Development of Soft sEMG Sensing Structures Using 3D-Printing Technologies

Recent advances of additively manufactured noninvasive kinematic biosensors

The necessity of reliable measurement data assessment in the realm of human life has experienced exponential growth due to its extensive utilization in health monitoring, rehabilitation, surgery, and long-term treatment. As a result, the significance of kinematic biosensors has substantially increased across various domains, including wearable devices, human-machine interaction, and bioengineering. Traditionally, the fabrication of skin-mounted biosensors involved complex and costly processes such as lithography and deposition, which required extensive preparation. However, the advent of additive manufacturing has revolutionized biosensor production by facilitating customized manufacturing, expedited processes, and streamlined fabrication. AM technology enables the development of highly sensitive biosensors capable of measuring a wide range of kinematic signals while maintaining a low-cost aspect. This paper provides a comprehensive overview of state-of-the-art noninvasive kinematic biosensors created using diverse AM technologies. The detailed development process and the specifics of different types of kinematic biosensors are also discussed. Unlike previous review articles that primarily focused on the applications of additively manufactured sensors based on their sensing data, this article adopts a unique approach by categorizing and describing their applications according to their sensing frequencies. Although AM technology has opened new possibilities for biosensor fabrication, the field still faces several challenges that need to be addressed. Consequently, this paper also outlines these challenges and provides an overview of future applications in the field. This review article offers researchers in academia and industry a comprehensive overview of the innovative opportunities presented by kinematic biosensors fabricated through additive manufacturing technologies.

Electrically Conductive Fused Deposition Modeling Filaments: Current Status and Medical Applications

Fused Deposition Modeling (FDM) is one of the most popular three dimensional (3D) printing techniques especially among researchers. Recently, FDM has been widely developed and improved in many areas. One of these improvements is the introduction of electrically conductive filaments. In general, conductive filaments are usually made of conductive polymer composites. These composites consist of a thermoplastic material blended with carbon-based materials. The quantity of commercially available conductive filaments has grown significantly in recent years. This paper presents a sample of currently available conductive filaments (eight filaments were chosen). These samples were compared by measuring resistance value and highlighting resulted defects of each sample. Additionally, this paper searched and reviewed articles that used conductive FDM filaments in medical applications. These articles were collected and summarized in terms of name of filaments were used, the specific function of the printed conductive object, and name of the printer used to print the conductive object. In conclusion, the main purpose of this project is to facilitate the work of future medical researchers who would like to use commercially available conductive FDM filaments.

3d Printed Bio-potential Dry Electrodes

The most commonly used bio-potential electrodes are silver/silver chlorides gel-electrodes (Ag/AgCl electrodes). However, wet electrodes are not suited for daily usage and long-term monitoring. Dry electrodes are the best choice for long-term measurements. Dry electrodes can be fabricated using various methods and materials; one of these methods is three dimensional (3d) printing. 3d printing is a cost-effective method and can be easily used in mass production. This paper will present 3d printed bio-potential dry electrodes using five different commercially available fused deposition modeling (FDM) electrically conductive filaments. Then, these printed electrodes will be tested and validated using electrocardiogram (ECG) portable acquisition system. Three out of five filaments were printed successfully. Collected ECG data from these electrodes showed acceptable quality with Signal to Noise Ratios (SNRs) ranging around 20 dB when compared with wet electrodes collected raw data as a reference. In conclusion, this study designed and printed a 100% 3d printed electrodes from three different FDM filaments which could be used efficiently for ECG signal monitoring in resting position.

4D printing of soft orthoses for tremor suppression

Tremor is an involuntary and oscillatory movement disorder that makes daily activities difficult for affected patients. Hand tremor-suppression orthoses are noninvasive, wearable devices designed to mitigate tremors. Various studies have shown that these devices are effective, economical, and safe; however, they have drawbacks such as large weight, awkward shape, and rigid parts. This study investigates different types of tremor-suppression orthoses and discusses their efficiency, mechanism, benefits, and disadvantages. First, various orthoses (with passive, semi-active, and active mechanisms) are described in detail. Next, we look at how additive manufacturing (AM) has progressed recently in making sensors and actuators for application in tremor orthoses. Then, the materials used in AM are further analyzed. It is found that traditional manufacturing problems can be solved with the help of AM techniques, like making orthoses that are affordable, lighter, and more customizable. Another concept being discussed is using smart materials and AM methods, such as four-dimensional (4D) printing, to make orthoses that are more comfortable and efficient.

Graphic abstract

Improved Motion Classification With an Integrated Multimodal Exoskeleton Interface

Human motion intention detection is an essential part of the control of upper-body exoskeletons. While surface electromyography (sEMG)-based systems may be able to provide anticipatory control, they typically require exact placement of the electrodes on the muscle bodies which limits the practical use and donning of the technology. In this study, we propose a novel physical interface for exoskeletons with integrated sEMG- and pressure sensors. The sensors are 3D-printed with flexible, conductive materials and allow multi-modal information to be obtained during operation. A K-Nearest Neighbours classifier is implemented in an off-line manner to detect reaching movements and lifting tasks that represent daily activities of industrial workers. The performance of the classifier is validated through repeated experiments and compared to a unimodal EMG-based classifier. The results indicate that excellent prediction performance can be obtained, even with a minimal amount of sEMG electrodes and without specific placement of the electrode.

3D Printing Polymeric Materials for Robots with Embedded Systems

The fabrication of robots and their embedded systems is challenging due to the complexity of the interacting components. The integration of additive manufacturing (AM) to robotics has made advancements in robotics manufacturing through sophisticated and state-of-the-art AM technologies and materials. With the emergence of 3D printing, 3D printing materials are also being considered and engineered for specific applications. This study reviews different 3D printing materials for 3D printing embedded robotics. Materials such as polyethylene glycol diacrylate (PEGDA), acrylonitrile butadiene styrene (ABS), flexible photopolymers, silicone, and elastomer-based materials were found to be the most used 3D printing materials due to their suitability for robotic applications. This review paper revealed that the key areas requiring more research are material formulations for improved mechanical properties, cost, and the inclusion of materials for specific applications. Future perspectives are also provided.

A 3D-Printed Soft Fingertip Sensor for Providing Information about Normal and Shear Components of Interaction Forces

Sensing of the interaction forces at fingertips is of great value in assessment and rehabilitation therapy. Current force sensors are not compliant to the fingertip tissue and result in loss of touch sensation of the user. This work shows the development and characterization of a flexible fully-3D-printed piezoresistive shear and normal force sensor that uses the mechanical deformation of the finger tissue. Two prototypes of the sensing structure are evaluated using a finite element model and a measurement setup that applies normal and shear forces up to 10 N on a fingertip phantom placed inside the sensing structure, which is fixed to prevent slippage. Furthermore, the relation between strain (rate) and resistance of the conductive TPU, used for the strain gauges, is characterized. The applied normal and shear force components of the 3D-printed sensing structure can be partly separated. FEM analysis showed that the output of the sensor is largely related to the sensor geometry and location of the strain gauges. Furthermore, the conductive TPU that was used has a negative gauge factor for the strain range used in this study and might cause non-linear behaviors in the sensor output.

Integration of a Passive Exoskeleton and a Robotic Supernumerary Finger for Grasping Compensation in Chronic Stroke Patients: The SoftPro Wearable System

Upper-limb impairments are all-pervasive in Activities of Daily Living (ADLs). As a consequence, people affected by a loss of arm function must endure severe limitations. To compensate for the lack of a functional arm and hand, we developed a wearable system that combines different assistive technologies including sensing, haptics, orthotics and robotics. The result is a device that helps lifting the forearm by means of a passive exoskeleton and improves the grasping ability of the impaired hand by employing a wearable robotic supernumerary finger. A pilot study involving 3 patients, which was conducted to test the capability of the device to assist in performing ADLs, confirmed its usefulness and serves as a first step in the investigation of novel paradigms for robotic assistance.

Modelling of Anisotropic Electrical Conduction in Layered Structures 3D-Printed with Fused Deposition Modelling

3D-printing conductive structures have recently been receiving increased attention, especially in the field of 3D-printed sensors. However, the printing processes introduce anisotropic electrical properties due to the infill and bonding conditions. Insights into the electrical conduction that results from the anisotropic electrical properties are currently limited. Therefore, this research focuses on analytically modeling the electrical conduction. The electrical properties are described as an electrical network with bulk and contact properties in and between neighbouring printed track elements or traxels. The model studies both meandering and open-ended traxels through the application of the corresponding boundary conditions. The model equations are solved as an eigenvalue problem, yielding the voltage, current density, and power dissipation density for every position in every traxel. A simplified analytical example and Finite Element Method simulations verify the model, which depict good correspondence. The main errors found are due to the limitations of the model with regards to 2D-conduction in traxels and neglecting the resistance of meandering ends. Three dimensionless numbers are introduced for the verification and analysis: the anisotropy ratio, the aspect ratio, and the number of traxels. Conductive behavior between completely isotropic and completely anisotropic can be modeled, depending on the dimensionless properties. Furthermore, this model can be used to explain the properties of certain 3D-printed sensor structures, like constriction-resistive strain sensors.