Matthew Chua

Carbon Nanotube-Based Artificial Tracheal Prosthesis: Carbon nanocomposite implants for patient-specific ENT care.

We have developed the first patient-specific carbon nanotube (CNT) composite artificial tracheal implant tested on a porcine model in vivo. The experimental subject has survived with the implant with no apparent problems. Carbon nanocomposite material and the patient-specific approach have also been used to develop a voice prosthesis device as well as new microclips for wound closure. This article presents our experimental investigation with the carbon nanocomposite materials for constructing patient-specific ear, nose, and throat (ENT) implants.

Development of a patient specific artificial tracheal prosthesis: Design, mechanical behavior analysis and manufacturing

There is a need to create patient specific organ replacements as there are differences in the anatomical dimensions among individuals. High failure rates in tracheal prosthesis are attributed to the lack of mechanical strength and flexibility, slow rate of growth of ciliated epithelium and leakage of interstitial fluid into the lumen. This paper proposes a methodology of design, simulations and fabrication of a patient specific artificial tracheal prosthesis for implantation to closely mimic the biomechanical properties of the natural trachea, and describes the prototype device and its materials. Results show that the patient-specific trachea prosthesis has mechanical properties approximate that of normal tracheal rings. The user centric tracheal prosthesis is demonstrated to be a promising candidate for tracheal replacement.

Patient-specific carbon nanocomposite tracheal prosthesis

Purpose Surgical removal of the trachea is the current gold standard for treating severe airway carcinoma and stenosis. Resection of 6 cm or more of the trachea requires a replacement graft due to anastomotic tension. The high failure rates of current grafts are attributed to a mismatching of mechanical properties and slow epithelium formation on the inner lumen surface. There is also a current lack of tracheal prostheses that are closely tailored to the patients anatomy. Methods We propose the development of a patient-specific, artificial trachea made of carbon nanotubes and poly-di-methyl-siloxane (CNT-PDMS) composite material. Computational simulations and finite element analysis were used to study the stress behavior of the designed implant in a patient-specific, tracheal model. Results Finite element studies indicated that the patient-specific carbon nanocomposite prosthesis produced stress distributions that are closer to that of the natural trachea. In vitro studies conducted on the proposed material have demonstrated its biocompatibility and suitability for sustaining tracheal epithelial cell proliferation and differentiation. In vivo studies done in porcine models showed no adverse side effects or breathing difficulties, with complete regeneration of the epithelium in the prosthesis lumen within 2 weeks. Conclusions This paper highlights the potential of a patient-specific CNT-PDMS graft as a viable airway replacement in severe tracheal carcinoma.

Probabilistic predictive modelling of carbon nanocomposites for medical implants design.

Modelling of the mechanical properties of carbon nanocomposites based on input variables like percentage weight of Carbon Nanotubes (CNT) inclusions is important for the design of medical implants and other structural scaffolds. Current constitutive models for the mechanical properties of nanocomposites may not predict well due to differences in conditions, fabrication techniques and inconsistencies in reagents properties used across industries and laboratories. Furthermore, the mechanical properties of the designed products are not deterministic, but exist as a probabilistic range. A predictive model based on a modified probabilistic surface response algorithm is proposed in this paper to address this issue. Tensile testing of three groups of different CNT weight fractions of carbon nanocomposite samples displays scattered stress-strain curves, with the instantaneous stresses assumed to vary according to a normal distribution at a specific strain. From the probabilistic density function of the experimental data, a two factors Central Composite Design (CCD) experimental matrix based on strain and CNT weight fraction input with their corresponding stress distribution was established. Monte Carlo simulation was carried out on this design matrix to generate a predictive probabilistic polynomial equation. The equation and method was subsequently validated with more tensile experiments and Finite Element (FE) studies. The method was subsequently demonstrated in the design of an artificial tracheal implant. Our algorithm provides an effective way to accurately model the mechanical properties in implants of various compositions based on experimental data of samples.

New Attenuation Predictive Model for Carbon-Based Nanocomposites

The use of carbon nanofibers (CNF) reinforced composites is popular among several industries such as healthcare, aerospace and defense as they have enhanced mechanical and thermal properties. CNF and carbon nanotubes (CNT) in the composites also improve damping and attenuation. We have been investigating its application for scaffold implants in human airways which undergoes vibratory stress and requires weight-sensitive sound proofing. This paper proposes a predictive model for the attenuation of sound waves through the composite that takes into consideration the Rayleigh scattering function, absorption, resonance and interfacial friction of the embedded fibers. These factors are dependent on the size, thickness, density, porosity, Young Modulus and volume fraction of the nanofibers or nanotubes. CNF reinforced poly-di-methyl-siloxane (PDMS) and single-walled CNT reinforced PDMS composites were investigated. Ultrasonic testing and measurement of sound wave attenuations through the material were done to validate the proposed model and results are shown to be consistent.

Experiments of carbon nanocomposite implants for patient specific ENT care

We have developed the first patient specific carbon nanotube composite artificial tracheal implant tested on a porcine model in vivo. The experimental subject has survived with the implant with no apparent problems. Carbon nanocomposite material and the patient specific approach have also been used to develop a voice prosthesis device, as well as new microclips for wound closure. This paper presents our experimental investigation with the carbon nanocomposite materials for constructing patient specific ENT implants.

Optimization of cell seeding in a 2D bio-scaffold system using computational models

The cell expansion process is a crucial part of generating cells on a large-scale level in a bioreactor system. Hence, it is important to set operating conditions (e.g. initial cell seeding distribution, culture medium flow rate) to an optimal level. Often, the initial cell seeding distribution factor is neglected and/or overlooked in the design of a bioreactor using conventional seeding distribution methods. This paper proposes a novel seeding distribution method that aims to maximize cell growth and minimize production time/cost. The proposed method utilizes two computational models; the first model represents cell growth patterns whereas the second model determines optimal initial cell seeding positions for adherent cell expansions. Cell growth simulation from the first model demonstrates that the model can be a representation of various cell types with known probabilities. The second model involves a combination of combinatorial optimization, Monte Carlo and concepts of the first model, and is used to design a multi-layer 2D bio-scaffold system that increases cell production efficiency in bioreactor applications. Simulation results have shown that the recommended input configurations obtained from the proposed optimization method are the most optimal configurations. The results have also illustrated the effectiveness of the proposed optimization method. The potential of the proposed seeding distribution method as a useful tool to optimize the cell expansion process in modern bioreactor system applications is highlighted.

Design and Characterization of a Soft Robotic Therapeutic Glove for Rheumatoid Arthritis

ABSTRACT The modeling and experimentation of a pneumatic actuation system for the development of a soft robotic therapeutic glove is proposed in this article for the prevention of finger deformities in rheumatoid arthritis (RA) patients. The Rehabilitative Arthritis Glove (RA-Glove) is a soft robotic glove fitted with two internal inflatable actuators for lateral compression and massage of the fingers and their joints. Two mechanical models to predict the indentation and bending characteristics of the inflatable actuators based on their geometrical parameters will be presented and validated with experimental results. Experimental validation shows that the model was within a standard deviation of the experimental mean for input pressure range of 0 to 2 bars. Evaluation of the RA-Glove was also performed on six healthy human subjects. The stress distribution along the fingers of the subjects using the RA-Glove was also shown to be even and specific to the finger sizes. This article demonstrates the modeling of soft pneumatic actuators and highlights the potential of the RA-Glove as a therapeutic device for the prevention of arthritic deformities of the fingers.

Design and evaluation of Rheumatoid Arthritis rehabilitative Device (RARD) for laterally bent fingers

This paper presents the design and evaluation of a soft-robotic exoskeleton, RARD, for the rehabilitation of arthritis affected individuals with laterally deformed fingers due to Heberdens nodes and Bouchards nodes. The exoskeleton operates using two 3D-printed soft pneumatic elastomeric actuators that are flexible to conform to the curvature of the deformity when not pressurized. Upon pressurization, the actuators can generate sufficient force to overcome the stiffness of the deformed fingers to realign them straight, allowing for progressive rehabilitation. Experimental study was performed on the designed pneumatic actuators to characterize its maximum bending force output from the pressure input. Additionally, the effectiveness of the exoskeleton was evaluated using a human mannequin hand with the simulated deformity. The soft-robotic exoskeleton has been demonstrated to be a promising rehabilitative device for treating laterally deformed digits on the hands.

Effects of visual feedback on motion mimicry ability during video-based rehabilitation

Abstract The motion mimicry ability of patients facilitates execution of therapy moves based on visual observation of rehabilitation exercise videos, which can help speed up the recovery process. This study investigates the effects of visual feedback on the mimicking ability of human subjects in video-based rehabilitation. Inertial Measurement Unit (IMU) sensors was used, which provide a portable system to detect human motion tracking, allowing for experiments to be conducted without space restrictions and provide a greater variety of actions that can be tested. In the experiment, healthy subjects were shown a video of an instructor performing a certain movement task and had to mimic actions to the best of their ability. A real-time visual feedback system, based on input data from IMU sensors, was introduced to inform subjects of the accuracy of their mimicking actions. Subjects were tested with and without feedback and the relevant joint angle data was collected to determine the individual’s mimicking ability. Our results showed a significant improvement in subject’s mimicking ability from “no feedback” to “feedback” condition. The key implication of the findings is that visual feedback provides an extrinsic source that allows patients to better synchronize their hand-eye coordination during mimicry. Potential prospective works will investigate the relevance of motion mimicry mechanism in home-based rehabilitation.