In the last decade, twisted coiled actuators (TCAs) made from nylon have drawn the attention of the community as an attractive electroactive mechanism mimicking the performance of human muscles, with notably favourable output power densities. The feasibility of the TCA, in terms of performance, size, safety, and scalability has been evaluated in previous studies, but they exhibit substantially non-linear behaviour, thereby requiring a sophisticated control system. Furthermore, it is desired that these actuators are able to rapidly actuate to match biological muscle levels of capability. To this end, the efficacy of a linear physics-based model of TCAs was tested to elucidate the relationship between temperature, force, and displacement in these actuators. The accuracy of this modelling approach is discussed in the context of position control theory using a two-degree- of-freedom proportional-integral-derivative (PID) controller to switch between Joule heating and active cooling with a continuously controlled fan to enhance actuator response time. This model was subsequently employed to simulate the TCA response to heating and cooling in the MATLAB-Simulink® environment while referencing the experimental results reported by Takagi et al. as a benchmark. Results from this investigation indicate a 5% offset error, which is attributed to the non-linear nature of the TCA. Finally, results confirm that TCAs augmented with active cooling exhibit significantly improved cycle times relative to conventionally heat-controlled TCAs.
The growing demand for wearable sensors has led to advancements in sports rehabilitation, robotic exoskeletons, etextiles, and human-machine interfaces, among other fields. In particular, stretchable tactile sensors for human motion tracking have become essential to the shift of healthcare activities towards more personalized, data-centric frameworks. In this paper, the fabrication, characterization, and deployment of an elastomeric capacitive strain sensor for tracking the Neck Motion Complex (NMC) is presented for physiotherapy applications. The sensor patch consists of a flexible and biocompatible dielectric PDMS film coated on either face with patterned graphene electrodes and encased in protective layers for stick-to-skin applications. The sensor transduces the strain from planar neck bending into a capacitive change between the electrode layers that is quantified and calibrated against the angle of bend. The sensor patch is worn on the side of the neck over the sternocleidomastoid muscle to capture lateral bending motions in our tests. We also present a simple and scalable fabrication method using easily available and lowcost materials and tools. Furthermore, a miniaturized built-for-purpose capacitance data acquisition system with an onboard memory card was designed and tested. The complete system is fully wearable, autonomous, and non-intrusive. Calibration of the sensor versus strain and neck bend was achieved using a high precision tensile tester and Aurora EMI system respectively. Characterization of the electrode performance under strain was also conducted. It is hoped that further iterations of the sensor design will quantify range of motion (ROM) and multi-plane neck motions.
KEYWORDS: 3D visualizations, Surgery, Visualization, Tissues, Haptic technology, 3D modeling, 3D vision, Robotics, 3D metrology, Visual process modeling
Objectives: The purpose of this study was to determine the effect of three-dimensional (3D) versus two-dimensional
(2D) visualization on the amount of force applied to mitral valve tissue during robotics-assisted mitral valve
annuloplasty, and the time to perform the procedure in an ex vivo animal model. In addition, we examined whether these
effects are consistent between novices and experts in robotics-assisted cardiac surgery.
Methods: A cardiac surgery test-bed was constructed to measure forces applied by the da Vinci surgical system
(Intuitive Surgical, Sunnyvale, CA) during mitral valve annuloplasty. Both experts and novices completed roboticsassisted
mitral valve annuloplasty with 2D and 3D visualization.
Results: The mean time for both experts and novices to suture the mitral valve annulus and to tie sutures using 3D
visualization was significantly less than that required to suture the mitral valve annulus and to tie sutures using 2D vision
(p∠0.01). However, there was no significant difference in the maximum force applied by novices to the mitral valve
during suturing (p = 0.3) and suture tying (p = 0.6) using either 2D or 3D visualization.
Conclusion: This finding suggests that 3D visualization does not fully compensate for the absence of haptic feedback in
robotics-assisted cardiac surgery.
Keywords: Robotics-assisted surgery, visualization, cardiac surgery
Trans-esophageal echocardiography (TEE) is a standard component of patient monitoring during most cardiac
surgeries. In recent years magnetic tracking systems (MTS) have become sufficiently robust to function effectively
in appropriately structured operating room environments. The ability to track a conventional multiplanar 2D
TEE transducer in 3D space offers incredible potential by greatly expanding the cumulative field of view of cardiac
anatomy beyond the limited field of view provided by 2D and 3D TEE technology. However, there is currently
no TEE probe manufactured with MTS technology embedded in the transducer, which means sensors must be
attached to the outer surface of the TEE. This leads to potential safety issues for patients, as well as potential
damage to the sensor during procedures. This paper presents a standard 2D TEE probe fully integrated with
MTS technology. The system is evaluated in an environment free of magnetic and electromagnetic disturbances,
as well as a clinical operating room in the presence of a da Vinci robotic system. Our first integrated TEE
device is currently being used in animal studies for virtual reality-enhanced ultrasound guidance of intracardiac
surgeries, while the "second generation" TEE is in use in a clinical operating room as part of a project to
measure perioperative heart shift and optimal port placement for robotic cardiac surgery. We demonstrate
excellent system accuracy for both applications.
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