skin interface and therefore they have a higher impedance than regular AgCl electrodes, imposing higher demands on the amplifier input impedance. Also, the electrodes need to stay in contact with the skin during movement to prevent the resulting signal from containing motion artifacts. Therefore, an amplifier that contains several techniques to improve the input impedance and a method that enables simultaneously measurement of the electrode impedance was developed. To connect the sEMG electrodes to the amplifier, pogo pins that connect to silver ink traces in the print were added to the amplifier. These pogo-pins allow a solderless connection of the sensors.

Yet another challenge is that only limited information can be obtained with a low number of 3D printed or conventional sEMG electrodes. Therefore, the use of multifrequency electrical impedance myography (mfEIM) is also explored. To do this, a multifrequency spectrometer that can measure both the sEMG and the mfEIM was developed. Then this spectrometer was connected to subjects performing tasks in a one degree of freedom exoskeleton that measures joint angle and joint torque. These measurements showed that mfEIM can provide additional information about the joint angle.

By researching these three research topics, 3D printed parts with integrated sensors are one step closer to reality.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • Krijnen, G. , Supervisor
  • Abayazid, Momen, Co-Supervisor
Award date17 May 2023
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5619-4
Electronic ISBNs978-90-365-5620-0
DOIs
Publication statusPublished - 17 May 2023

Fingerprint

Dive into the research topics of '3D Printed sensors and bio-electronics for robotic applications'. Together they form a unique fingerprint.

Cite this