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https://www.readbyqxmd.com/read/28814032/studying-the-implementation-of-iterative-impedance-control-for-assistive-hand-rehabilitation-using-an-exoskeleton
#1
T Martineau, R Vaidyanathan
A positive training synergy can be obtained when two individuals attempt to learn the same motor task while mechanically coupled to one another. In this paper, we have studied how mimicking this interaction through impedance control can be exploited to improve assistance delivered by hand exoskeleton devices during rehabilitation. In this context, the machine and user take complementary roles akin to two coupled individuals. We present the derivation of a dynamic model of the human hand for the purpose of controller development for new hand exoskeleton platforms...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813959/-wink-to-grasp-comparing-eye-voice-emg-gesture-control-of-grasp-with-soft-robotic-gloves
#2
Bernardo Noronha, Sabine Dziemian, Giuseppe A Zito, Charalambos Konnaris, A Aldo Faisal
The ability of robotic rehabilitation devices to support paralysed end-users is ultimately limited by the degree to which human-machine-interaction is designed to be effective and efficient in translating user intention into robotic action. Specifically, we evaluate the novel possibility of binocular eye-tracking technology to detect voluntary winks from involuntary blink commands, to establish winks as a novel low-latency control signal to trigger robotic action. By wearing binocular eye-tracking glasses we enable users to directly observe their environment or the actuator and trigger movement actions, without having to interact with a visual display unit or user interface...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813938/online-sparse-gaussian-process-based-human-motion-intent-learning-for-an-electrically-actuated-lower-extremity-exoskeleton
#3
Yi Long, Zhi-Jiang Du, Chao-Feng Chen, Wei Dong, Wei-Dong Wang
The most important step for lower extremity exoskeleton is to infer human motion intent (HMI), which contributes to achieve human exoskeleton collaboration. Since the user is in the control loop, the relationship between human robot interaction (HRI) information and HMI is nonlinear and complicated, which is difficult to be modeled by using mathematical approaches. The nonlinear approximation can be learned by using machine learning approaches. Gaussian Process (GP) regression is suitable for high-dimensional and small-sample nonlinear regression problems...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813929/soft-brain-machine-interfaces-for-assistive-robotics-a-novel-control-approach
#4
Lucia Schiatti, Jacopo Tessadori, Giacinto Barresi, Leonardo S Mattos, Arash Ajoudani
Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813907/position-and-stiffness-modulation-of-a-wrist-haptic-device-using-myoelectric-interface
#5
Chris Wilson Antuvan, Lorenzo Masia
Modulation of stiffness provides a great deal of advantage in the way humans interact with the environment, and is very important in successfully performing activities of daily living. In the context of human-machine interactions, stiffness control could provide a safer interaction, especially when dealing with unpredictable environment. In this paper we propose a user-modulated stiffness and position control for the wrist flexion/extension degree of freedom while physically coupled to a haptic device. A virtual position tracking experiment in a varying external force field is designed in order to test the performance of the control strategy with and without co-contraction techniques...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813903/let-s-do-this-together-bi-manu-interact-a-novel-device-for-studying-human-haptic-interactive-behavior
#6
Ekaterina Ivanova, Axel Krause, Marie Schalicke, Franziska Schellhardt, Natalie Jankowski, Josy Achner, Henning Schmidt, Michael Joebges, Jorg Kruger
Our area of interest is robotic-based rehabilitation after stroke, and our goal is to help patients achieve optimal motor learning during high-intensity repetitive movement training through the assistance of robots. It is important, that the robotic assistance is adapted to the patients' abilities, thereby ensuring that the device is only supporting the patient as necessary ("assist-as-needed"). We hypothesize that natural and learning-effective human-machine interaction can be achieved by programming the robot's control, so that it emulates how a physiotherapist adaptively supports the patients' limb movement during stroke rehabilitation...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28806936/enhancement-of-hepatitis-virus-immunoassay-outcome-predictions-in-imbalanced-routine-pathology-data-by-data-balancing-and-feature-selection-before-the-application-of-support-vector-machines
#7
Alice M Richardson, Brett A Lidbury
BACKGROUND: Data mining techniques such as support vector machines (SVMs) have been successfully used to predict outcomes for complex problems, including for human health. Much health data is imbalanced, with many more controls than positive cases. METHODS: The impact of three balancing methods and one feature selection method is explored, to assess the ability of SVMs to classify imbalanced diagnostic pathology data associated with the laboratory diagnosis of hepatitis B (HBV) and hepatitis C (HCV) infections...
August 14, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28806050/linking-high-throughput-screens-to-identify-moas-and-novel-inhibitors-of-mycobacterium-tuberculosis-dihydrofolate-reductase
#8
John P Santa Maria, Yumi Park, Lihu Yang, Nicholas Murgolo, Michael D Altman, Paul Zuck, Greg Adam, Chad Chamberlin, Peter Saradjian, Peter Dandliker, Helena I M Boshoff, Clifton E Barry, Charles Garlisi, David B Olsen, Katherine Young, Meir Glick, Elliott Nickbarg, Peter S Kutchukian
Though phenotypic and target-based high-throughput screening approaches have been employed to discover new antibiotics, the identification of promising therapeutic candidates remains challenging. Each approach provides different information, and understanding their results can provide hypotheses for mechanism of action (MoA) and reveal actionable chemical matter. Here we describe a framework for identifying efficacy targets of bioactive compounds. High throughput biophysical profiling against a broad range of targets coupled with machine learning is employed to identify chemical features with predicted efficacy targets for a given phenotypic screen...
August 14, 2017: ACS Chemical Biology
https://www.readbyqxmd.com/read/28802824/highly-accurate-prediction-of-protein-self-interactions-by-incorporating-the-average-block-and-pssm-information-into-the-general-pseaac
#9
Jing-Xuan Zhai, Tian-Jie Cao, Ji-Yong An, Yong-Tao Bian
It is a challenging task for fundamental research whether proteins can interact with their partners. Protein self-interaction (SIP) is a special case of PPIs, which plays a key role in the regulation of cellular functions. Due to the limitations of experimental self-interaction identification, it is very important to develop an effective biological tool for predicting SIPs based on protein sequences. In the study, we developed a novel computational method called RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) for detecting SIPs from protein sequences...
August 9, 2017: Journal of Theoretical Biology
https://www.readbyqxmd.com/read/28796622/w-fyd-a-wearable-fabric-based-display-for-haptic-multi-cue-delivery-and-tactile-augmented-reality
#10
Simone Fani, Simone Ciotti, Edoardo Battaglia, Alessandro Moscatelli, Matteo Bianchi
Despite the importance of softness, there is no evidence of wearable haptic systems able to deliver controllable softness cues. Here, we present the Wearable Fabric Yielding Display (W-FYD), a fabric-based display for multi-cue delivery that can be worn on user's finger and enables, for the first time, both active and passive softness exploration. It can also induce a sliding effect under the finger-pad. A given stiffness profile can be obtained by modulating the stretching state of the fabric through two motors...
August 7, 2017: IEEE Transactions on Haptics
https://www.readbyqxmd.com/read/28775347/liquid-metal-amoeba-with-spontaneous-pseudopodia-formation-and-motion-capability
#11
Liang Hu, Bin Yuan, Jing Liu
The unique motion of amoeba with a deformable body has long been an intriguing issue in scientific fields ranging from physics, bionics to mechanics. So far, most of the currently available artificial machines are still hard to achieve the complicated amoeba-like behaviors including stretching pseudopodia. Here through introducing a multi-materials system, we discovered a group of very unusual biomimetic amoeba-like behaviors of self-fueled liquid gallium alloy on the graphite surface immersed in alkaline solution...
August 3, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28769776/affective-aspects-of-perceived-loss-of-control-and-potential-implications-for-brain-computer-interfaces
#12
Sebastian Grissmann, Thorsten O Zander, Josef Faller, Jonas Brönstrup, Augustin Kelava, Klaus Gramann, Peter Gerjets
Most brain-computer interfaces (BCIs) focus on detecting single aspects of user states (e.g., motor imagery) in the electroencephalogram (EEG) in order to use these aspects as control input for external systems. This communication can be effective, but unaccounted mental processes can interfere with signals used for classification and thereby introduce changes in the signal properties which could potentially impede BCI classification performance. To improve BCI performance, we propose deploying an approach that potentially allows to describe different mental states that could influence BCI performance...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28769747/movement-related-sensorimotor-high-gamma-activity-mainly-represents-somatosensory-feedback
#13
Seokyun Ryun, June S Kim, Eunjeong Jeon, Chun K Chung
Somatosensation plays pivotal roles in the everyday motor control of humans. During active movement, there exists a prominent high-gamma (HG >50 Hz) power increase in the primary somatosensory cortex (S1), and this provides an important feature in relation to the decoding of movement in a brain-machine interface (BMI). However, one concern of BMI researchers is the inflation of the decoding performance due to the activation of somatosensory feedback, which is not elicited in patients who have lost their sensorimotor function...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28761935/the-skin-microbiome-of-cohabiting-couples
#14
Ashley A Ross, Andrew C Doxey, Josh D Neufeld
Distinct microbial communities inhabit individuals as part of the human skin microbiome and are continually shed to the surrounding environment. Microbial communities from 17 skin sites of 10 sexually active cohabiting couples (20 individuals) were sampled to test whether cohabitation impacts an individual's skin microbiome, leading to shared skin microbiota among partner pairs. Amplified 16S rRNA genes of bacteria and archaea from a total of 340 skin swabs were analyzed by high-throughput sequencing, and the results demonstrated that cohabitation was significantly associated with microbial community composition, although this association was greatly exceeded by characteristics of body location and individuality...
July 2017: MSystems
https://www.readbyqxmd.com/read/28754147/design-and-implementation-of-a-custom-next-generation-sequencing-panel-for-selected-vitamin-d-associated-genes
#15
Katherine Angela Benson, Sourabh Chand, Alexander Peter Maxwell, Laura Jane Smyth, Jill Kilner, Richard Borrows, Amy Jayne McKnight
BACKGROUND: Biologically active vitamin D has an important regulatory role within the genome. It binds the vitamin D receptor (VDR) in order to control the expression of a wide range of genes as well as interacting with the epigenome to modify chromatin and methylation status. Vitamin D deficiency is associated with several human diseases including end-stage renal disease. METHODS: This article describes the design and testing of a custom, targeted next generation sequencing (NGS) panel for selected vitamin D associated genes...
July 28, 2017: BMC Research Notes
https://www.readbyqxmd.com/read/28738675/transparent-and-flexible-triboelectric-sensing-array-for-touch-security-applications
#16
Zuqing Yuan, Tao Zhou, Yingying Yin, Ran Cao, Congju Li, Zhong Lin Wang
Tactile sensor with large-scale array and high sensitivity is essential for human-machine interaction, smart wearable devices and mobile network. Here, a transparent and flexible triboelectric sensing array (TSA) with fingertip-sized pixels is demonstrated by integrating ITO electrodes, FEP film and signal-transmission circuits on an undivided palm-sized PET substrate. The sensing pixels can be triggered by the corresponding external contact to induce the electrostatic potential in the transparent electrodes without power consumption, which is individually recognized by the sensor...
July 24, 2017: ACS Nano
https://www.readbyqxmd.com/read/28728020/neuroscience-inspired-artificial-intelligence
#17
REVIEW
Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, Matthew Botvinick
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals...
July 19, 2017: Neuron
https://www.readbyqxmd.com/read/28727560/a-multimodal-framework-based-on-integration-of-cortical-and-muscular-activities-for-decoding-human-intentions-about-lower-limb-motions
#18
Chengkun Cui, Gui-Bin Bian, Zeng-Guang Hou, Jun Zhao, Hao Zhou
In this study, a multimodal fusion framework based on three different modal biosignals is developed to recognize human intentions related to lower limb multi-joint motions which commonly appear in daily life. Electroencephalogram (EEG), electromyogram (EMG) and mechanomyogram (MMG) signals were simultaneously recorded from twelve subjects while performing nine lower limb multi-joint motions. These multimodal data are used as the inputs of the fusion framework for identification of different motion intentions...
August 2017: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/28726762/user-interaction-modeling-and-profile-extraction-in-interactive-systems-a-groupware-application-case-study
#19
Cristina Tîrnăucă, Rafael Duque, José L Montaña
A relevant goal in human-computer interaction is to produce applications that are easy to use and well-adjusted to their users' needs. To address this problem it is important to know how users interact with the system. This work constitutes a methodological contribution capable of identifying the context of use in which users perform interactions with a groupware application (synchronous or asynchronous) and provides, using machine learning techniques, generative models of how users behave. Additionally, these models are transformed into a text that describes in natural language the main characteristics of the interaction of the users with the system...
July 20, 2017: Sensors
https://www.readbyqxmd.com/read/28725997/mitotic-spindle-kinetochore-fibers-hold-on-tight-to-interpolar-bundles
#20
REVIEW
Iva M Tolić
When a cell starts to divide, it forms a spindle, a micro-machine made of microtubules, which separates the duplicated chromosomes. The attachment of microtubules to chromosomes is mediated by kinetochores, protein complexes on the chromosome. Spindle microtubules can be divided into three major classes: kinetochore microtubules, which form k-fibers ending at the kinetochore; interpolar microtubules, which extend from the opposite sides of the spindle and interact in the middle; and astral microtubules, which extend towards the cell cortex...
July 19, 2017: European Biophysics Journal: EBJ
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