Phuoc Thien Phan, Trung Thien Hoang, Mai Thanh Thai, Harrison Low · 7 authors
Wound closure with surgical sutures is a critical challenge for flexible endoscopic surgeries. Substantial efforts have been introduced to develop functional and smart surgical sutures to either monitor wound conditions or ease the complexity of knot tying. Although research interests in smart sutures by soft robotic technologies have emerged for years, it is challenging to develop a soft robotic structure that possesses a similar physical structure as conventional sutures while offering a self-tightening knot or anchor to close the wound. This paper introduces a new concept of smart sutures that can be programmed to achieve desired and uniform tension distribution while offering self-tightening knots or automatically deploying secured anchors. The core technology is a soft hydraulic artificial muscle that can be elongated and contracted under applied fluid pressure. Each suture is equipped with a pressure locking mechanism to hold its temporary elongated state and to induce self-shrinking ability. The puncturing and holding force for the smart sutures with anchors are examined. Ex-vivo experiments on fresh porcine stomach and colon demonstrate the usefulness of the new smart sutures. The new approaches are expected to pave the way for the further development of smart sutures that will benefit research, training, and commercialization in the surgical field.
Fiber-reinforced soft actuators use inextensible fibers to shape the expansion of elastomeric fluid-filled chambers. The classic example, McKibben muscles, is part of a broader class of cylindrical soft actuators known as fiber-reinforced elastomeric enclosures (FREEs). These actuators can be designed to twist while extending or contracting. Using a circuit of conductive, electrically insulated wire as the reinforcing fibers allows one to measure the motion of the actuator with the circuit inductance. These sensors, developed previously for McKibben muscles, are known as “Smart Braids.” This paper extends the concept of Smart Braids to the broader class of two-fiber-family cylindrical FREEs. A dimensionless model for the inductance of Smart Braid FREEs is presented that can be scaled to specific sensor geometries. This model depends only on the ratio of the fiber lengths in the two families and the angle of one of the fibers. The model was validated both numerically and experimentally, predicting the sensitivity of experimental sensors accurately, the largest errors being -11% and 9%. The model presented in this paper will enable high-level design decisions for Smart Braid FREES and optimization without computationally expensive direct numerical simulation.
Looping of the colonoscope shaft is the most common problem associated with a colonoscopy procedure. One study has shown that looping occurred in 91 out of 100 cases [1]. Looping can have a variety of effects ranging from extended procedure times, incomplete examinations, or even perforation of the colon wall [2]. Another study shows that 37 perforations occurred in 116,000 patients [3]. Looping increases discomfort for the patient, requiring larger amounts of anesthesia, and increasing operation time. Looping forces the doctor to reposition the colonoscope by twisting and retracting the shaft with varying degrees of success. This additional maneuvering of the colonoscope shaft during the procedure places extra stress on the inner lining of the colon wall.The problem of looping can be lessened with the help of manipulation by the doctor. By applying pressure to the abdomen and rotating the patient on his/her left or right side, looping can be reduced [4]. Some examples of existing equipment that is currently used to help combat this problem include: a double balloon sheath around the distal tip, a shape locking overtube guide, a general overtube, or a variable stiffness colonoscope. These are devices that passively prevent looping from forming. A better way to try and solve this problem is to constantly monitor the shape of the colonoscope shaft to determine if and when a loop will form and prevent it from happening. Some of the devices that employ a similar method to this include: the computer assisted NeoGuide system, fluoroscopy, and magnetic endoscopic imaging. The first of these devices uses a computer controlled, articulated colonoscope such that each segment follows the exact same path as the segment preceding it. The latter two give the doctor a 3D image of the shaft. If these devices were less expensive, then they might be more widely used, but as it is they are very expensive.With this in mind, a proof of concept method for detecting the shape of the colonoscope shaft during the procedure is introduced. If the shape of the colonoscope shaft is known then looping can be detected and avoided more easily. It would be more beneficial to avoid a loop all together than to backtrack once it is already formed.A model was developed that consists of multiple sets of connected links to be placed along the middle of the colonoscope shaft. These links are free to rotate in two different directions to show the motion of the shaft in full. Each rotation joint is equipped with a 6 mm rotational potentiometer, an angular displacement sensor. The potentiometer is a variable resistor that increases its resistance linearly from zero to a peak value over a range of 240 deg. Every rotation joint has a potentiometer attached to it through a modified pin. Figure 1 shows a single link with potentiometer attached.This only shows a single link but the entire model has 20 links connected together to give an image of a much larger stretch of the colonoscope. The link system is designed to conform to the inside of the colonoscope shaft only increasing the stiffness marginally. The system setup is shown in Fig. 2.Figure 2 above shows the complete system diagram with all components and order of attachment. Once the model was finished it each sensor was wired together in series on the power and ground pins with a power supply. The sensor output pins were wired separately and returned to the end of the system to a data acquisition device to process the signals. The signals acquired are voltage readings from each potentiometer. Signal express was used to acquire the signal and save it as a file. The file was then inserted into a computer program in matlab, which graphed an image of the model.The linkage was formed into a straight line to show the baseline reading for the system. The second configuration was a small alpha loop with 3 cm radius. This was formed because the alpha loop is one of the most common types of loops found in the colonoscopy procedure. Both configurations are shown in Fig. 3.Once this was done, the voltage readings from the sensors were recorded into a file. This file was then inserted into a program that manipulates these values into corresponding angles based upon calibration charts. From the corresponding angles a graphical image was produced that closely resembles the original model. The matlab graphs are set to the same scale as the original model. The graphical images can be seen in Fig. 4. The straight line and alpha loop configuration both very accurately resemble the physical model with little error (Figs. 4(a) and 4(b)). This shows that the model can accurately predict complex shapes and configurations, with little error, that are commonly found inside the colon during a procedure.From the results presented above, it can be seen that the linkage model method with attached potentiometers can easily manage loops commonly found in the everyday procedure. This ability combined with the graphical imaging software can help a doctor to potentially see a loop as it is about to be formed. As has been previously said, the key to stopping loop formation is the prediction of loops before they form. With this model and software, loops can be accurately predicted and viewed during a procedure. With little to no training at all a doctor can look at the computer screen and be able to tell if the shaft of the colonoscope is approaching the tipping point between loop formation and following the colon wall around a curve such as in the sigmoid colon. This would be greatly helpful with decreasing the numbers of incomplete colonoscopies due to loop formation. Along with this, knowing the curvature of the shaft of the colonoscope and the basic knowledge of the shape of the colon, the doctor can give a more accurate description of locations of polyps discovered in the colon.Overall, this method of loop detection that has been discussed could serve as an additional tool to helping a doctor complete a colonoscopy procedure. This method could reduce procedure time due to loop formation as well as decrease pain to the patient. The doctor could also decrease the number of incomplete colonoscopies that result from looping of the colonoscope shaft.
Soft Robotics and Applications
Mathematics, Computing, and Information Processing