AI-driven automatic compression system for colorectal anastomosis.

Although circular staplers offer technical advancements over traditional hand-sewn techniques, their use remains challenging for unskilled users, necessitating substantial time and experience for mastery. In particular, it is challenging to apply a consistent pressure of an appropriate magnitude. We developed an automated circular anastomosis device using artificial intelligence (AI) to solve this problem. Automation through AI reduces experiential factors during the anastomosis process. We defined damage occurring during the anastomosis process, noting that a greater depth of damage indicated a more severe injury. For automated anastomosis, data at a tissue strain of 40% were used for the AI model, as this strain level showed optimal performance based on the accuracy and cost matrix. We compared the outcomes of automated anastomosis using a trained AI with those of unskilled users. The results were validated using the Shapiro-Wilk test and t tests. Compression damage was verified on collagen sheets. The AI-driven automatic compression system resulted in less damage compared to unskilled users. In particular, a more significant difference in damage was observed in poor-condition collagen than in good-condition collagen. Damage to the collagen under poor conditions was 54.8% when handled by unskilled users, while the AI-driven automatic compression system resulted in 38.9% damage. This study confirmed that novices' use of AI for automated anastomosis reduces the risk of damage, especially for tissues in poor condition.

Improved Frequency Sweep Keying CDMA Using Faster R-CNN for Extended Ultrasonic Crosstalk Reduction.

Ultrasonic sensors are inexpensive and provide highly accurate measurements, even with simple hardware configurations, facilitating their use in various fields. When multiple ultrasonic sensors exist in the measurement space, crosstalk occurs due to other nodes, which leads to incorrect measurements. Crosstalk includes not only receiving homogeneous signals from other nodes, but also overlapping by other signals and interference by heterogeneous signals. This paper proposes using frequency sweep keying modulation to provide robustness against overlap and a faster region-based convolutional neural network (R-CNN) demodulator to reduce the interference caused by heterogeneous signals. The demodulator works by training Faster R-CNN with the spectrograms of various received signals and classifying the received signals using Faster R-CNN. Experiments implementing an ultrasonic crosstalk environment showed that, compared to on-off keying (OOK), phase-shift keying (PSK), and frequency-shift keying (FSK), the proposed method can implement CDMA even with shorter codes and is robust against overlap. Compared to correlation-based frequency sweep keying, the time-of-flight error was reduced by approximately 75%. While the existing demodulators did not consider heterogeneous signals, the proposed method ignored approximately 99% of the OOK and PSK signals and approximately 79% of the FSK signals. The proposed method performed better than the existing methods and is expected to be used in various applications.

Edge Bleeding Artifact Reduction for Shape from Focus in Microscopic 3D Sensing.

Shape from focus enables microscopic 3D sensing by combining it with a microscope system. However, edge bleeding artifacts of estimated depth easily occur in this environment. Therefore, this study analyzed artifacts and proposed a method to reduce edge bleeding artifacts. As a result of the analysis, the artifact factors are the depth of field of the lens, object texture, brightness difference between layers, and the slope of the object. Additionally, to reduce artifacts, a weighted focus measure value method was proposed based on the asymmetry of local brightness in artifacts. The proposed reduction method was evaluated through simulation and implementation. Edge bleeding artifact reduction rates of up to 60% were shown in various focus measure operators. The proposed method can be used with postprocessing algorithms and reduces edge bleeding artifacts.

The Safe Values of Quantitative Perfusion Parameters of ICG Angiography Based on Tissue Oxygenation of Hyperspectral Imaging for Laparoscopic Colorectal Surgery: A Prospective Observational Study.

BACKGROUND: Safe values for quantitative perfusion parameters of indocyanine green (ICG) angiography have not been fully defined, and interpretation remains at the surgeon's discretion. This prospective observational study aimed to establish the safe values for the quantitative perfusion parameters by comparing tissue oxygenation levels from HSI images in laparoscopic colorectal surgery. METHODS: ICG angiography was performed using a laparoscopic near-infrared (NIR) camera system with ICG diluted in 10 mL of distilled water. For quantitative perfusion parameters, the changes in fluorescence intensity with perfusion times were analyzed to plot a time-fluorescence intensity graph. To assess real-time tissue oxygen saturation (StO2) in the colon, the TIVITA® Tissue System was utilized for hyperspectral imaging (HSI) acquisition. The StO2 levels were compared with the quantitative perfusion parameters derived from ICG angiography at corresponding points to define the safe range of ICG parameters reflecting good tissue oxygenation. RESULTS: In the regression analysis, T1/2MAX, TMAX, slope, and NIR perfusion index were correlated with tissue oxygen saturation. Using this regression model, the cutoff values of quantitative perfusion parameters were calculated as T1/2MAX ≤ 10 s, TMAX ≤ 30 s, slope ≥ 5, and NIR perfusion index ≥50, which best reflected colon StO2 higher than 60%. Diagnostic values were analyzed to predict colon StO2 of 60% or more, and the ICG perfusion parameters T1/2MAX, TMAX, and perfusion TR showed high sensitivity values of 97% or more, indicating their ability to correctly identify cases with acceptable StO2. CONCLUSION: The safe values for quantitative perfusion parameters derived from ICG angiography were T1/2MAX ≤ 10 s and TMAX ≤ 30 s, which were associated with colon tissue oxygenation levels higher than 60% in the laparoscopic colorectal surgery.

Capacitive coupling leading to electrical skin burn injury during laparoscopic surgery.

Purpose: Trocar-site burns occurring during laparoscopic surgery have been reported in various cases, and several efforts to reduce them are underway. This study aimed to analyze the effect of capacitive coupling on trocar site by observing electrical and histological changes for electrical skin burn injury. Methods: To measure the electrical changes relating to capacitive coupling, the temperature, current, voltage, and impedance around the trocar were measured when an open circuit and a closed circuit were formed using insulation intact instruments and repeated after insulation failure. After the experiment, the tissue around the trocar was collected, and microscopic examination was performed. Results: When open circuits were formed with the intact insulation, the impedance was significantly reduced compared to the cases of closed circuits (142.0 Ω vs. 109.3 Ω, p = 0.040). When the power was 30 W and there was insulation failure, no significant difference was measured between the open circuit and the closed circuit (147.7 Ω vs. 130.7 Ω, p = 0.103). Collagen hyalinization, nuclear fragmentation, and coagulation necrosis suggesting burns were observed in the skin biopsy at the trocar insertion site. Conclusion: This study demonstrated that even with a plastic trocar and electrosurgical instruments that have intact insulation, if an open circuit is formed, capacitive coupling increases, and trocar-site burn can occur. When using electrocautery, careful manipulation must be taken to avoid creating an open circuit to prevent capacitive coupling related to electrical skin burn.

Frequency Sweep Keying CDMA for Reducing Ultrasonic Crosstalk.

Various sensors are embedded in automobiles to implement intelligent safety technologies such as autonomous driving and front-rear collision avoidance technology. In particular, ultrasonic sensors have been used in the past because they have an accuracy of centimeters to sub-centimeters in air despite their low cost and low hardware complexity. Recently, the crosstalk problem between ultrasonic sensors has been raised because the number of ultrasonic sensors in the unit space has increased as the number of vehicles increases. Various studies have been conducted to solve the crosstalk, but a demodulation error occurs when signals overlap. Therefore, in this paper, we propose a method that is robust to ultrasonic signal overlap, is robust even at shorter code length, and has reduced time of flight (TOF) error compared to the existing method by applying frequency sweep keying modulation based on code division multiple access (CDMA). As a result of the experiment, the code was detected accurately regardless of the overlap ratio of the two signals, and it was robust even in situations where the power of the two signals was different. In addition, it shows an accurate TOF estimation even if the ID code length is shorter than the existing on-off-keying, frequency shift keying, and phase shift keying methods.

Compression automation of circular stapler for preventing compression injury on gastrointestinal anastomosis.

BACKGROUND: Conventional manual compression relies on the surgeon's subjective sensations, so excessive compression can cause tissue injury to the stapling line of the intestinal anastomosis. METHODS: Automatic compression monitoring and compression control system was developed for circular stapler. The tissue injury related compression variables were evaluated and accommodated by compression control device. The compression injury-reducing performance was verified on collagen sheets of in vitro experiments. RESULTS: Excessive pressure and tissue deformation were associated with compression-induced tissue damages. The safe pressure range was very narrow in weaker tissue than normal collagen. The automatic system performed proper compression within a safe pressure range without tissue injury. CONCLUSIONS: Manual compression of circular stapler could cause tissue injuries by excessive pressure and tissue deformation. Our automatic compression system is designed to control peak pressure to prevent the compressive tissue injury.

Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor.

Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters can be used to determine asymmetric walking. The spatiotemporal parameter has the disadvantage that it does not consider the influence of the diversity of patterns and the walking speed. Therefore, in this paper, we propose a method to analyze asymmetric walking using Dynamic Time Warping (DTW) distance, a time series analysis method. The DTW distance was obtained by combining gyroscope data and pressure data. The experiment was carried out by performing symmetrical walking and asymmetrical walking, and asymmetric walking was performed as a simulation of hemiplegic walking by fixing one ankle using an auxiliary device. The proposed method was compared with the existing asymmetric gait analysis method. As a result of the experiment, a p-value lower than 0.05 was obtained, which proved that there was a statistically significant difference.

Optimization of indocyanine green angiography for colon perfusion during laparoscopic colorectal surgery.

AIM: This study aims to evaluate the extrinsic effects of conditional factors affecting quantitative parameters and to establish the optimization of indocyanine green (ICG) angiography using in vitro experiments and a prospective observational study. METHOD: In vitro experiments were performed to evaluate the correlation between conditional factors such as camera distance, surrounding lighting, fluorescence emission sources and ICG doses. The fluorescence intensity was measured from the ICG-containing test tube in each condition. In the clinical study, ICG angiography was applied to patients with colorectal cancer (n = 164). The quantitative perfusion parameters were the maximal fluorescence intensity (FMAX ), slope, T1/2MAX and perfusion time ratio (TR). Camera position, distance to colon, fluorescence emission source, surrounding lighting, site of angiography and ICG specific mode were considered as conditional factors and compared with the quantitative parameters to identify the optimal condition of ICG angiography. RESULTS: The fluorescence intensity had an inverse correlation with distance, and the transitional zone was shown at a distance of 4-5 cm by slope differential. FMAX , T1/2MAX and slope were affected significantly by camera distance, site of angiography, fluorescence emission source and ICG mode as conditional factors. On multivariate analysis, FMAX was independently associated with spectral ICG mode with red inversion, laser mode and camera distance. Conversely, TR was not related to any conditional factors. CONCLUSION: Since quantitative parameters of ICG angiography are influenced by various conditions, a standardized protocol is required. The application of ICG specific modes with a constant distance of 4-5 cm can provide optimized fluorescence images.

Clinical effect and standardization of indocyanine green angiography in the laparoscopic colorectal surgery.

Anastomotic complications occur after 5% to 20% of operations for rectosigmoid colon cancer. The intestinal perfusion status at the anastomotic site is an important modifiable risk factor, and surgeons should carefully evaluate and optimize the perfusion at the intended site of anastomosis. Indocyanine green (ICG) angiography is a simple noninvasive perfusion assessment modality. The use of ICG angiography is rapidly spreading in the field of colorectal surgery. However, there is debate on its contribution to reducing anastomotic complications. In this review, we discuss the clinical utility and the standardization of ICG angiography. ICG angiography can unequivocally reveal unfavorable perfusion zones and provide quantitative parameters to predict the risk of hypoperfusion-related anastomotic complications. Many studies have demonstrated the clinical utility of ICG angiography for reducing anastomotic complications. Recently, two multicenter randomized clinical trials reported that ICG angiography did not significantly reduce the incidence of anastomotic leakage. Most previous studies have been small-scale single-center studies, and there is no standardized ICG angiography protocol to date. Additionally, ICG angiography evaluations have mostly relied on surgeons' subjective judgment. For these reasons, it is necessary to establish a standardized ICG angiography protocol and develop a quantitative analysis protocol for the objective assessment. In conclusion, ICG angiography could be useful for detecting poorly perfused colorectal segments to prevent anastomotic leakage after colorectal surgery. An optimized and standardized ICG angiography protocol should be established to improve the reliability of perfusion assessments. In the future, artificial intelligence-based quantitative analyses could be used to easily assess colonic perfusion status.

Artificial intelligence based real-time microcirculation analysis system for laparoscopic colorectal surgery.

BACKGROUND: Colonic perfusion status can be assessed easily by indocyanine green (ICG) angiography to predict ischemia related anastomotic complications during laparoscopic colorectal surgery. Recently, various parameter-based perfusion analysis have been studied for quantitative evaluation, but the analysis results differ depending on the use of quantitative parameters due to differences in vascular anatomical structure. Therefore, it can help improve the accuracy and consistency by artificial intelligence (AI) based real-time analysis microperfusion (AIRAM). AIM: To evaluate the feasibility of AIRAM to predict the risk of anastomotic complication in the patient with laparoscopic colorectal cancer surgery. METHODS: The ICG curve was extracted from the region of interest (ROI) set in the ICG fluorescence video of the laparoscopic colorectal surgery. Pre-processing was performed to reduce AI performance degradation caused by external environment such as background, light source reflection, and camera shaking using MATLAB 2019 on an I7-8700k Intel central processing unit (CPU) PC. AI learning and evaluation were performed by dividing into a training patient group (n = 50) and a test patient group (n = 15). Training ICG curve data sets were classified and machine learned into 25 ICG curve patterns using a self-organizing map (SOM) network. The predictive reliability of anastomotic complications in a trained SOM network is verified using test set. RESULTS: AI-based risk and the conventional quantitative parameters including T 1/2max , time ratio (TR), and rising slope (RS) were consistent when colonic perfusion was favorable as steep increasing ICG curve pattern. When the ICG graph pattern showed stepped rise, the accuracy of conventional quantitative parameters decreased, but the AI-based classification maintained accuracy consistently. The receiver operating characteristic curves for conventional parameters and AI-based classification were comparable for predicting the anastomotic complication risks. Statistical performance verifications were improved in the AI-based analysis. AI analysis was evaluated as the most accurate parameter to predict the risk of anastomotic complications. The F1 score of the AI-based method increased by 31% for T 1/2max , 8% for TR, and 8% for RS. The processing time of AIRAM was measured as 48.03 s, which was suitable for real-time processing. CONCLUSION: In conclusion, AI-based real-time microcirculation analysis had more accurate and consistent performance than the conventional parameter-based method.

Indoor Positioning System Using Magnetic Field Map Navigation and an Encoder System.

In the indoor environment, variation of the magnetic field is caused by building structures, and magnetic field map navigation is based on this feature. In order to estimate position using this navigation, a three-axis magnetic field must be measured at every point to build a magnetic field map. After the magnetic field map is obtained, the position of the mobile robot can be estimated with a likelihood function whereby the measured magnetic field data and the magnetic field map are used. However, if only magnetic field map navigation is used, the estimated position can have large errors. In order to improve performance, we propose a particle filter system that integrates magnetic field map navigation and an encoder system. In this paper, multiple magnetic sensors and three magnetic field maps (a horizontal intensity map, a vertical intensity map, and a direction information map) are used to update the weights of particles. As a result, the proposed system estimates the position and orientation of a mobile robot more accurately than previous systems. Also, when the number of magnetic sensors increases, this paper shows that system performance improves. Finally, experiment results are shown from the proposed system that was implemented and evaluated.