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Human machine interface

Quynh C Nguyen, Dapeng Li, Hsien-Wen Meng, Suraj Kath, Elaine Nsoesie, Feifei Li, Ming Wen
BACKGROUND: Studies suggest that where people live, play, and work can influence health and well-being. However, the dearth of neighborhood data, especially data that is timely and consistent across geographies, hinders understanding of the effects of neighborhoods on health. Social media data represents a possible new data resource for neighborhood research. OBJECTIVE: The aim of this study was to build, from geotagged Twitter data, a national neighborhood database with area-level indicators of well-being and health behaviors...
October 17, 2016: JMIR Public Health and Surveillance
Peter V Coveney, Edward R Dougherty, Roger R Highfield
The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales...
November 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
Kyle B Serkies, Reena Garcha, Laura E Tam, Grace M De Souza, Yoav Finer
OBJECTIVE: Assess the modulating effect of matrix metalloproteinase (MMP) inhibition on simulated human salivary enzyme (SHSE)-catalyzed degradation of interfacial fracture-toughness (FT) of self-etched and total-etched resin-dentin interfaces. METHODS: Miniature short-rod FT specimens (N=10/group) containing a resin composite bonded to human dentin, using a self-etch (Easy Bond, EB) or a total-etch (Scotchbond, SB) adhesives, were prepared with and without application of an MMP inhibitor (galardin)...
September 28, 2016: Dental Materials: Official Publication of the Academy of Dental Materials
David Azzopardi, Kharishma Patel, Tomasz Jaunky, Simone Santopietro, Oscar M Camacho, John McAughey, Marianna Gaça
Electronic cigarettes (E-cigarettes) are a potential means of addressing the harm to public health caused by tobacco smoking by offering smokers a less harmful means of receiving nicotine. As e-cigarettes are a relatively new phenomenon, there are limited scientific data on the longer-term health effects of their use. This study describes a robust in vitro method for assessing the cytotoxic response of e-cigarette aerosols that can be effectively compared with conventional cigarette smoke. This was measured using the regulatory accepted Neutral Red Uptake assay modified for air-liquid interface (ALI) exposures...
July 2016: Toxicology Mechanisms and Methods
Jianhai Zhang, Ming Chen, Shaokai Zhao, Sanqing Hu, Zhiguo Shi, Yu Cao
Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience...
2016: Sensors
Chang-Hyun Kim, Sujin Sung, Myung-Han Yoon
Organic neuromorphic devices hold great promise for unconventional signal processing and efficient human-machine interfaces. Herein, we propose novel synaptic organic transistors devised to overcome the traditional trade-off between channel conductance and memory performance. A vacuum-processed, nanoscale metallic interlayer provides an ultra-flat surface for a high-mobility molecular film as well as a desirable degree of charge trapping, allowing for low-temperature fabrication of uniform device arrays on plastic...
2016: Scientific Reports
Noel J Leigh, Ralph I Lawton, Pamela A Hershberger, Maciej L Goniewicz
BACKGROUND: E-cigarettes or electronic nicotine delivery systems (ENDS) are designed to deliver nicotine-containing aerosol via inhalation. Little is known about the health effects of flavoured ENDS aerosol when inhaled. METHODS: Aerosol from ENDS was generated using a smoking machine. Various types of ENDS devices or a tank system prefilled with liquids of different flavours, nicotine carrier, variable nicotine concentrations and with modified battery output voltage were tested...
September 15, 2016: Tobacco Control
Tâm Minh Lê, Margot Brard, Sébastien Lê
Through this article, we aim to introduce Holos-a new collaborative environment that allows researchers to carry out experiments based on similarity assessments between stimuli, such as in projective-mapping and sorting tasks. An important feature of Holos is its capacity to assess real-time individual processes during the task. Within the Holos environment, researchers can design experiments on its platform, which can handle four kinds of stimuli: concepts, images, sounds, and videos. In addition, researchers can share their study resources within the scientific community, including stimuli, experimental protocols, and/or the data collected...
September 8, 2016: Behavior Research Methods
Frank Bremmer, Andre Kaminiarz, Steffen Klingenhoefer, Jan Churan
Primates perform saccadic eye movements in order to bring the image of an interesting target onto the fovea. Compared to stationary targets, saccades toward moving targets are computationally more demanding since the oculomotor system must use speed and direction information about the target as well as knowledge about its own processing latency to program an adequate, predictive saccade vector. In monkeys, different brain regions have been implicated in the control of voluntary saccades, among them the lateral intraparietal area (LIP)...
2016: Frontiers in Integrative Neuroscience
Yong Lin Kong, Maneesh K Gupta, Blake N Johnson, Michael C McAlpine
The ability to three-dimensionally interweave biological and functional materials could enable the creation of bionic devices possessing unique and compelling geometries, properties, and functionalities. Indeed, interfacing high performance active devices with biology could impact a variety of fields, including regenerative bioelectronic medicines, smart prosthetics, medical robotics, and human-machine interfaces. Biology, from the molecular scale of DNA and proteins, to the macroscopic scale of tissues and organs, is three-dimensional, often soft and stretchable, and temperature sensitive...
June 2016: Nano Today
Markus Nowak, Claudio Castellini
Simultaneous and proportional myocontrol of dexterous hand prostheses is to a large extent still an open problem. With the advent of commercially and clinically available multi-fingered hand prostheses there are now more independent degrees of freedom (DOFs) in prostheses than can be effectively controlled using surface electromyography (sEMG), the current standard human-machine interface for hand amputees. In particular, it is uncertain, whether several DOFs can be controlled simultaneously and proportionally by exclusively calibrating the intended activation of single DOFs...
2016: PloS One
Laureen Logger, Marie-Stéphanie Aschtgen, Marie Guérin, Eric Cascales, Eric Durand
The type VI secretion system (T6SS) is a multi-protein complex that catalyses toxin secretion through the bacterial cell envelope of various Gram-negative bacteria including important human pathogens. This machine uses a bacteriophage-like contractile tail to puncture the prey cell and inject armful toxins. The T6SS tail comprises an inner tube capped by the cell-puncturing spike and wrapped by the contractile sheath. This structure is built on an assembly platform, the baseplate, which is anchored to the bacterial cell envelope by the TssJLM membrane complex...
September 3, 2016: Journal of Molecular Biology
P Aricò, G Borghini, G Di Flumeri, A Colosimo, S Pozzi, F Babiloni
In the last decades, it has been a fast-growing concept in the neuroscience field. The passive brain-computer interface (p-BCI) systems allow to improve the human-machine interaction (HMI) in operational environments, by using the covert brain activity (eg, mental workload) of the operator. However, p-BCI technology could suffer from some practical issues when used outside the laboratories. In particular, one of the most important limitations is the necessity to recalibrate the p-BCI system each time before its use, to avoid a significant reduction of its reliability in the detection of the considered mental states...
2016: Progress in Brain Research
Lin Gao, Wei Cheng, Jinhua Zhang, Jue Wang
Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects...
August 2016: Review of Scientific Instruments
Lara Vilar, Israel Gómez, Javier Martínez-Vega, Pilar Echavarría, David Riaño, M Pilar Martín
The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence...
2016: PloS One
Nurhazimah Nazmi, Mohd Azizi Abdul Rahman, Shin-Ichiroh Yamamoto, Siti Anom Ahmad, Hairi Zamzuri, Saiful Amri Mazlan
In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions...
2016: Sensors
Chris Wilson Antuvan, Federica Bisio, Francesca Marini, Shih-Cheng Yen, Erik Cambria, Lorenzo Masia
BACKGROUND: Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, and follows two approaches: EMG and synergy features. More recently, muscle synergy based features are being increasingly explored, since it simplifies dimensionality of control, and are considered to be more robust to signal variations. Another important aspect in a myoelectrically controlled devices is the learning capability and speed of performance for online decoding...
2016: Journal of Neuroengineering and Rehabilitation
Meng Wang, Liping Wei
Accurate prediction of the pathogenicity of genomic variants, especially nonsynonymous single nucleotide variants (nsSNVs), is essential in biomedical research and clinical genetics. Most current prediction methods build a generic classifier for all genes. However, different genes and gene families have different features. We investigated whether gene-specific and family-specific customized classifiers could improve prediction accuracy. Customized gene-specific and family-specific attributes were selected with AIC, BIC, and LASSO, and Support Vector Machine classifiers were generated for 254 genes and 152 gene families, covering a total of 5,985 genes...
2016: Scientific Reports
Shachar Arnon, Nir Dahan, Amir Koren, Oz Radiano, Matan Ronen, Tal Yannay, Jonathan Giron, Lee Ben-Ami, Yaniv Amir, Yacov Hel-Or, Doron Friedman, Ido Bachelet
We report a new type of brain-machine interface enabling a human operator to control nanometer-size robots inside a living animal by brain activity. Recorded EEG patterns are recognized online by an algorithm, which in turn controls the state of an electromagnetic field. The field induces the local heating of billions of mechanically-actuating DNA origami robots tethered to metal nanoparticles, leading to their reversible activation and subsequent exposure of a bioactive payload. As a proof of principle we demonstrate activation of DNA robots to cause a cellular effect inside the insect Blaberus discoidalis, by a cognitively straining task...
2016: PloS One
Ana R C Donati, Solaiman Shokur, Edgard Morya, Debora S F Campos, Renan C Moioli, Claudia M Gitti, Patricia B Augusto, Sandra Tripodi, Cristhiane G Pires, Gislaine A Pereira, Fabricio L Brasil, Simone Gallo, Anthony A Lin, Angelo K Takigami, Maria A Aratanha, Sanjay Joshi, Hannes Bleuler, Gordon Cheng, Alan Rudolph, Miguel A L Nicolelis
Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3-13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback, and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects...
2016: Scientific Reports
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