Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 113 of 113 Journals sorted alphabetically
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Human-Robot Interaction     Open Access   (Followers: 3)
Advanced Robotics     Hybrid Journal   (Followers: 28)
Advances in Computed Tomography     Open Access   (Followers: 2)
Advances in Image and Video Processing     Open Access   (Followers: 25)
Advances in Robotics & Automation     Open Access   (Followers: 11)
American Journal of Robotic Surgery     Full-text available via subscription   (Followers: 7)
Annual Review of Control, Robotics, and Autonomous Systems     Full-text available via subscription   (Followers: 12)
Artificial Life and Robotics     Hybrid Journal   (Followers: 17)
Augmented Human Research     Hybrid Journal  
Automated Software Engineering     Hybrid Journal   (Followers: 9)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Automation and Remote Control     Hybrid Journal   (Followers: 5)
Autonomous Agents and Multi-Agent Systems     Hybrid Journal   (Followers: 9)
Autonomous Robots     Hybrid Journal   (Followers: 11)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomimetic Intelligence and Robotics     Open Access  
Cognitive Robotics     Open Access   (Followers: 6)
Computational Intelligence and Neuroscience     Open Access   (Followers: 18)
Computer-Aided Design     Hybrid Journal   (Followers: 9)
Construction Robotics     Hybrid Journal   (Followers: 4)
Current Robotics Reports     Hybrid Journal   (Followers: 4)
Cybernetics & Human Knowing     Full-text available via subscription   (Followers: 3)
Cybernetics and Systems Analysis     Hybrid Journal  
Cybernetics and Systems: An International Journal     Hybrid Journal   (Followers: 1)
Design Automation for Embedded Systems     Hybrid Journal   (Followers: 7)
Digital Zone : Jurnal Teknologi Informasi Dan Komunikasi     Open Access  
Drone Systems and Applications     Open Access   (Followers: 1)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Facta Universitatis, Series : Automatic Control and Robotics     Open Access   (Followers: 1)
Foundations and Trends® in Robotics     Full-text available via subscription   (Followers: 5)
Frontiers in Neurorobotics     Open Access   (Followers: 6)
Frontiers in Robotics and AI     Open Access   (Followers: 8)
GIScience & Remote Sensing     Open Access   (Followers: 59)
IAES International Journal of Robotics and Automation     Open Access   (Followers: 5)
IEEE Robotics & Automation Magazine     Full-text available via subscription   (Followers: 70)
IEEE Robotics and Automation Letters     Hybrid Journal   (Followers: 9)
IEEE Transactions on Affective Computing     Hybrid Journal   (Followers: 23)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 17)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 71)
IEEE Transactions on Cybernetics     Hybrid Journal   (Followers: 16)
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
IEEE Transactions on Medical Robotics and Bionics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Neural Networks and Learning Systems     Hybrid Journal   (Followers: 54)
IEEE Transactions on Robotics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews     Hybrid Journal   (Followers: 16)
IET Cyber-systems and Robotics     Open Access   (Followers: 2)
IET Systems Biology     Open Access   (Followers: 1)
Industrial Robot An International Journal     Hybrid Journal   (Followers: 2)
Intelligent Control and Automation     Open Access   (Followers: 6)
Intelligent Service Robotics     Hybrid Journal   (Followers: 2)
International Journal of Adaptive, Resilient and Autonomic Systems     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Pervasive and Ubiquitous Computing     Full-text available via subscription   (Followers: 4)
International Journal of Advanced Robotic Systems     Full-text available via subscription   (Followers: 1)
International Journal of Agent Technologies and Systems     Full-text available via subscription   (Followers: 4)
International Journal of Ambient Computing and Intelligence     Full-text available via subscription   (Followers: 3)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 3)
International Journal of Applied Evolutionary Computation     Full-text available via subscription   (Followers: 3)
International Journal of Artificial Life Research     Full-text available via subscription  
International Journal of Automation and Control     Hybrid Journal   (Followers: 11)
International Journal of Automation and Control Engineering     Open Access   (Followers: 5)
International Journal of Automation and Logistics     Hybrid Journal   (Followers: 3)
International Journal of Automation and Smart Technology     Open Access   (Followers: 3)
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 15)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 2)
International Journal of Cyber Behavior, Psychology and Learning     Full-text available via subscription   (Followers: 7)
International Journal of Humanoid Robotics     Hybrid Journal   (Followers: 6)
International Journal of Imaging & Robotics     Full-text available via subscription   (Followers: 3)
International Journal of Intelligent Information Technologies     Full-text available via subscription   (Followers: 2)
International Journal of Intelligent Machines and Robotics     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Mechatronics and Robotics     Full-text available via subscription   (Followers: 5)
International Journal of Intelligent Robotics and Applications     Hybrid Journal  
International Journal of Intelligent Systems Design and Computing     Hybrid Journal   (Followers: 1)
International Journal of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 3)
International Journal of Machine Consciousness     Hybrid Journal   (Followers: 6)
International Journal of Machine Learning and Cybernetics     Hybrid Journal   (Followers: 38)
International Journal of Machine Learning and Networked Collaborative Engineering     Open Access   (Followers: 16)
International Journal of Mechanisms and Robotic Systems     Hybrid Journal   (Followers: 2)
International Journal of Mechatronics and Automation     Hybrid Journal   (Followers: 5)
International Journal of Robotics and Automation     Full-text available via subscription   (Followers: 8)
International Journal of Robotics and Control     Open Access   (Followers: 3)
International Journal of Robotics Applications and Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Robotics Research     Hybrid Journal   (Followers: 15)
International Journal of Space-Based and Situated Computing     Hybrid Journal   (Followers: 2)
International Journal of Synthetic Emotions     Full-text available via subscription  
International Journal of Tomography & Simulation     Full-text available via subscription   (Followers: 1)
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Biomechanical Engineering     Full-text available via subscription   (Followers: 12)
Journal of Computer Assisted Tomography     Hybrid Journal   (Followers: 2)
Journal of Control & Instrumentation     Full-text available via subscription   (Followers: 19)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 13)
Journal of Intelligent and Robotic Systems     Hybrid Journal   (Followers: 6)
Journal of Intelligent Learning Systems and Applications     Open Access   (Followers: 4)
Journal of Physical Agents     Open Access   (Followers: 1)
Journal of Robotic Surgery     Hybrid Journal   (Followers: 3)
Journal of Robotics     Open Access   (Followers: 6)
Jurnal Otomasi Kontrol dan Instrumentasi     Open Access  
Machine Translation     Hybrid Journal   (Followers: 13)
Proceedings of the ACM on Human-Computer Interaction     Hybrid Journal   (Followers: 3)
Results in Control and Optimization     Open Access   (Followers: 3)
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
ROBOMECH Journal     Open Access   (Followers: 1)
Robotic Surgery : Research and Reviews     Open Access   (Followers: 1)
Robotica     Hybrid Journal   (Followers: 5)
Robotics and Autonomous Systems     Hybrid Journal   (Followers: 19)
Robotics and Biomimetics     Open Access   (Followers: 1)
Robotics and Computer-Integrated Manufacturing     Hybrid Journal   (Followers: 7)
Science Robotics     Full-text available via subscription   (Followers: 11)
Soft Robotics     Hybrid Journal   (Followers: 5)
Universal Journal of Control and Automation     Open Access   (Followers: 2)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 3)

           

Similar Journals
Journal Cover
Artificial Life and Robotics
Journal Prestige (SJR): 0.226
Number of Followers: 17  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1614-7456 - ISSN (Online) 1433-5298
Published by Springer-Verlag Homepage  [2468 journals]
  • Design of social navigation quality evaluation model based on combined
           weight

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      Abstract: Abstract Based on the human–robot interaction behavior of mobile robots in social navigation, this paper proposes a social navigation quality evaluation model based on combined weights for the problems of single indicators, rough quantification and non-convergence of information in social navigation quality evaluation. Firstly, three evaluation modules of comfort, naturalness and sociality are designed, and each module is refined into primary and secondary indicators. The robot path navigation data are calculated by the indicator quantification formula. Secondly, the subjective and objective weights of hierarchical analysis method and the entropy weight method are combined to determine the index weights at each level. The weighted sum is used to achieve the fusion of index information and obtain the optimal solution of the evaluation navigation algorithm. Finally, we simulate the social scene through visualization simulation experiments to obtain the trajectory data of the robot in the social scene. The experimental results verify the feasibility of the theoretical model and give the final scores and optimization opinions of the tested algorithms. Through the evaluation of the social navigation quality evaluation model, the path planning algorithm that best suits the comfort perception of pedestrians in the current scenario can be found in the tested algorithms.
      PubDate: 2023-08-28
       
  • High-frequency SSVEP–BCI with less flickering sensation using
           personalization of stimulus frequency

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      Abstract: Abstract The problem of brain–computer interface (BCI) using steady-state visual evoked potential (SSVEP) is a flickering sensation caused by the flashing stimuli used to induce SSVEP. To use of high-frequency flashing stimuli is one of the countermeasures of this problem. This study focused on the relationship between the magnitude of SSVEP components for each subject and proposed a high-frequency (56–70 Hz) SSVEP–BCI that uses only the frequencies at which SSVEP induction was confirmed. For comparison, the accuracy of SSVEP–BCI using learning CCA (LCCA), an extension of canonical correlation analysis (CCA), was 98.61% for the low-frequency (26–40 Hz) SSVEP–BCI for comparison, 62.78% for the high frequency (56–70 Hz) SSVEP–BCI, and 87.19% for the high frequency (56–70 Hz) SSVEP–BCI with personalized stimulus frequency. As a result of comparing with and without personalization using information transfer rate (ITR), non-personalized (normal) and personalized high-frequency SSVEP–BCI ITR were 24.25 bits/min and 29.64 bits/min.
      PubDate: 2023-08-10
       
  • Development of keypads which use colors or shapes to prevent shoulder
           surfing

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      Abstract: Abstract In conventional smart phones and ATMs, a four-digit passcode is entered into a keypad, and the user confirms whether the passcode matches the keypad. However, there is a risk that a third party can easily steal the password by watching the code entry or analyzing the position of fingerprints left on the keypad. There are other solutions, such as biometric authentication or the use of special displays, but both of them are costly and difficult to implement. In this study, we propose a keypad that does not leave fingerprints on the screen, is low cost, and can be used to input passcodes without worry, even if someone is standing next to it. The proposed keypad uses cursors that are moved by directional keys to select numbers, making fingerprint analysis difficult. Because attackers do not know the color that the user has selected, they cannot know which cursor the user is moving. To verify the safety and convenience of this system, we conducted experiments on subjects in their 20 s and 50 s. The results showed that the average difference in authentication time from the conventional method was about 5 s, and the method was generally convenient. We conclude that our keypad system is secure, because no peeping attacks on a subject were successful in guessing the subject’s passcode.
      PubDate: 2023-08-02
       
  • Does the Gel Biter create an illusion of food texture perception due to
           differences in mastication speed '

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      Abstract: Abstract One of the new computational frameworks is physical reservoir computing. Focusing on this method, we have previously developed a soft-matter artificial mouth ”Gel Biter”, which is composed of multiple polymeric materials based on the structure of the human oral cavity. This soft machine can discriminate even subtle differences in food texture with high accuracy. In general, chewing speed differs from person to person. Then, we focus on the result that brittle foods tend to be chewed faster or more finely based on sensory evaluation in some cognitive studies. This study has analyzed the accuracy of the Gel Biter by changing the parameters of its robotic arm and the differences in food texture perceived when the chewing speed is changed. As a result, there is no significant difference in discrimination accuracy for each speed. The cluster analysis shows that the food characteristics are captured and classified. In addition, the estimation results for Fast chewing indicate that the mechanical mouth also generates the illusion that humans perceive different food textures.
      PubDate: 2023-08-01
       
  • Correction to: Development of a behavioral trajectory measurement system
           (Bucket-ANTAM) for organisms moving in a two-dimensional plane

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      PubDate: 2023-08-01
       
  • Six-legged crawling soft robot: NOBIYAKA

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      Abstract: Abstract In recent years, soft robotics composed of soft silicone rubber have attracted significant attention, as they can adapt to various unknown environments owing to their flexible bodies, resulting into a variety of robots. In our previous work, we focused on robots that operate in real complex environments, such as rescue robots, agriculture robots, and contracting robots, and developed various flexible robots such as octopus-like manipulators, pipe-climbing robots, and wall-climbing robots. In this study, we aimed to develop a multi-legged soft robot that can move in various types of surfaces, and then we employed a layered structure for the robot body to assemble it easily. We developed an actual robot and conducted experiments to confirm its mobility in three environments: a horizontal board, pebbles, and water. As a result, we confirmed that the desired crawling motion was realized and the proposed robot could move in various types of surfaces by using the dynamics of its soft body. Additionally, this study confirmed that the designed soft robot works as an integrated system, that is, the soft body simultaneously works as a structure, actuator, sensor, and controller.
      PubDate: 2023-08-01
       
  • An investigation of software describing methods to design dual background
           scrolling hardware in high-level synthesis

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      Abstract: Abstract We are developing a game programing library which can be converted to hardware modules by high-level synthesis, HLS technology to realize high-performance and low-power mobile terminals executing game applications. High-level synthesis is a technology that converts software into hardware automatically. The game software is executed by high-speed and low-power hardware on the reconfigurable devices in the mobile terminals instead of power-hungry software execution. To make high-level synthesis tool generate desirable hardware module, we must describe software program well considering the hardware organization. In this paper, we developed two software description methods for dual background scrolling processing as one of functions in high-level synthesis-oriented game software library. We also evaluate the execution time, resource usage, and power consumption of hardware modules that high-level synthesis generated through the experiments and investigate which hardware module has better performance.
      PubDate: 2023-08-01
       
  • Automatic parameter learning method for agent activation spreading network
           by evolutionary computation

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      Abstract: Abstract A variety of planning research is being actively conducted in multiple research fields. The focus of these studies is to flexibly utilize both immediate and deliberative planning in response to the environment and to adaptively prioritize multiple goals and actions in a human-like manner. To achieve this, a method that applies active propagation to multi-agent planning (agent activation spreading network) has been proposed and is being utilized in various research fields. Furthermore, with the recent development of large-scale artificial intelligence models, we should soon be able to incorporate tacit human knowledge into this architecture. However, there is not yet a method for adjusting the parameters in this architecture which creates a barrier to future extension. In response, we have developed a method for automatically adjusting the parameters using evolutionary computation. Our experimental results showed that (1) the proposed method enables a higher degree of adaptation, thanks to taking the agent’s semantics into account, and (2) it is possible to obtain parameters that are appropriate to the environment even when the experimental environment is changed.
      PubDate: 2023-08-01
       
  • Development of a person-following robotic assist walker with
           compliant-control arbitrated role-switching

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      Abstract: Abstract To help ease the caregiving burden that comes with population aging, we proposed a bistable control system for walking-assist robots in which the transition between two stable control modes is governed using a compliance-controlled handle. The first modeis where the robot takes the role of the leader and operates autonomously by following a target person. Whereas in the second mode, the user is the leader, and the robot follows the intent of the user. In these two stable control modes, because either the leader or the robot is fully in control, there is minimal conflict of intent, thereby reducing physical and cognitive load of the user as well as minimizing competition between the intent of the user and that of the robot. When there is a conflict, the robot and the user express their intent physically by rotating the compliance-controlled handle. This compliance-controlled handle arbitrates between the user’s and the robot’s intent and decides whether to transition to a different stable control mode (switching roles) depending on the angle rotated.
      PubDate: 2023-08-01
       
  • Analysis of negative phototaxis in the pill bug (Armadillidium vulgare)
           using omnidirectional servosphere

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      Abstract: Abstract In recent years, automated systems and robots have been implemented in biological behavioral experiments to understand taxis. In this study, we propose a servosphere system (PSYCO-ANTAM) that is an extension of our previous studies. We measured the negative phototaxis of a pill bug (Armadillidium vulgare) as in the previous studies. A photostimulus presentation system was placed around the sphere of the PSYCO-ANTAM to control the presentation method of the photostimuli. By measuring the behavior of target organisms that receive these stimuli, we can measure changes in their phototactic behavior. In this study, PSYCO-ANTAM was used to clarify the conditions under which negative phototaxis occurs in pill bugs.
      PubDate: 2023-08-01
       
  • Detecting deception using machine learning with facial expressions and
           pulse rate

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      Abstract: Abstract Given the ongoing COVID-19 pandemic, remote interviews have become an increasingly popular approach in many fields. For example, a survey by the HR Research Institute (PCR Institute in Survey on hiring activities for graduates of 2021 and 2022. https://www.hrpro.co.jp/research_detail.php'r_no=273. Accessed 03 Oct 2021) shows that more than 80% of job interviews are conducted remotely, particularly in large companies. However, for some reason, an interviewee might attempt to deceive an interviewer or feel difficult to tell the truth. Although the ability of interviewers to detect deception among interviewees is significant for their company or organization, it still strongly depends on their individual experience and cannot be automated. To address this issue, in this study, we propose a machine learning approach to aid in detecting whether a person is attempting to deceive the interlocutor by associating the features of their facial expressions with those of their pulse rate. We also constructed a more realistic dataset for the task of deception detection by asking subjects not to respond artificially, but rather to improvise natural responses using a web camera and wearable device (smartwatch). The results of an experimental evaluation of the proposed approach with 10-fold cross-validation using random forests classifier show that the accuracy and the F1 value were in the range between 0.75 and 0.8 for each subject, and the highest values were 0.87 and 0.88, respectively. Through the analysis of the importance of the features the trained models, we revealed the crucial features of each subject during deception, which differed among the subjects.
      PubDate: 2023-08-01
       
  • Video stabilization algorithm for field robots in uneven terrain

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      Abstract: Abstract Field robots equipped with visual sensors have been used to automate several services. In many scenarios, these robots are tele-operated by a remote operator who controls the robot motion based on a live video feed from the robot’s cameras. In other cases, like surveillance and monitoring applications, the video recorded by the robot is later analyzed or inspected manually. A shaky video is produced on an uneven terrain. It could also be caused due to loose and vibrating mechanical frame on which the camera has been mounted. Jitters or shakes in these videos are undesired for tele-operation, and to maintain desired quality of service. In this paper, we present an algorithm to stabilize the undesired jitters in a shaky video using only the camera information for different areas of vineyard based on terrain profile. The algorithm works by tracking robust feature points in the successive frames of the camera, smoothing the trajectory, and generating desired transformations to output a stabilized video. We have tested the algorithm in actual field robots in uneven terrains used for agriculture, and found the algorithm to produce good results.
      PubDate: 2023-07-11
      DOI: 10.1007/s10015-023-00883-x
       
  • Improvements of detection accuracy and its confidence of defective areas
           by YOLOv2 using a data set augmentation method

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      Abstract: Abstract Recently, CNN (Convolutional Neural Network) and Grad-CAM (Gradient-weighted Class Activation Map) are being applied to various kinds of defect detection and position recognition for industrial products. However, in training process of a CNN model, a large amount of image data are required to acquire a desired generalization ability. In addition, it is not easy for Grad-CAM to clearly identify the defect area which is predicted as the basis of a classification result. Moreover, when they are deployed in an actual production line, two calculation processes for CNN and Grad-CAM have to be sequentially called for defect detection and position recognition, so that the processing time is concerned. In this paper, the authors try to apply YOLOv2 (You Only Look Once) to defect detection and its visualization to process them at once. In general, a YOLOv2 model can be built with less training images; however, a complicated labeling process is required to prepare ground truth data for training. A data set for training a YOLOv2 model has to be composed of image files and the corresponding ground truth data file named gTruth. The gTruth file has names of all the image files and their labeled information, such as label names and box dimensions. Therefore, YOLOv2 requires complex data set augmentation for not only images but also gTruth data. Actually, target products dealt with in this paper are produced with various kinds and small quantity, and also the frequency of occurrence of the defect is infrequent. Moreover, due to the fixed indoor production line, the valid image augmentation to be applied is limited to the horizontal flip. In this paper, a data set augmentation method is proposed to efficiently generate training data for YOLOv2 even in such a production situation and to consequently enhance the performance of defect detection and its visualization. The effectiveness is shown through experiments.
      PubDate: 2023-07-08
      DOI: 10.1007/s10015-023-00885-9
       
  • Real-time monitoring of elderly people through computer vision

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      Abstract: Abstract In recent years, many countries including Japan are facing the problems of increasing old-age population and shortage of labor. This has increased the demands of automating several tasks using robots and artificial intelligence in agriculture, production, and healthcare sectors. With increasing old-age population, an increasing number of people are expected to be admitted in old-age home and rehabilitation centers in the coming years where they receive proper care and attention. In such a scenario, it can be foreseen that it will be increasingly difficult to accurately monitor each patient. This requires an automation of patient’s activity detection. To this end, this paper proposes to use computer vision for automatic detection of patient’s behavior. The proposed work first detects the pose of the patient through a Convolution Neural Network. Next, the coordinates of the different body parts are detected. These coordinates are input in the decision generation layer which uses the relationship between the coordinates to predict the person’s actions. This paper focuses on the detection of important activities like: sudden fall, sitting, eating, sleeping, exercise, and computer usage. Although previous works in behavior detection focused only on detecting a particular activity, the proposed work can detect multiple activities in real-time. We verify the proposed system thorough experiments in real environment with actual sensors. The experimental results shows that the proposed system can accurately detect the activities of the patient in the room. Critical scenarios like sudden fall are detected and an alarm is raised for immediate support. Moreover, the the privacy of the patient is preserved though an ID based method in which only the detected activities are chronologically stored in the database.
      PubDate: 2023-07-06
      DOI: 10.1007/s10015-023-00882-y
       
  • Pain scores estimation using surgical pleth index and long short-term
           memory neural networks

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      Abstract: Abstract Pain monitoring is crucial to provide proper healthcare for patients during general anesthesia (GA). In this study, photoplethysmographic waveform amplitude (PPGA), heartbeat interval (HBI), and surgical pleth index (SPI) are utilized for predicting pain scores during GA based on expert medical doctors’ assessments (EMDAs). Time series features are fed into different long short-term memory (LSTM) models, with different hyperparameters. The models’ performance is evaluated using mean absolute error (MAE), standard deviation (SD), and correlation (Corr). Three different models are used, the first model resulted in 6.9271 ± 1.913, 9.4635 ± 2.456, and 0.5955 0.069 for an overall MAE, SD, and Corr, respectively. The second model resulted in 3.418 ± 0.715, 3.847 ± 0.557, and 0.634 ± 0.068 for an overall MAE, SD, and Corr, respectively. In contrast, the third model resulted in 3.4009 ± 0.648, 3.909 ± 0.548, and 0.6197 ± 0.0625 for an overall MAE, SD, and Corr, respectively. The second model is selected as the best model based on its performance and applied 5-fold cross-validation for verification. Statistical results are quite similar: 4.722 ± 0.742, 3.922 ± 0.672, and 0.597 ± 0.053 for MAE, SD, and Corr, respectively. In conclusion, the SPI effectively predicted pain score based on EMDA, not only on good evaluation performance, but the trend of EMDA is replicated, which can be interpreted as a relation between SPI and EMDA; however, further improvements on data consistency are also needed to validate the results and obtain better performance. Furthermore, the usage of further signal features could be considered along with SPI.
      PubDate: 2023-06-24
      DOI: 10.1007/s10015-023-00880-0
       
  • MORI-A CPS: 3D printed soft actuators with 4D assembly simulation

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      Abstract: Abstract Soft modular robotics combines soft materials and modular mechanisms. We are developing a vacuum-driven actuator module, MORI-A, which combines a 3D-printed flexible parallel cross structure with a cube-shaped hollow silicone. The MORI-A module has five deformation modes: no deformation, uniform contraction, uniaxial contraction, flexion, and shear. By combining these modules, soft robots with a variety of deformabilities can be constructed. However, assembling MORI-A requires predicting the deformation from the posture and mode of the modules, making assembly difficult. To overcome this problem, this study aims to construct a system called “MORI-A CPS,” which can predict the motion of a soft robot composed of MORI-A modules by simply arranging cubes in a virtual space. This paper evaluates how well the motion of virtual MORI-A modules, defined as a combination of swelling and shrinking voxels, approximates real-world motion. Then, it shows that the deformations of virtual soft robots constructed via MORI-A CPS are similar to those of real robots.
      PubDate: 2023-06-17
      DOI: 10.1007/s10015-023-00878-8
       
  • Correction to: Detecting deception using machine learning with facial
           expressions and pulse rate

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      PubDate: 2023-06-13
      DOI: 10.1007/s10015-023-00877-9
       
  • Engineering a data processing pipeline for an ultra-lightweight lensless
           fluorescence imaging device with neuronal-cluster resolution

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      Abstract: Abstract In working toward the goal of uncovering the inner workings of the brain, various imaging techniques have been the subject of research. Among the prominent technologies are devices that are based on the ability of transgenic animals to signal neuronal activity through fluorescent indicators. This paper investigates the utility of an original ultra-lightweight needle-type device in fluorescence neuroimaging. A generalizable data processing pipeline is proposed to compensate for the reduced image resolution of the lensless device. In particular, a modular solution centered on baseline-induced noise reduction and principal component analysis is designed as a stand-in for physical lenses in the aggregation and quasi-reconstruction of neuronal activity. Data-driven evidence backing the identification of regions of interest is then demonstrated, establishing the relative superiority of the method over neuroscience conventions within comparable contexts.
      PubDate: 2023-06-12
      DOI: 10.1007/s10015-023-00875-x
       
  • Experimental verification of the wavelet-based surface modeling method
           considering wear progression process

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      Abstract: Abstract Industrial technology has been significantly developed, and the high performance and precision machines are desired. Friction and wear are the important factors to achieve the development. Mechanical machines consisting of the parts have usually mating surfaces, and friction and wear on the surface affect the product performance and life. Therefore, friction and wear phenomena must be considered at the design stage to design a machine that has long life and high performance. Predicting the surface feature quantitatively and accurately is difficult because the wear phenomena are not cleared yet. There are various methods to predict the worn surfaces, but those methods cannot generate the virtual surfaces randomly. In this study, a generation method of the virtual primary profile curves is proposed in consideration of wear applying wavelet transformation, and the simulated profile curves are verified comparing the actual profiles obtained in actual experiments.
      PubDate: 2023-06-08
      DOI: 10.1007/s10015-023-00876-w
       
  • Estimation of habit-related information from male voice data using machine
           learning-based methods

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      Abstract: Abstract According to a survey on the cause of death among Japanese people, lifestyle-related diseases (such as malignant neoplasms, cardiovascular diseases, and pneumonia) account for 55.8% of all deaths. Three habits, namely, drinking, smoking, and sleeping, are considered the most important factors associated with lifestyle-related diseases, but it is difficult to measure these habits autonomously and regularly. Here, we propose a machine learning-based approach for detecting these lifestyle habits using voice data. We used classifiers and probabilistic linear discriminant analysis based on acoustic features, such as mel-frequency cepstrum coefficients (MFCCs) and jitter, extracted from a speech dataset we developed, and an X-vector from a pre-trained ECAPA-TDNN model. For training models, we used several classifiers implemented in MATLAB 2021b, such as support vector machines, K-nearest neighbors (KNN), and ensemble methods with some feature-projection options. Our results show that a cubic KNN method using acoustic features performs well on the sleep habit classification, while X-vector-based models perform well on smoking and drinking habit classifications. These results suggest that X-vectors may help estimate factors directly affecting the vocal cords and vocal tracts of the users (e.g., due to smoking and drinking), while acoustic features may help classify chronotypes, which might be informative with respect to the individuals’ vocal cord and vocal tract ultrastructure.
      PubDate: 2023-06-01
      DOI: 10.1007/s10015-023-00870-2
       
 
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