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https://www.readbyqxmd.com/read/28436837/passive-bci-in-operational-environments-insights-recent-advances-and-future-trends
#1
Pietro Arico, Gianluca Borghini, Gianluca Di Flumeri, Nicolina Sciaraffa, Alfredo Colosimo, Fabio Babiloni
OBJECTIVE: this mini-review aims to highlight recent important aspects to consider and evaluate when passive Brain-Computer Interface (pBCI) systems would be developed and used in operational environments, and remarks future directions of their applications. METHODS: Electroencephalography (EEG)-based pBCI has become an important tool for real-time analysis of brain activity, since it could potentially provide, covertly - without distracting the user from the main task - and objectively - not affected by the subjective judgement of an observer or the user itself - information about the operator cognitive state...
April 17, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28429598/preliminary-clinical-validation-of-a-differential-correction-method-for-improving-measurement-accuracy-in-noninvasive-measurement-of-blood-glucose-using-near-infrared-spectroscopy
#2
Guang Han, Xuyao Yu, Dandan Xia, Rong Liu, Jin Liu, Kexin Xu
One of the main challenges in the noninvasive sensing of blood glucose by near-infrared (NIR) spectroscopy is the background variations from light source drift, sweating, and temperature change at the human-machine interface. In this paper, a differential correction method based on the spectra from the floating-reference position and measuring position is proposed to eliminate these spectral variations from background interferences. Its effectiveness was validated by in vitro and in vivo experiments in which the diffuse reflectance of intralipid solutions and human skin was collected at the source distances of 0...
January 1, 2017: Applied Spectroscopy
https://www.readbyqxmd.com/read/28420135/a-prosthetic-hand-body-area-controller-based-on-efficient-pattern-recognition-control-strategies
#3
Simone Benatti, Bojan Milosevic, Elisabetta Farella, Emanuele Gruppioni, Luca Benini
Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI)...
April 15, 2017: Sensors
https://www.readbyqxmd.com/read/28420129/hand-motion-detection-in-fnirs-neuroimaging-data
#4
Mohammadreza Abtahi, Amir Mohammad Amiri, Dennis Byrd, Kunal Mankodiya
As the number of people diagnosed with movement disorders is increasing, it becomes vital to design techniques that allow the better understanding of human brain in naturalistic settings. There are many brain imaging methods such as fMRI, SPECT, and MEG that provide the functional information of the brain. However, these techniques have some limitations including immobility, cost, and motion artifacts. One of the most emerging portable brain scanners available today is functional near-infrared spectroscopy (fNIRS)...
April 15, 2017: Healthcare (Basel, Switzerland)
https://www.readbyqxmd.com/read/28410558/ultrasensitive-vertical-piezotronic-transistor-based-on-zno-twin-nanoplatelet
#5
Longfei Wang, Shuhai Liu, Xiaolong Feng, Qi Xu, Suo Bai, Laipan Zhu, Libo Chen, Yong Qin, Zhong Lin Wang
High sensitivity of pressure/strain sensor is the key to accurately evaluate external mechanical stimuli and could become more important in future generations of human-machine interfaces and artificial skin. Here we report the study of a two-terminal piezotronic transistor based on ZnO twin nanoplatelets (TNPT). Owing to the mirror symmetrical structure of ZnO twin nanplatelet, compressive pressure induced positive piezoelectric polarization charges created at both metal-semiconductor interfaces can simultaneously lower the both Schottky barrier heights and thus significantly modulate the carriers transport...
April 14, 2017: ACS Nano
https://www.readbyqxmd.com/read/28389030/harnessing-prefrontal-cognitive-signals-for-brain-machine-interfaces
#6
REVIEW
Byoung-Kyong Min, Ricardo Chavarriaga, José Del R Millán
Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of human intentions. Therefore, additional sources of brain activity for controlling BMIs need to be explored. In particular, higher-order cognitive brain signals, specifically those encoding goal-directed intentions, are natural candidates for enlarging the repertoire of BMI control signals and making them more efficient and intuitive...
April 4, 2017: Trends in Biotechnology
https://www.readbyqxmd.com/read/28386448/elasticity-improves-handgrip-performance-and-user-experience-during-visuomotor-control
#7
Michael Mace, Paul Rinne, Jean-Luc Liardon, Catherine Uhomoibhi, Paul Bentley, Etienne Burdet
Passive rehabilitation devices, providing motivation and feedback, potentially offer an automated and low-cost therapy method, and can be used as simple human-machine interfaces. Here, we ask whether there is any advantage for a hand-training device to be elastic, as opposed to rigid, in terms of performance and preference. To address this question, we have developed a highly sensitive and portable digital handgrip, promoting independent and repetitive rehabilitation of grasp function based around a novel elastic force and position sensing structure...
February 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28375650/emerging-frontiers-of-neuroengineering-a-network-science-of-brain-connectivity
#8
Danielle S Bassett, Ankit N Khambhati, Scott T Grafton
Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph...
March 27, 2017: Annual Review of Biomedical Engineering
https://www.readbyqxmd.com/read/28362480/flexible-light-emission-diode-arrays-made-of-transferred-si-microwires-zno-nanofilm-with-piezo-phototronic-effect-enhanced-lighting
#9
Xiaoyi Li, Renrong Liang, Juan Tao, Zhengchun Peng, Qiming Xu, Xun Han, Xiandi Wang, Chunfeng Wang, Jing Zhu, Caofeng Pan, Zhong Lin Wang
Due to the fragility and the poor optoelectronic performances of Si, it is challenging and exciting to fabricate the Si-based flexible light-emitting diode (LED) array devices. Here, a flexible LED array device made of Si microwires-ZnO nanofilm, with the advantages of flexibility, stability, lightweight, and energy savings, is fabricated and can be used as a strain sensor to demonstrate the two-dimensional pressure distribution. Based on piezo-phototronic effect, the intensity of the flexible LED array can be increased more than 3 times (under 60 MPa compressive strains)...
April 25, 2017: ACS Nano
https://www.readbyqxmd.com/read/28361947/mapping-ecog-channel-contributions-to-trajectory-and-muscle-activity-prediction-in-human-sensorimotor-cortex
#10
Yasuhiko Nakanishi, Takufumi Yanagisawa, Duk Shin, Hiroyuki Kambara, Natsue Yoshimura, Masataka Tanaka, Ryohei Fukuma, Haruhiko Kishima, Masayuki Hirata, Yasuharu Koike
Studies on brain-machine interface techniques have shown that electrocorticography (ECoG) is an effective modality for predicting limb trajectories and muscle activity in humans. Motor control studies have also identified distributions of "extrinsic-like" and "intrinsic-like" neurons in the premotor (PM) and primary motor (M1) cortices. Here, we investigated whether trajectories and muscle activity predicted from ECoG were obtained based on signals derived from extrinsic-like or intrinsic-like neurons. Three participants carried objects of three different masses along the same counterclockwise path on a table...
March 31, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28358916/classifying-three-imaginary-states-of-the-same-upper-extremity-using-time-domain-features
#11
Mojgan Tavakolan, Zack Frehlick, Xinyi Yong, Carlo Menon
Brain-computer interface (BCI) allows collaboration between humans and machines. It translates the electrical activity of the brain to understandable commands to operate a machine or a device. In this study, we propose a method to improve the accuracy of a 3-class BCI using electroencephalographic (EEG) signals. This BCI discriminates rest against imaginary grasps and elbow movements of the same limb. This classification task is challenging because imaginary movements within the same limb have close spatial representations on the motor cortex area...
2017: PloS One
https://www.readbyqxmd.com/read/28339629/orders-on-file-but-no-labs-drawn-investigation-of-machine-and-human-errors-caused-by-an-interface-idiosyncrasy
#12
Richard Schreiber, Dean F Sittig, Joan Ash, Adam Wright
In this report, we describe 2 instances in which expert use of an electronic health record (EHR) system interfaced to an external clinical laboratory information system led to unintended consequences wherein 2 patients failed to have laboratory tests drawn in a timely manner. In both events, user actions combined with the lack of an acknowledgment message describing the order cancellation from the external clinical system were the root causes. In 1 case, rapid, near-simultaneous order entry was the culprit; in the second, astute order management by a clinician, unaware of the lack of proper 2-way interface messaging from the external clinical system, led to the confusion...
February 16, 2017: Journal of the American Medical Informatics Association: JAMIA
https://www.readbyqxmd.com/read/28325008/feasibility-of-an-ultra-low-power-digital-signal-processor-platform-as-a-basis-for-a-fully-implantable-brain-computer-interface-system
#13
Po T Wang, Keulanna Gandasetiawan, Colin M McCrimmon, Alireza Karimi-Bidhendi, Charles Y Liu, Payam Heydari, Zoran Nenadic, An H Do
A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g. electrocorticogram) and translate them into control commands for external prostheses. The feasibility of such a system was tested by implementing its benchtop analogue, centered around a commercial, ultra-low power (ULP) digital signal processor (DSP, TMS320C5517, Texas Instruments). A suite of signal processing and BCI algorithms, including (de)multiplexing, Fast Fourier Transform, power spectral density, principal component analysis, linear discriminant analysis, Bayes rule, and finite state machine was implemented and tested in the DSP...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28315750/fun-cube-based-brain-gym-cognitive-function-assessment-system
#14
Tao Zhang, Chung-Chih Lin, Tsang-Chu Yu, Jing Sun, Wen-Chuin Hsu, Alice May-Kuen Wong
The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment...
March 3, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28283691/-modulation-of-the-intestinal-microbiota-by-nutritional-interventions
#15
S Derer, H Lehnert, C Sina, A E Wagner
Humans live in symbiosis with billions of commensal bacteria. The so-called microbiota live on different biological interfaces such as the skin, the urogenital tract and the gastrointestinal tract. Commensal bacteria replace potentially pathogenic microbes, synthesize vitamins and ferment dietary fibre. An imbalance in the bacterial composition of the intestinal microbiota has been associated with various diseases including gut-associated disorders such as inflammatory bowel diseases, colorectal cancer and nonalcoholic fatty liver disease...
March 10, 2017: Der Internist
https://www.readbyqxmd.com/read/28281337/recent-advancements-in-flexible-and-stretchable-electrodes-for-electromechanical-sensors-strategies-materials-and-features
#16
Songfang Zhao, Jinhui Li, Duxia Cao, Guoping Zhang, Jia Li, Kui Li, Yang Yang, Wei Wang, Yufeng Jin, Rong Sun, Ching-Ping Wong
Stretchable and flexible sensors attached onto the surface of the human body can perceive external stimuli, thus attracting extensive attention due to their lightweight, low modulus, low cost, high flexibility, and stretchability. Recently, a myriad of efforts have been devoted to improving the performance and functionality of wearable sensors. Herein, this review focuses on recent remarkable advancements in the development of flexible and stretchable sensors. Multifunction of these wearable sensors is realized by incorporating some desired features (e...
March 30, 2017: ACS Applied Materials & Interfaces
https://www.readbyqxmd.com/read/28269380/hand-motion-recognition-based-on-forearm-deformation-measured-with-a-distance-sensor-array
#17
Sung-Gwi Cho, Masahiro Yoshikawa, Kohei Baba, Kazunori Ogawa, Jun Takamatsu, Tsukasa Ogasawara
Studies of upper limb motion analysis using surface electromyogram (sEMG) signals measured from the forearm plays an important role in various applications, such as human interfaces for controlling robotic exoskeletons, prosthetic hands, and evaluation of body functions. Though the sEMG signals have a lot of information about the activities of the muscles, the signals do not have the activities of the deep layer muscles. We focused on forearm deformation, since hand motion brings the muscles, tendons, and skeletons under the skin...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269298/skills-based-evaluation-of-alternative-input-methods-to-command-a-semi-autonomous-electric-wheelchair
#18
Mario Rojas, Pedro Ponce, Arturo Molina
This paper presents the evaluation, under standardized metrics, of alternative input methods to steer and maneuver a semi-autonomous electric wheelchair. The Human-Machine Interface (HMI), which includes a virtual joystick, head movements and speech recognition controls, was designed to facilitate mobility skills for severely disabled people. Thirteen tasks, which are common to all the wheelchair users, were attempted five times by controlling it with the virtual joystick and the hands-free interfaces in different areas for disabled and non-disabled people...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268958/reward-value-is-encoded-in-primary-somatosensory-cortex-and-can-be-decoded-from-neural-activity-during-performance-of-a-psychophysical-task
#19
David B McNiel, John S Choi, John P Hessburg, Joseph T Francis
Encoding of reward valence has been shown in various brain regions, including deep structures such as the substantia nigra as well as cortical structures such as the orbitofrontal cortex. While the correlation between these signals and reward valence have been shown in aggregated data comprised of many trials, little work has been done investigating the feasibility of decoding reward valence on a single trial basis. Towards this goal, one non-human primate (macaca radiata) was trained to grip and hold a target level of force in order to earn zero, one, two, or three juice rewards...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268892/eeg-based-single-trial-detection-of-errors-from-multiple-error-related-brain-activity
#20
Guofa Shou, Lei Ding
A key ability of the human brain is to monitor erroneous events and adjust behaviors accordingly. Electrophysiological and neuroimaging studies have demonstrated different brain activities related to errors. Meanwhile, the recognition of error-related brain activity as one aspect of performance monitoring has been reported for potential applications in clinical neuroscience and brain-machine interface, where single-trial analysis and classification would provide novel insights on dynamic brain responses to errors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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