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https://www.readbyqxmd.com/read/28325033/user-intent-prediction-with-a-scaled-conjugate-gradient-trained-artificial-neural-network-for-lower-limb-amputees-using-a-powered-prosthesis
#1
Richard B Woodward, John A Spanias, Levi J Hargrove
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28287078/the-design-of-and-chronic-tissue-response-to-a-composite-nerve-electrode-with-patterned-stiffness
#2
Max Freeberg, Matthew Stone, Ronald Triolo, Dustin Tyler
As neural interfaces demonstrate success in chronic applications, a novel class of reshaping electrodes with patterned regions of stiffness will enable application to a widening range of anatomical locations. Patterning stiff regions and flexible regions of the electrode enables nerve reshaping while accommodating anatomical constraints of various implant locations ranging from peripheral nerves to spinal and autonomic plexi. Introduced is a new composite electrode enabling patterning of regions of various electrode mechanical properties...
March 13, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28280321/transdiaphragmatic-pressure-and-neural-respiratory-drive-measured-during-inspiratory-muscle-training-in-stable-patients-with-chronic-obstructive-pulmonary-disease
#3
Weiliang Wu, Xianming Zhang, Lin Lin, Yonger Ou, Xiaoying Li, Lili Guan, Bingpeng Guo, Luqian Zhou, Rongchang Chen
PURPOSE: Inspiratory muscle training (IMT) is a rehabilitation therapy for stable patients with COPD. However, its therapeutic effect remains undefined due to the unclear nature of diaphragmatic mobilization during IMT. Diaphragmatic mobilization, represented by transdiaphragmatic pressure (Pdi), and neural respiratory drive, expressed as the corrected root mean square (RMS) of the diaphragmatic electromyogram (EMGdi), both provide vital information to select the proper IMT device and loads in COPD, therefore contributing to the curative effect of IMT...
2017: International Journal of Chronic Obstructive Pulmonary Disease
https://www.readbyqxmd.com/read/28278476/review-human-intracortical-recording-and-neural-decoding-for-brain-computer-interfaces
#4
David M Brandman, Sydney S Cash, Leigh R Hochberg
Brain Computer Interfaces (BCIs) use neural information recorded from the brain for voluntary control of external devices. The development of BCI systems has largely focused on improving functional independence for individuals with severe motor impairments, including providing tools for communication and mobility. In this review, we describe recent advances in intracortical BCI technology and provide potential directions for further research.
March 2, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28275048/brain-machine-interfaces-from-basic-science-to-neuroprostheses-and-neurorehabilitation
#5
REVIEW
Mikhail A Lebedev, Miguel A L Nicolelis
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity...
April 2017: Physiological Reviews
https://www.readbyqxmd.com/read/28269766/methylene-blue-tetramethylthionine-chloride-influences-the-mobility-of-adult-neural-stem-cells-a-potentially-novel-therapeutic-mechanism-of-a-therapeutic-approach-in-the-treatment-of-alzheimer-s-disease
#6
Amelie van der Ven, Julius Pape, Dirk Hermann, Robert Schloesser, Just Genius, Nadine Fischer, Rainald Mößner Mössnerf, Norbert Scherbaum, Jens Wiltfang, Dan Rujescu, Jens Benninghoff
An interest in neurogenesis in the adult human brain as a relevant and targetable process has emerged as a potential treatment option for Alzheimer's disease and other neurodegenerative conditions. The aim of this study was to investigate the effects of tetramethylthionine chloride (methylene blue, MB) on properties of adult murine neural stem cells. Based on recent clinical studies, MB has increasingly been discussed as a potential treatment for Alzheimer's disease. While no differences in the proliferative capacity were identified, a general potential of MB in modulating the migratory capacity of adult neural stem cells was indicated in a cell mobility assay...
March 2, 2017: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/28269548/ear-eeg-allows-extraction-of-neural-responses-in-challenging-listening-scenarios-a-future-technology-for-hearing-aids
#7
L Fiedler, J Obleser, T Lunner, C Graversen
Advances in brain-computer interface research have recently empowered the development of wearable sensors to record mobile electroencephalography (EEG) as an unobtrusive and easy-to-use alternative to conventional scalp EEG. One such mobile solution is to record EEG from the ear canal, which has been validated for auditory steady state responses and discrete event related potentials (ERPs). However, it is still under discussion where to place recording and reference electrodes to capture best responses to auditory stimuli...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268413/recent-machine-learning-advancements-in-sensor-based-mobility-analysis-deep-learning-for-parkinson-s-disease-assessment
#8
Bjoern M Eskofier, Sunghoon I Lee, Jean-Francois Daneault, Fatemeh N Golabchi, Gabriela Ferreira-Carvalho, Gloria Vergara-Diaz, Stefano Sapienza, Gianluca Costante, Jochen Klucken, Thomas Kautz, Paolo Bonato
The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268403/cuff-less-ppg-based-continuous-blood-pressure-monitoring-a-smartphone-based-approach
#9
Aman Gaurav, Maram Maheedhar, Vijay N Tiwari, Rangavittal Narayanan
Cuff-less estimation of systolic (SBP) and diastolic (DBP) blood pressure is an efficient approach for non-invasive and continuous monitoring of an individual's vitals. Although pulse transit time (PTT) based approaches have been successful in estimating the systolic and diastolic blood pressures to a reasonable degree of accuracy, there is still scope for improvement in terms of accuracies. Moreover, PTT approach requires data from sensors placed at two different locations along with individual calibration of physiological parameters for deriving correct estimation of systolic and diastolic blood pressure (BP) and hence is not suitable for smartphone deployment...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28266608/human-amniotic-fluid-contaminants-alter-thyroid-hormone-signalling-and-early-brain-development-in-xenopus-embryos
#10
Jean-Baptiste Fini, Bilal B Mughal, Sébastien Le Mével, Michelle Leemans, Mélodie Lettmann, Petra Spirhanzlova, Pierre Affaticati, Arnim Jenett, Barbara A Demeneix
Thyroid hormones are essential for normal brain development in vertebrates. In humans, abnormal maternal thyroid hormone levels during early pregnancy are associated with decreased offspring IQ and modified brain structure. As numerous environmental chemicals disrupt thyroid hormone signalling, we questioned whether exposure to ubiquitous chemicals affects thyroid hormone responses during early neurogenesis. We established a mixture of 15 common chemicals at concentrations reported in human amniotic fluid. An in vivo larval reporter (GFP) assay served to determine integrated thyroid hormone transcriptional responses...
March 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28263926/dopamine-depletion-impairs-gait-automaticity-by-altering-cortico-striatal-and-cerebellar-processing-in-parkinson-s-disease
#11
Moran Gilat, Peter T Bell, Kaylena A Ehgoetz Martens, Matthew J Georgiades, Julie M Hall, Courtney C Walton, Simon J G Lewis, James M Shine
Impairments in motor automaticity cause patients with Parkinson's disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinson's disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait...
March 3, 2017: NeuroImage
https://www.readbyqxmd.com/read/28253275/impact-of-frontal-white-matter-hyperintensity-on-instrumental-activities-of-daily-living-in-elderly-women-with-alzheimer-disease-and-amnestic-mild-cognitive-impairment
#12
Noriko Ogama, Takashi Sakurai, Toshiharu Nakai, Shumpei Niida, Naoki Saji, Kenji Toba, Hiroyuki Umegaki, Masafumi Kuzuya
BACKGROUND: Instrumental activities of daily living (IADL) start to decline during the progression of amnestic mild cognitive impairment (aMCI) to Alzheimer disease (AD). Cognitive and physical decline are involved in the loss of functional independence. However, little is known about AD-related neural change that leads to IADL impairment. The purpose of this study was to clarify the effects of regional white matter hyperintensity (WMH) on IADL impairment in persons with AD and aMCI. METHODS: The participants were 347 female subjects aged 65-85 years diagnosed with AD (n = 227), aMCI (n = 44) or normal cognition (n = 76)...
2017: PloS One
https://www.readbyqxmd.com/read/28247230/update-from-the-4th-edition-of-the-world-health-organization-of-head-and-neck-tumours-tumours-of-the-oral-cavity-and-mobile-tongue
#13
Susan Müller
There have been several additions and deletions in Chapter 4 on Tumours of the oral cavity and mobile tongue in the 2017 fourth edition of the World Health Organization Classification of Tumours of the Head and Neck. This chapter excludes the oropharynx, which now is a stand-alone chapter acknowledging the uniqueness of the oropharynx from the oral cavity. New entries in Chapter 4 include rhabdomyoma, haemangioma, schwannoma, neurofibroma and myofibroblastic sarcoma in the section titled Soft tissue and neural tumours...
March 2017: Head and Neck Pathology
https://www.readbyqxmd.com/read/28243199/concurrent-indicators-of-gait-velocity-and-variability-are-associated-with-25-year-cognitive-change-a-retrospective-longitudinal-investigation
#14
Stuart W S MacDonald, Sandra Hundza, Janet A Love, Correne A DeCarlo, Drew W R Halliday, Paul W H Brewster, Timothy V Lukyn, Richard Camicioli, Roger A Dixon
Background/Objectives: Physical function indicators, including gait velocity, stride time and step length, are linked to neural and cognitive function, morbidity and mortality. Whereas cross-sectional associations are well documented, far less is known about long-term patterns of cognitive change as related to objective indicators of mobility-related physical function. Methods: Using data from the Victoria Longitudinal Study, a long-term investigation of biological and health aspects of aging and cognition, we examined three aspects of cognition-physical function linkages in 121 older adults...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28241776/the-effectiveness-of-robot-assisted-gait-training-versus-conventional-therapy-on-mobility-in-severely-disabled-progressive-multiple-sclerosis-patients-ragtime-study-protocol-for-a-randomized-controlled-trial
#15
Sofia Straudi, Fabio Manfredini, Nicola Lamberti, Paolo Zamboni, Francesco Bernardi, Giovanna Marchetti, Paolo Pinton, Massimo Bonora, Paola Secchiero, Veronica Tisato, Stefano Volpato, Nino Basaglia
BACKGROUND: Gait and mobility impairments affect the quality of life (QoL) of patients with progressive multiple sclerosis (MS). Robot-assisted gait training (RAGT) is an effective rehabilitative treatment but evidence of its superiority compared to other options is lacking. Furthermore, the response to rehabilitation is multidimensional, person-specific and possibly involves functional reorganization processes. The aims of this study are: (1) to test the effectiveness on gait speed, mobility, balance, fatigue and QoL of RAGT compared to conventional therapy (CT) in progressive MS and (2) to explore changes of clinical and circulating biomarkers of neural plasticity...
February 27, 2017: Trials
https://www.readbyqxmd.com/read/28241479/unmanned-aerial-vehicle-systems-for-remote-estimation-of-flooded-areas-based-on-complex-image-processing
#16
Dan Popescu, Loretta Ichim, Florin Stoican
Floods are natural disasters which cause the most economic damage at the global level. Therefore, flood monitoring and damage estimation are very important for the population, authorities and insurance companies. The paper proposes an original solution, based on a hybrid network and complex image processing, to this problem. As first novelty, a multilevel system, with two components, terrestrial and aerial, was proposed and designed by the authors as support for image acquisition from a delimited region. The terrestrial component contains a Ground Control Station, as a coordinator at distance, which communicates via the internet with more Ground Data Terminals, as a fixed nodes network for data acquisition and communication...
February 23, 2017: Sensors
https://www.readbyqxmd.com/read/28228695/accessory-joint-and-neural-mobilizations-for-shoulder-range-of-motion-restriction-after-breast-cancer-surgery-a-pilot-randomized-clinical-trial
#17
Irene de la Rosa Díaz, María Torres Lacomba, Ester Cerezo Téllez, Cristina Díaz Del Campo Gómez-Rico, Carlos Gutiérrez Ortega
OBJECTIVE: The aim of this study was to assess the methods to conduct a substantive clinical trial to evaluate the effects of accessory joint mobilization (AJM) vs neural mobilization (NM) techniques for shoulder motion restriction after breast cancer surgery. METHODS: This pilot study was a prospective randomized and double-blind clinical trial in which 18 women who underwent unilateral breast cancer surgery and axillary lymph node dissection participated. The study was conducted at the Women's Health Research Group at the Physical Therapy Department of Alcalá University, Madrid, Spain...
March 2017: Journal of Chiropractic Medicine
https://www.readbyqxmd.com/read/28227976/user-intent-prediction-with-a-scaled-conjugate-gradient-trained-artificial-neural-network-for-lower-limb-amputees-using-a-powered-prosthesis
#18
Richard B Woodward, John A Spanias, Levi J Hargrove, Richard B Woodward, John A Spanias, Levi J Hargrove, John A Spanias, Richard B Woodward, Levi J Hargrove
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227803/ear-eeg-allows-extraction-of-neural-responses-in-challenging-listening-scenarios-a-future-technology-for-hearing-aids
#19
L Fiedler, J Obleser, T Lunner, C Graversen, L Fiedler, J Obleser, T Lunner, C Graversen, J Obleser, C Graversen, L Fiedler, T Lunner
Advances in brain-computer interface research have recently empowered the development of wearable sensors to record mobile electroencephalography (EEG) as an unobtrusive and easy-to-use alternative to conventional scalp EEG. One such mobile solution is to record EEG from the ear canal, which has been validated for auditory steady state responses and discrete event related potentials (ERPs). However, it is still under discussion where to place recording and reference electrodes to capture best responses to auditory stimuli...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226583/recent-machine-learning-advancements-in-sensor-based-mobility-analysis-deep-learning-for-parkinson-s-disease-assessment
#20
Bjoern M Eskofier, Sunghoon I Lee, Jean-Francois Daneault, Fatemeh N Golabchi, Gabriela Ferreira-Carvalho, Gloria Vergara-Diaz, Stefano Sapienza, Gianluca Costante, Jochen Klucken, Thomas Kautz, Paolo Bonato, Bjoern M Eskofier, Sunghoon I Lee, Jean-Francois Daneault, Fatemeh N Golabchi, Gabriela Ferreira-Carvalho, Gloria Vergara-Diaz, Stefano Sapienza, Gianluca Costante, Jochen Klucken, Thomas Kautz, Paolo Bonato, Fatemeh N Golabchi, Gianluca Costante, Gloria Vergara-Diaz, Paolo Bonato, Gabriela Ferreira-Carvalho, Jean-Francois Daneault, Bjoern M Eskofier, Jochen Klucken, Sunghoon I Lee, Thomas Kautz, Stefano Sapienza
The development of wearable sensors has opened the door for long-term assessment of movement disorders. However, there is still a need for developing methods suitable to monitor motor symptoms in and outside the clinic. The purpose of this paper was to investigate deep learning as a method for this monitoring. Deep learning recently broke records in speech and image classification, but it has not been fully investigated as a potential approach to analyze wearable sensor data. We collected data from ten patients with idiopathic Parkinson's disease using inertial measurement units...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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