Design of an Automatically Controlled Multi-Axis Stretching Device for Mechanical Evaluations of the Anterior Eye Segment.

The young eye has an accommodative ability involving lens shape changes to focus over different distances. This function gradually decreases with age, resulting in presbyopia. Greater insights into the mechanical properties of anterior eye structures can improve understanding of the causes of presbyopia. The present study aims to develop a multi-axis stretching device for evaluating the mechanical properties of the intact eye lens. A stretching device integrating the mechanical stretcher, motor, torque sensor and data transmission mechanism was designed and developed by 3D printing. The mechanical stretcher can convert rotation into radial movement, both at constant speeds, according to the spiral of Archimedes. The loading unit equipped with eight jaws can hold the eye sample tightly. The developed device was validated with a spring of known constant and was further tested with anterior porcine eye segments. The validation experiment using the spring resulted in stiffness values close to the theoretical spring constant. Findings from measurements with porcine eye samples indicated that the measured forces are within the ranges reported in the literature. The developed multi-axis stretching device has good repeatability during experiments with similar settings and can be reliably used for mechanical evaluations of the intact eye lens.

Effects of cane use on the kinematic and kinetic of lower-extremity joints in inexperienced users.

The cane is commonly prescribed for the elderly to maintain balance and enhance independent mobility. However, improper use of cane can increase the risk of falling. Understanding the characteristics of cane gait is critical for better establishing proper cane usage norms. The paper aimed to investigate effects of cane use on kinematics and kinetics of lower extremities in the elderly and the young to guide the development of adaptive cane gait. Twenty participants (10 elder and 10 young) were recruited and walked at a self-comfortable speed or with a cane in a two-point gait. The spatiotemporal gait parameters, hip/knee/ankle joint angles and ground reaction force (GRF) were statistically analyzed using MANOVAs to assess the effects of age and cane. Using the cane significantly decreased step length, cadence and speed and increased step time in both age groups. Age and cane had significant effects on ankle plantarflexion angle in initial swing phase (APA-ISw). In cane gait, the peaks of vertical GRF(V-GRF) and anterior-posterior GRF (AP-GRF) in bilateral lower extremities significantly decreased, and the troughs of right V-GRF significantly increased for both groups. These results suggest that using a cane does interfere with the natural gait of the user and insufficient ankle plantarflexion in initial swing phase (ISw) and reduced AP-GRF may be two key risk factors contributing to cane gait instability. Therefore, the users should consider actively increasing ankle plantarflexion in ISw to avoid deteriorating gait performance due to over-reliance on the cane.

Micromechanics Modeling of Transverse Tensile Strength for Unidirectional CFRP Composite.

Transverse tensile strength of unidirectional (UD) composites plays a key role in overall failure of fiber-reinforced composites. To predict this strength by micromechanics, calculation of actual stress in constituent matrix is essentially required. However, traditional micromechanics models can only give the volume-averaged homogenized stress rather than an actual one for a matrix, which in practice will cause large errors. In this paper, considering the effect of stress concentration on a matrix, a novel micromechanics method was proposed to give an accurate calculation of the actual stress in the matrix for UD composite under transverse tension. A stress concentration factor for a matrix in transverse tensile direction is defined, using line-averaged pointwise stress (obtained from concentric cylinder assemblage model) divided by the homogenized quantity (obtained from a bridging model). The actual stress in matrix is then determined using applied external stress multiplied by the factor. Experimental validation on six UD carbon fiber-reinforced polymer (CFRP) specimens indicates that the predicted transverse tensile strength by the proposed method presents a minor deviation with an averaged relative error of 5.45% and thus is reasonable, contrary to the traditional method with an averaged relative error of 207.27%. Furthermore, the morphology of fracture section of the specimens was studied by scanning electron microscopy (SEM). It was observed that different scaled cracks appeared within the matrix, indicating that failure of a UD composite under transverse tension is mainly governed by matrix failure. Based on the proposed approach, the transverse tensile strength of a UD composite can be accurately predicted.

Comparative analysis of popular predictors for difficult laryngoscopy using hybrid intelligent detection methods.

Difficult laryngoscopy is associated with airway injury, and asphyxia. There are no guidelines or gold standards for detecting difficult laryngoscopy. There are many opinions on which predictors to use to detect difficult laryngoscopy exposure, and no comprehensively unified comparative analysis has been conducted. The efficacy and accuracy of deep learning (DL)-based models and machine learning (ML)-based models for predicting difficult laryngoscopy need to be evaluated and compared, under the circumstance that the flourishing of deep neural networks (DNN) has increasingly left ML less concentrated and uncreative. For the first time, the performance of difficult laryngoscopy prediction for a dataset of 671 patients, under single index and integrated multiple indicators was consistently verified under seven ML-based models and four DL-based approaches. The top dog was a simple traditional machine learning model, Naïve Bayes, outperforming DL-based models, the best test accuracy is 86.6%, the F1 score is 0.908, and the average precision score is 0.837. Three radiological variables of difficult laryngoscopy were all valuable separately and combinedly and the ranking was presented. There is no significant difference in performance among the three radiological indicators individually (83.06% vs. 83.20% vs. 83.33%) and comprehensively (83.74%), suggesting that anesthesiologists can flexibly choose appropriate measurement indicators according to the actual situation to predict difficult laryngoscopy. Adaptive spatial interaction was imposed to the model to boost the performance of difficult laryngoscopy prediction with preoperative cervical spine X-ray.

Intraocular Snake Integrated with the Steady-Hand Eye Robot for Assisted Retinal Microsurgery.

Due to the confined intraocular space and physical constraints in tool manipulation, snake-like robots have a significant potential for use in retinal microsurgery. By enhancing the dexterity at the tool tip, not only the operable space on the retina can be enlarged, but also the delicate target tissues can be reached at an optimal angle minimizing the damage and making the operation much easier. In this study, we present an improved version of our earlier integrated intraocular snake (IRIS) robot, and combine it with another robotic assistant: the cooperatively controlled Steady-Hand Eye Robot (SHER). SHER is used to drive IRIS close to the retina with precision, while IRIS makes omnidirectional bends by combining its yaw and pitch motions and provides a significantly enhanced intraocular dexterity while holding the sclerotomy port fixed. For precise control of IRIS, its snake-like tip actuation has been characterized through experiments considering both a free tool tip and external loading at the tool tip. The workspace analysis showed ±45° yaw and pitch with excellent repeatability (±1°) despite the highly miniaturized articulated segment length (3 mm) and very thin shaft (Ø 0.9 mm). Our preliminary experiments in an artificial eye model have shown feasibility in reaching targets requiring bends up to 55° accurately.

3-DOF Force-Sensing Micro-Forceps for Robot-Assisted Membrane Peeling: Intrinsic Actuation Force Modeling.

Membrane peeling is a challenging procedure in retinal microsurgery, requiring careful manipulation of delicate tissues by using a micro-forceps and exerting very fine forces that are mostly imperceptible to the surgeon. Previously, we developed a micro-forceps with three integrated fiber Bragg grating (FBG) sensors to sense the lateral forces at the instrument's tip. However, importantly this architecture was insufficient to sense the tissue pulling forces along the forceps axis, which may be significant during membrane peeling. Our previous 3-DOF force sensing solutions developed for pick tools are not appropriate for forceps tools due to the motion and intrinsic forces that develop while opening/closing the forceps jaws. This paper presents a new design that adds another FBG attached to the forceps jaws to measure the axial loads. This involves not only the external tool-to-tissue interactions that we need to measure, but also the adverse effect of intrinsic actuation forces that arise due to the elastic deformation of jaws and friction. In this study, through experiments and finite element analyses, we model the intrinsic actuation force. We investigate the effect of the coefficient of friction and material type (stainless steel, titanium, nitinol) on this model. Then, the obtained model is used to separate the axial tool-to-tissue forces from the raw sensor measurements. Preliminary experiments and simulation results indicate that the developed linear model based on the actuation displacement is feasible to accurately predict the axial forces at the tool tip.