In this work, a cost-effective, scalable pneumatic silicone actuator array is introduced, designed to dynamically conform to the user’s skin and thereby alleviate localised pressure within a prosthetic socket. The appropriate constitutive models for developing a finite element representation of these actuators are systematically identified, parametrised, and validated. Employing this computational framework, the surface deformation fields induced by 270 variations in soft actuator array design parameters under realistic load conditions are examined, achieving predictive accuracies within 70 µm. The results elucidate how individual design factors influence surface deformation and, consequently, pressure distribution. A novel speckle imaging technique is employed to address the complex non-linear deformations, enabling surface displacement measurements with an accuracy of approximately 40 µm. These measurements confirm that the Ogden N3 model can predict actuator deformation with an accuracy of 16%. These findings elucidate the relationships among actuator geometry, material behaviour, and surface deformation. Although demonstrated in a dynamically reconfigurable socket for transtibial amputees, these insights are readily transferable to other robotics applications that require soft, deformable, load-bearing interfaces. This validated modelling strategy and imaging technique provide a foundation for optimising soft actuator arrays, ultimately improving user comfort and enhancing the functionality of future prosthetic and robotic devices.

Many transtibial amputees rate the fit between their residual limb and prosthetic socket as the most critical factor in satisfaction with using their prosthesis. This study aims to address the issue of prosthetic socket fit by reconfiguring the socket shape at the interface of the residual limb and socket. The proposed reconfigurable socket shifts pressure from sensitive areas and compensates for residual limb volume fluctuations, the most important factors in determining a good socket fit. Computed tomography scan images are employed to create the phantom limb of an amputee and to manufacture the reconfigurable socket. The performance of the reconfigurable socket was evaluated both experimentally and numerically using finite element modelling. The study showed that the reconfigurable socket can reduce interface pressure at targeted areas by up to 61%.

The fit of a prosthetic socket is a critical factor in designing a comfortable socket. The socket fits depend primarily on residual limb volume fluctuation and pressure distribution over the residual limb. Using soft actuator arrays is a recent method to improve the socket fit by compensating for the residual limb volume fluctuation and controlling pressure distribution over the residual limb. However, there is currently no study to investigate the design of an inexpensive soft actuator array and measure the surface deformation field of the soft actuator array when it comes in contact with the residual limb.In this study, we propose a multi-layer soft actuator array to be embedded into the prosthetic socket. We used a new sub-pixel image registration algorithm to measure the soft actuator array surface deformation with 50 μm accuracy. We measured 90 different soft actuator array surface deformations by changing the actuator input pressures and actuating different actuator layers of soft actuator arrays.Our study demonstrated that soft actuator arrays can control the pressure distribution over the residual limb, and the input pressure to the actuators can be used to compensate for residual limb volume fluctuations.

In this paper we propose a new optical-based technique to identify the constitutive relation coefficients of the hyperelastic material using a hybrid optimisation approach. This technique can be used in place of traditional mechanical testing of elastomers for applications that involve inhomogeneous deformation. The purpose of the proposed method is to identify the incompressible hyperelastic material constitutive relation coefficients using a single experiment under different loading cases. The method comprises sample surface 3D reconstruction and uses finite element simulations to replicate the experiments, and uses a hybrid optimisation technique to minimise the error between actual 3D deformations and FE simulation results. The proposed hybrid technique predicts the hyperelastic constitutive relation coefficients more accurately than other optimisation methods. This study introduces a novel approach by employing a subpixel image registration algorithm for 3D reconstruction. The method requires a single experiment with diverse loading cases to accurately determine the coefficients of hyperelastic constitutive relations. The setup is portable and can be accommodated in a small suitcase. For this purpose, an apparatus was constructed comprising a stereoscopic system with eight cameras and a six-degree-of-freedom force-torque sensor to measure the induced forces and torques during the experiments. We identified the constitutive relation coefficients of Ogden N1, Ogden N3, Yeoh, and Arruda-Boyce relations which are commonly used models for silicone materials, using a traditional uniaxial test, optical uniaxial test (experiments performed using a constructed optical system), and inhomogeneous deformations tests. The study demonstrated that the coefficients obtained from inhomogeneous deformation tests provided the most accurate FE predictions. It was also shown that hyperelastic constitutive relation coefficients obtained from traditional uniaxial tests are insufficient to describe the material behaviour when the material undergoes inhomogeneous deformations.

RATIONALE:Colonic high-resolution manometry (cHRM) is an emerging clinical tool for defining colonic function in health and disease. Current analysis methods are conducted manually, thus being inefficient and open to interpretation bias.OBJECTIVE:The main objective of the study was to build an automated system to identify propagating contractions and compare the performance to manual marking analysis.METHODS:cHRM recordings were performed on 5 healthy subjects, 3 subjects with diarrhea-predominant irritable bowel syndrome, and 3 subjects with slow transit constipation. Two experts manually identified propagating contractions, from five randomly selected 10-min segments from each of the 11 subjects (72 channels per dataset, total duration 550 min). An automated signal processing and detection platform was developed to compare its effectiveness to manually identified propagating contractions. In the algorithm, individual pressure events over a threshold were identified and were then grouped into a propagating contraction. The detection platform allowed user-selectable thresholds, and a range of pressure thresholds was evaluated (2 to 20 mmHg).KEY RESULTS:The automated system was found to be reliable and accurate for analyzing cHRM with a threshold of 15 mmHg, resulting in a positive predictive value of 75%. For 5-h cHRM recordings, the automated method takes 22 ± 2 s for analysis, while manual identification would take many hours.CONCLUSIONS:An automated framework was developed to filter, detect, quantify, and visualize propagating contractions in cHRM recordings in an efficient manner that is reliable and consistent.

A common scenario found in experimentation is to synchronize events, such as breaks between visual stimulus, with the video record taken of an experiment made of participants as they undertake the task. In our case, we recently synchronized a protocol of stimulus presentations shown on a laptop display, with webcam video made of participants’ (who were two year old children) facial and eye movements as they were shown trials of stimulus containing moving dots (a random dot kinematogram or RDK). The purpose was to assess eye movements in response to these RDK stimulus as a part of a potential neurological assessment for children. The video contained audio signals such as “beeps” and musical interludes that indicated the start and end of trials, thereby providing a convenient opportunity to align these audio events with the timing of known events in the video record. The process of alignment can be performed manually, but this is a tedious and time consuming task when considering, for example, large databases of videos. In this paper, we tested two alternate methods for synchronizing known audio events using: 1) a deep learning based model, and a 2) standard template matching algorithm. These methods were used to synchronize the known protocol of stimulus events in videos by processing the audio contents of the recording. The deep learning approach utilized simple mel-spectrum audio signal feature extraction, whilst we adopted a cross-correlation algorithm that detected an audio template in the time domain. We found that whilst correlation was not effective as a means of beep detection; but our machine learning-based technique was robust with 90% accuracy in the testing dataset and did not the same amount of remediation required of the correlation approach.

Buckling and post-buckling behaviors of geometrically imperfect annular sector plates made from nanoparticle reinforced composites have been investigated. Two types of nanoparticles are considered including graphene oxide powders (GOPs) and silicone oxide (SiO2). Nanoparticles are considered to have uniform and functionally graded distributions within the matrix and the material properties are derived using Halpin-Tsai procedure. Annular sector plate is formulated based upon thin shell theory considering geometric nonlinearity and imperfectness. After solving the governing equations via Galerkin\'s technique, it is showed that the post-buckling curves of annular sector plates rely on the geometric imperfection, nanoparticle type, amount of nanoparticles, sector inner/outer radius and sector open angle.

The present paper deals with analyzing nonlinear forced vibrational behaviors of nonlocal multi-phase piezo-magnetic beam rested on elastic substrate and subjected to an excitation of elliptic type. The applied elliptic force may be presented as a Fourier series expansion of Jacobi elliptic functions. The considered multi-phase smart material is based on a composition of piezoelectric and magnetic constituents with desirable percentages. Additionally, the equilibrium equations of nanobeam with piezo-magnetic properties are derived utilizing Hamilton's principle and von-Karman geometric nonlinearity. Then, an exact solution based on Jacobi elliptic functions has been provided to obtain nonlinear vibrational frequencies. It is found that nonlinear vibrational behaviors of the nanobeam are dependent on the magnitudes of induced electrical voltages, magnetic field intensity, elliptic modulus, force magnitude and elastic substrate parameters.