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[Purpose] We compared and analyzed energy consumption and excess post-exercise oxygen consumption (EPOC) following Taekwondo Taegeuk Poomsae performances.[Methods] Forty-two healthy men who could perform Taegeuk Poomsae 1–8 Jangs were enrolled in this study. To reduce the impact of Poomsae, a random cross-design was used. The washout time was set to at least three days. Oxygen consumption (VO2) was monitored after performing each Poomsae until a reference line was resumed. Each Taegeuk Poomsae was performed at a speed of 60 bpm.[Results] There was no significant difference in VO2, carbon dioxide excretion, and heart rate after performing the Taegeuk Poomsae once; however, all variables increased significantly in combined results of EPOC metabolism (Fp2p2

Measuring functional fitness (FF) to track the decline in physical abilities is important in order to maintain a healthy life in old age. This paper aims to develop an estimation model of FF variables, which represents strength, flexibility, and aerobic endurance, using easy-to-measure physical parameters for Korean older adults aged over 65 years old. The estimation models were developed using various machine learning techniques and were trained with the National Fitness Award datasets from 2015 to 2019 compiled by the Korea Sports Promotion Foundation. The machine-learning-based nonlinear regression models were employed to improve the performance of the previous linear regression models. To derive the optimal estimation model that showed the best estimation accuracy, we developed five different machine-learning-based estimation models and compares the estimation accuracy not only among the machine learning models, but also with the previous linear regression model. The coefficient of determination of the FF variables was used to compare the performance of each model; the mean absolute percentage error (MAPE) and standard error of estimation (SEE) were used to evaluate the model performance. The deep neural network (DNN) model presented the best performance among the regression models for the estimation of all of the FF variables. The coefficient of determination in the HGS test was 0.784, while those of the others were less than 0.5 meaning that the HGS of older adults can be reliably estimated using easy-to-measure independent variables.

Intense heat from fire can result in significant damage to firefighting robots. To avoid this damage, numerous studies have been conducted on the thermal insulation of firefighting robots using electrical motors and sensors that can not withstand high temperatures. In this paper, we present an attachable skin for enhancing the thermal resistance of firefighting robots using polydimethylsiloxane (PDMS), where a wet chemical extinguishing agent is injected into the holes on PDMS. The pilot experiment was conducted to verify the thermal insulation performance of a wet chemical extinguishing agent compared to water. Several experiments were also carried out with different diameters, depths, shapes, and degrees of PDMS holes to determine optimum hole dimensions. The results demonstrated that the thermal resistance of PDMS skin is related to the capacity of the wet chemical extinguishing agent. In addition, the performance of the PDMS skin can be verified by its variation according to the ignition time.

Estimation of health-related physical fitness (HRPF) levels of individuals is indispensable for providing personalized training programs in smart fitness services. In this study, we propose an artificial neural network (ANN)-based estimation model to predict HRPF levels of the general public using simple affordable physical information. The model is designed to use seven inputs of personal physical information, including age, gender, height, weight, percent body fat, waist circumference, and body mass index (BMI), to estimate levels of muscle strength, flexibility, maximum rate of oxygen consumption (VO2max), and muscular endurance. HRPF data (197,719 sets) gathered from the National Fitness Award dataset are used for training (70%) and validation (30%) of the model. In-depth analysis of the model’s estimation accuracy is conducted to derive optimal estimation accuracy. This included input/output correlation, hidden layer structures, data standardization, and outlier removals. The performance of the model is evaluated by comparing the estimation accuracy with that of a multiple linear regression (MLR) model. The results demonstrate that the proposed model achieved up to 10.06% and 30.53% improvement in terms of R2 and SEE, respectively, compared to the MLR model and provides reliable estimation of HRPF levels acceptable to smart fitness applications.

Wearable exoskeletons have generally been designed to enhance user strength or to reduce user fatigue. Two areas that have often been overlooked are that exoskeletons should increase user safety and have increased durability for use in extreme environments. In this paper, we developed an SMA spring-based shock absorption module for an exoskeleton or a quadruped walking robot, which can provide increased protection to the user during high-impact events in an extreme environment. We analyzed the impact force during the collision between the module and the ground based on impulse and momentum theories. The shock absorber module can be reused by exploiting the inherent shape memory characteristics of the SMA spring after every use. We confirmed that the spring constant of the SMA spring and the maximum allowable length affect the impulse reduction, and the results showed that the latter has a greater influence on impulse reduction.

In this paper, we present a comprehensive review of the latest autonomous navigation technologies for unmanned ships. Maritime trade has increased enormously along with the evolution of industrial economies over the last century. The unmanned ship has received worldwide attention as a next-generation transportation vessel. It can change the paradigm of global maritime trade. In this paper, first, we present the global trend of unmanned ship development by reviewing the major research project currently conducted by several research groups. One of them describes the three steps of an unmanned ship according to the level of autonomy. The core technologies of the unmanned ship are classified into three categories in terms of safety, efficiency, and connectivity. The state-of-the-art technologies and the remaining challenges in each category are reviewed comprehensively.

Cricothyrotomy procedures, involving risky incisions on the neck skin and internal membranes, require rigorous training. In this paper, a novel incision sensor measuring the incision path in a cricothyrotomy training simulation is proposed. The sensor provides quantitative feedback to trainees on their incision practice, enhancing the effectiveness of the simulation. The sensor measures the electric potential, which decreases monotonically along the direction of current flow on the conductive material at the incision point, and converts it to coordinate values, based on the relationship between the electric potential and the position. The sensor comprises three layers of conductive tape, which are electrically isolated by two dielectric layers, and is fabricated as a thin film. The first two conductive layers (driving layers) are alternately energized to create distributions of electric potential in the $x$ or $y$ directions across the sensor plane. The third conductive layer (sensing layer), placed under the driving layers, transfers the electric potential to the output channel of the sensor at the point where a metal blade creates a short circuit between the energized driving layer and the sensing layer. The alternating measurements are converted to $x$ and $y$ coordinates of the incision position. The experiments for characterization and performance validation were performed using sensor prototypes fabricated with the proposed design and fabrication procedures. The experimental results show that the proposed sensor facilitates the measurement of the incision paths aligned with and diagonal to the $x$ and $y$ axes within root mean square errors of 0.98 and 1.03 mm, respectively.

A haptic interface based on electrical muscle stimulation (EMS) has huge potential in terms of usability and applicability compared with conventional haptic interfaces. This study analyzed the force response characteristics of forearm extensor muscles for EMS-based haptic rendering. We introduced a simplified mathematical model of the force response, which has been developed in the field of rehabilitation, and experimentally validated its feasibility for haptic applications. Two important features of the force response, namely the peak force and response time, with respect to the frequency and amplitude of the electrical stimulation were identified by investigating the experimental force response of the forearm extensor muscles. An exponential function was proposed to estimate the peak force with respect to the frequency and amplitude, and it was verified by comparing with the measured peak force. The response time characteristics were also examined with respect to the frequency and amplitude. A frequency-dependent tendency, i.e., an increase in response time with increasing frequency, was observed, whereas there was no correlation with the amplitude. The analysis of the force response characteristics with the application of the proposed force response model may help enhance the fidelity of EMS-based haptic rendering.

Marine bioprospecting is the procedure of identifying the characteristics of marine organisms to develop them into commercial products. This paper proposes a 3D reconstruction algorithm to facilitate 3D visualization of underwater scene for the marine bioprospecting using remotely operated underwater vehicle (ROV). It allows to provide an operator with intuitive user interface and accordingly contribute to enhance the operability of the ROV in the bioprospecting operation. The reconstruction algorithm transforms 2D pixel coordinates of the sonar image into the corresponding 3D spatial coordinates of the scene surface by restoring the surface elevation missing in the sonar image. First, the algorithm segments the objects and shadows in the image by classifying the pixels based on the intensity value of the seafloor. Second, it computes the surface elevation on the object pixels based on their intensity values. Third, the elevation correction factor, which is derived by the ratio between height of the object and the length of the shadow, is multiplied to the surface elevation value. Finally, the 3D coordinates of the scene surfaces are reconstructed using the coordinate transformation from the image plane to the seafloor with the restored surface elevation values. The experimental results show the algorithm successfully reconstructs the surface of the reference object within an error range less than 10 % of the object dimension, and practical applicability to the marine bioprospecting operation.

최소 침습 수술(minimally invasive surgery, MIS)에서 수술 도구의 유연성과 조작 용이성은 매우 중요한 요소이다. 유연 수술 로봇은 유연한 동작이 가능하고 조작이 용이하여 기존 복강경 수술로봇 대비 향상된 수술결과를 기대할 수 있어 기존 수술로봇의 한계를 극복할 수 있는 진보된 수술로봇으로 주목을 받고 있다. 본 논문에서는 메소-스케일(meso-scale)의 최신 유연 수술 로봇을 소개하고, 유연 수술 로봇의 디자인 및 한계점을 분석하고자 한다. 연 조직(soft tissue)을 대상으로 개발된 다양한 최신의 유연수술 로봇들을 소개하고 유연 수술 로봇의 한계점을 극복하기 위한 영상 유도 기법, 관절의 강성 조절기법, 로봇의 재질 등에 대한 최신의 연구동향을 살펴본다. 현재 유연 수술 로봇의 기술적 한계점을 분석하고 향후 연구개발 방향을 제시한다.

High-precision register control is essential for manufacturing reliable micro-electronic devices using roll-to-roll (R2R) printing press. Thus far, many researches have reported on the structure of register controller and various control techniques, but printing defects in register marks have not been seriously considered even though it degrades the control performance by causing register measurement errors. This paper presents the statistical analysis on smearing defects according to printing conditions including ink viscosity, web speed, and doctor pressure. It analyzes the effects of the printing conditions on the mean and standard deviation of the smearing length using analysis of variance (ANOVA) and derives optimal printing conditions to minimize the smearing length using a Box-Behnken design. The effect of the optimization on the register measurement error was verified experimentally. The experimental results showed that the measurement and repeatability errors in the register measurement were improved by 73.3 and 42.3%, respectively, under the optimal conditions. This study suggests that the smearing defects could cause the register error and degrade the quality of printed layers, and the register error owing to the printing defects could be improved by changing parameters of printing press (e.g., web velocity and doctor pressure) as well as ink characteristics.

Recently, the need for a more efficient method for ship route planning was raised due to the financial crisis in the shipping industry, a strengthening of emission regulations, and the limitations of the existing methods. So far, numerous ship route planning methods have been developed, but most of them do not correctly reflect the effect of a change of the ship speed in the path-determination stage. For this study, a ship route planning problem was formulated as an optimization problem. To solve this, a method for a simultaneous determination of the path and the speed of a ship is proposed. To check the efficiency and the applicability of the proposed method, sensitivity analyses and a comparative test regarding some other methods was performed. The proposed method was applied to various examples of ship route planning and the results show that the proposed method can reduce the total fuel consumption compared with the other methods.

Muscle synergy is the association of several muscle groups contracting simultaneously as a single functional unit. Recently, the synergy has been emphasized in neurophysiological studies to utilize it as an evaluation index for stroke patients. In this paper, we proposed novel method for quantitatively comparing muscle synergy of normal people and the stroke patient for evaluating severity of the stroke. The proposed method uses NNR (Non-Negative Matrix Reconstruction) algorithm for reconstructing muscle weight matrix W. The proposed method synchronizes the time sequence of EMG data of the stroke patient with the normal people based on working phases. The method improves the distortion problem of NNR algorithm through the synchronization of time sequence.

Objective To evaluate a novel multi-channel functional electrical stimulation (FES) rehabilitation method based on the evaluation of patient-specific walking dysfunction. Methods This study investigated a novel multi-channel FES-based rehabilitation method that analysed the patient’s muscle synergy and walking posture. A patient-specific FES profile was produced in the pre-evaluation stage by comparing the muscle synergy and walking posture of the patient with those of healthy control subjects. During the rehabilitation phase, this profile was used to determine an appropriate FES pulse width and amplitude for stimulating the patient’s muscles as they walked across a flat surface. Results Two stroke patients with hemiplegic symptoms participated in a clinical evaluation of the proposed method involving a 4-week course of rehabilitation. An evaluation of the rehabilitation results based on a comparison of the pre- and post-rehabilitation muscle synergy and walking posture revealed that the rehabilitation enhanced the muscle synergy similarity between the patients and healthy control subjects and their quantitative walking performance, as measured by a 10-m walk test and walking speed, by up to 23.38% and 30.00%, respectively. Conclusion These results indicated that the proposed rehabilitation method improved walking ability by improving muscle coordination and adequately supporting weakened muscles in stroke patients.

The vehicular ad hoc network (VANET) has been identified as one of the most promising technologies for managing future intelligent transportation systems. This paper proposes a distributed transmission power adjustment algorithm for communication congestion control and awareness enhancement to address communication congestion problems that can arise in VANETs. The objective of the proposed algorithm is to provide maximum awareness of surrounding vehicles' status while maintaining a communications channel load below the allowed threshold. The proposed algorithm accomplishes this by adjusting the transmission range of each vehicle in the network progressively and gradually, while monitoring the communications channel load of each vehicle. By changing the transmission range of a vehicle little by little according to the communications channel load of its neighboring vehicles, the algorithm finds the optimal transmission range that provides maximum awareness without resulting in communications congestion. In addition, the proposed algorithm appropriately controls the channel load in a fair manner without sacrificing awareness of specific vehicles in the congested situation. This allows nearby vehicles to obtain more peripheral information to help them stay away from potential hazards and maintain safety. The proposed algorithm was implemented in a simulation environment, and its performance was validated in various traffic scenarios. The simulation results show that the proposed algorithm can deal with communication congestion by controlling the transmission power fairly to a target threshold in various traffic situations.

This paper focuses on the human perception capabilities for haptic interaction with remote environments. The perception capabilities are compared for two well-known control methods with two kinds of haptic cues. Analytical and psychophysical methods are used to analyze the performance. The first control method aims at maximizing the transparency of the remote interactions (i.e., transparency-based method ), whereas the second one aims at maximizing the detection and discrimination abilities of the human operator (i.e., perception-based method ). For each of these two control methods, two kinds of haptic cues are studied, which use position and force cues from remote environments. Hybrid matrix formulation is employed, and it is analyzed in the frequency domain for these studies. Psychophysical experiments are then conducted for human-centered evaluation and comparison of the control methods. Analytical and experimental results clearly show that the perception-based method, when compared with the transparency-based method, enhances the human operator's perceptual capabilities of remote environments irrespective of force cues. For each of the two control methods, the force cues always contribute more to the increase in perceptual sensitivity when compared with the case of position cues.

This paper proposes a novel method for a real-time cutting simulation of deformable objects using meshless method. The method utilizes a rapid refinement of topological relations among the simulation nodes of meshless deformable objects. Topological relations are defined as an undirected graph based on a visibility criterion. The graph connects the adjacent nodes that lie within a support of each node. The topological relations are refined by removing the edges of the graph that is intersected by the cut surface during the cutting simulation. Our approach utilizes a bounding volume hierarchy (BVH) to accelerate the computation of the intersection test. The BVH reconstruction algorithm is proposed to account for the cases where pieces of the object are completely cut out from the object. Algorithms to examine the connectivity among simulation nodes and accordingly reconstructing the BVH using two-level BVH are presented. The proposed approach achieves real-time cutting simulation of deformable objects through the rapid refinement of the topological relation. In addition, the computational performance of the cutting procedure is preserved during the entire simulation, thanks to the real-time reconstruction of the BVH. Copyright © 2012 John Wiley & Sons, Ltd.

Background Colonoscopy simulation has been increasingly applied as a method of training, which can supplement the traditional patient-based training in recent years. However, the current level of realism of the simulation is insufficient. One of the main difficulties degrading the realism is real-time simulation of colon deformation involving multi-contact interaction with the endoscope. Methods This paper proposes a novel simulation framework for real-time deformation of the colon and endoscope, using a skeleton-driven deformation method. Cylindrical lattices and a centre-line are employed as the skeletons, and a mass-spring model is applied to the skeletons for the mechanics-based simulation. The centre-line-based collision detection and resolution algorithm is proposed to simulate the interaction between the colon and endoscope. A haptic rendering algorithm using the energy method is proposed to produce feedback force, based on physical interaction between the colon and endoscope. Results The proposed simulation framework has been implemented and evaluated in colonoscopy simulation. The simulation results show that the proposed method allows real-time simulation (28 Hz) using a colon model composed of up to 241,440 meshes. Conclusions The proposed method allows real-time simulation of colon and endoscope deformation while maintaining a visually plausible result and realistic haptic sensation. Copyright © 2012 John Wiley & Sons, Ltd.