Read by QxMD icon Read

Human machine interface

Mehmet C Kayacan, Yakup B Baykal, Tamer Karaaslan, Koray Özsoy, İlker Alaca, Burhan Duman, Yunus E Delikanlı
BACKGROUND: This study investigated the design and osseointegration process of transitive porous implants that can be used in humans and all trabecular and compact bone structure animals. The aim was to find a way of forming a strong and durable tissue bond on the bone-implant interface. METHODS: Massive and transitive porous implants were produced on a direct metal laser sintering machine, surgically implanted into the skulls of sheep and kept in place for 12 weeks...
November 13, 2017: Journal of Applied Biomaterials & Functional Materials
Vito M Manghisi, Michele Fiorentino, Michele Gattullo, Antonio Boccaccio, Vitoantonio Bevilacqua, Giuseppe L Cascella, Michele Dassisti, Antonio E Uva
This article explores what it takes to make interactive computer graphics and VR attractive as a promotional vehicle, from the points of view of tourism agencies and the tourists themselves. The authors exploited current VR and human-machine interface (HMI) technologies to develop an interactive, innovative, and attractive user experience called the Multisensory Apulia Touristic Experience (MATE). The MATE system implements a natural gesture-based interface and multisensory stimuli, including visuals, audio, smells, and climate effects...
November 2017: IEEE Computer Graphics and Applications
Wei Luo, Tongfei Wu, Biqiong Chen, Mei Liang, Huawei Zou
Highly stretchable and durable conductors are significant to the development of wearable devices, robots, human-machine interfaces and other artificial intelligence products. Although many respectable methods have been reported, it is still a challenge to fabricate stretchable conductors with a large elastic limit, high conductivity and excellent reliability in rapid, effective and economic ways. Herein, a facile method is offered to fabricate high-performance stretchable tubular conductors (TCs) based on a macro-confined structure of expanded graphite (EG) in rubber tubing by simply physical packing...
November 15, 2017: ACS Applied Materials & Interfaces
Yue Li, Shaomin Zhang, Yile Jin, Bangyu Cai, Marco Controzzi, Junming Zhu, Jianmin Zhang, Xiaoxiang Zheng
Electrocorticography (ECoG) has been demonstrated as a promising neural signal source for developing brain-machine interfaces (BMIs). However, many concerns about the disadvantages brought by large craniotomy for implanting the ECoG grid limit the clinical translation of ECoG-based BMIs. In this study, we collected clinical ECoG signals from the sensorimotor cortex of three epileptic participants when they performed hand gestures. The ECoG power spectrum in hybrid frequency bands was extracted to build a synchronous real-time BMI system...
2017: Behavioural Neurology
Junqing Zhao, Hang Guo, Yao Kun Pang, Fengben Xi, Zhi Wei Yang, Guoxu Liu, Tong Guo, Guifang Dong, Chi Zhang, Zhong Lin Wang
Flexible electronics has attracted enormous interest in wearable electronics and human-machine interfacing. Here, a flexible organic tribotronic transistor (FOTT) without a top gate electrode has been demonstrated. The FOTT is fabricated on a flexible polyethylene terephthalate film using the p-type pentacene and poly(methyl methacrylate)/Cytop composites as the conductive channel and dielectric layer, respectively. The charge carriers can be modulated by the contact electrification between the dielectric layer and a mobile triboelectric layer...
November 8, 2017: ACS Nano
Stephanie Lees, Natalie Dayan, Hubert Cecotti, Paul McCullagh, Liam Maguire, Fabien Lotte, Damien H Coyle
Rapid serial visual presentation (RSVP) combined with the detection of event related brain responses facilitates the selection of relevant information contained in a stream of images presented rapidly to a human. Event related potentials (ERPs), measured non-invasively with electroencephalography (EEG), can be associated with infrequent target stimuli(images) in groups of images, potentially providing an interface for human-machine symbiosis, where humans can interact and interface with a computer without moving and which may offer faster image sorting than scenarios where humans are expected to physically react when a target image is detected...
November 3, 2017: Journal of Neural Engineering
Steven A Wartman, C Donald Combs
Changes to the medical profession require medical education reforms that will enable physicians to more effectively enter contemporary practice. Proposals for such reforms abound. Common themes include renewed emphasis on communication, teamwork, risk-management, and patient safety. These reforms are important but insufficient. They do not adequately address the most fundamental change--the practice of medicine is rapidly transitioning from the information age to the age of artificial intelligence. Employers need physicians who: work at the top of their license, have knowledge spanning the health professions and care continuum, effectively leverage data platforms, focus on analyzing outcomes and improving performance, and communicate the meaning of the probabilities generated by massive amounts of data to patients given their unique human complexities...
November 1, 2017: Academic Medicine: Journal of the Association of American Medical Colleges
Chi-Ying Lin, Ping-Jung Hsieh
The gathering of ingredients for decoctions of traditional Chinese herbs still relies on manual dispensation, due to the irregular shape of many items and inconsistencies in weights. In this study, we developed an automatic dispensing system for Chinese herbal decoctions with the aim of reducing manpower costs and the risk of mistakes. We employed machine vision in conjunction with a robot manipulator to facilitate the grasping of ingredients. The name and formulation of the decoction are input via a human-computer interface, and the dispensing of multiple medicine packets is performed automatically...
2017: Journal of Healthcare Engineering
Francesco Bovo, Giacomo De Rossi, Francesco Visentin
This paper presents a lean approach to training in robot assisted surgery. Minimally Invasive Surgical procedures can be decomposed in a sequence of tasks, each surgical task can be further decomposed in basic gestures. Each surgical gesture seems similar to perform rather in laparoscopic than in robot assisted technique, but surgeon posture, tools dexterity, force and vision feedback are different. As a consequence, performing a robot-assisted procedure needs specific training. Currently, the most used robot in in abdominal and pelvic surgery is the da Vinci Surgical System and a different set of skills is needed to master the human-machine interface of this device...
2017: J Vis Surg
Chunya Wang, Kailun Xia, Mingchao Zhang, Muqiang Jian, Yingying Zhang
Flexible skin-mimicking electronics are highly desired for development of smart human-machine interfaces and wearable human-health monitors. Human skins are able to simultaneously detect different information, such as touch, friction, temperature, and humidity. However, due to the mutual interferences of sensors with different functions, it is still a big challenge to fabricate multifunctional electronic skins (E-skins). Herein, a combo temperature-pressure E-skin is reported through assembling a temperature sensor and a strain sensor in both of which flexible and transparent silk-nanofiber-derived carbon fiber membranes (SilkCFM) are used as the active material...
November 3, 2017: ACS Applied Materials & Interfaces
Kristofer E Bouchard, Alejandro F Bujan, Edward F Chang, Friedrich T Sommer
The concept of sparsity has proven useful to understanding elementary neural computations in sensory systems. However, the role of sparsity in motor regions is poorly understood. Here, we investigated the functional properties of sparse structure in neural activity collected with high-density electrocorticography (ECoG) from speech sensorimotor cortex (vSMC) in neurosurgical patients. Using independent components analysis (ICA), we found individual components corresponding to individual major oral articulators (i...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Yaguang Jia, Jun Xie, Guanghua Xu, Min Li, Sicong Zhang, Ailing Luo, Xingliang Han
Signal processing is one of the key points in brain computer interface (BCI) application. The common methods in BCI signal classification include canonical correlation analysis (CCA), support vector machine (SVM) and so on. However, because BCI signals are very complex and valid signals often come with confounded background noise, many current classification methods would lose meaningful information embedded in human EEGs. Otherwise, due to the huge inter-subject variability with respect to characteristics and patterns of BCI signals, there often exists large difference of classification accuracy among different subjects...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Huijuan Yang, Camilo Libedinsky, Cuntai Guan, Kai Keng Ang, Rosa Q So
The nonstationarity of neural signal is still an unresolved issue despite the rapid progress made in brain-machine interface (BMI). This paper investigates how to utilize the rich information and dynamics in multi-day data to address the variability in day-to-day signal quality and neural tuning properties. For this purpose, we propose a classifier-level fusion technique to build a robust decoding model by jointly considering the classifier outputs from multiple base-training models using multi-day data collected prior to test day...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Trieu Phat Luu, Justin A Brantley, Fangshi Zhu, Jose L Contreras-Vidal
This study investigates if the electrocortical amplitude modulations relative to the mean gait cycle are different across walking conditions (i.e., level-ground (LW), ramp ascent (RA), and stair ascent (SA)). Non-invasive electroencephalography (EEG) signals were recorded and a systematic EEG processing method was implemented to reduce artifacts. Source localization using independent component analysis and k-means clustering revealed the involvement of four clusters in the brain (Left and Right Occipital Lobe, Posterior Parietal Cortex (PPC), and Sensorimotor Area) during the walking tasks...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Han-Lin Hsieh, Yan T Wong, Bijan Pesaran, Maryam M Shanechi
Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Susan Michie, James Thomas, Marie Johnston, Pol Mac Aonghusa, John Shawe-Taylor, Michael P Kelly, Léa A Deleris, Ailbhe N Finnerty, Marta M Marques, Emma Norris, Alison O'Mara-Eves, Robert West
BACKGROUND: Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support...
October 18, 2017: Implementation Science: IS
Thomas W M Crozier, Michele Tinti, Mark Larance, Angus I Lamond, Michael A J Ferguson
A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis-generating proteomic data are provided in an open access online data visualisation environment (http://134...
October 17, 2017: Molecular & Cellular Proteomics: MCP
Chunyan Jiang, Ting Liu, Chunhua Du, Xin Huang, Mengmeng Liu, Zhenfu Zhao, Linxuan Li, Xiong Pu, Junyi Zhai, Weiguo Hu, Zhong Lin Wang
The piezotronic effect utilizes strain-induced piezoelectric polarization charges to tune the carrier transportation across the interface/junction. We fabricated a high-performance AlGaN/GaN high electron mobility transistor (HEMT), and the transport property was proven to be enhanced by applying an external stress for the first time. The enhanced source-drain current was also observed at any gate voltage and the maximum enhancement of the saturation current was up to 21% with 15 N applied stress (0.18 GPa at center) at -1 V gate voltage...
October 17, 2017: Nanotechnology
Ahmed Allam, Michael Krauthammer
Motivation: Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Results: Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks...
November 1, 2017: Bioinformatics
Sébastien Puma, Nadine Matton, Pierre-V Paubel, Éric Raufaste, Radouane El-Yagoubi
Cognitive workload is of central importance in the fields of human factors and ergonomics. A reliable measurement of cognitive workload could allow for improvements in human machine interface designs and increase safety in several domains. At present, numerous studies have used electroencephalography (EEG) to assess cognitive workload, reporting the rise in cognitive workload to be associated with increases in theta band power and decreases in alpha band power. However, results have been inconsistent with some failing to reach the required level of significance...
October 7, 2017: International Journal of Psychophysiology
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"