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https://www.readbyqxmd.com/read/28227999/polysilicon-based-flexible-temperature-sensor-for-high-spatial-resolution-brain-temperature-monitoring
#1
Zhizhen Wu, Chunyan Li, Jed Hartings, Raj K Narayan, Chong Ahn, Zhizhen Wu, Chunyan Li, Jed Hartings, Raj K Narayan, Chong Ahn, Zhizhen Wu, Chunyan Li, Chong Ahn, Jed Hartings, Raj K Narayan
In this paper, we present a flexible temperature sensor with ultra-small polysilicon thermistors for brain temperature monitoring. In vitro sensitivity, resolution, thermal hysteresis and long term stability tests were performed. Temperature coefficient of resistance (TCR) of -0.0031/ °C and resolution of 0.1 °C were obtained for the sensor. Thermal hysteresis for temperature range of 30~45 °C was less than 0.1 °C. With silicon nitride as the passivation layer, the temperature sensor showed a drift within 0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227996/a-novel-approach-for-chewing-detection-based-on-a-wearable-ppg-sensor
#2
Vasileios Papapanagiotou, Christos Diou, Lingchuan Zhou, Janet van den Boer, Monica Mars, Anastasios Delopoulos, Vasileios Papapanagiotou, Christos Diou, Lingchuan Zhou, Janet van den Boer, Monica Mars, Anastasios Delopoulos, Janet van den Boer, Vasileios Papapanagiotou, Lingchuan Zhou, Anastasios Delopoulos, Monica Mars, Christos Diou
Monitoring of human eating behaviour has been attracting interest over the last few years, as a means to a healthy lifestyle, but also due to its association with serious health conditions, such as eating disorders and obesity. Use of self-reports and other non-automated means of monitoring have been found to be unreliable, compared to the use of wearable sensors. Various modalities have been reported, such as acoustic signal from ear-worn microphones, or signal from wearable strain sensors. In this work, we introduce a new sensor for the task of chewing detection, based on a novel photoplethysmography (PPG) sensor placed on the outer earlobe to perform the task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227995/comparison-of-pulse-wave-velocity-derived-from-accelerometer-and-reflective-photo-plethysmography-signals-placed-at-the-carotid-and-femoral-artery
#3
Jens Muehlsteff, Erik Bresch, Lars Schmitt, Jos Gelissen, Peter Bingley, Jens Muehlsteff, Erik Bresch, Lars Schmitt, Jos Gelissen, Peter Bingley, Jos Gelissen, Peter Bingley, Lars Schmitt, Jens Muehlsteff, Erik Bresch
Carotid - femoral pulse wave velocity is an established measure to assess cardiovascular risk and an interesting surrogate parameter towards non-invasive continuous blood pressure inference. Due to progress in sensing technologies for wearable wrist worn sensors, there are low cost sensor combinations of photo-plethysmography and high fidelity accelerometers available offering access to pulse information from larger arteries complemented by blood volume changes in the superficial tissue. In this work we compare pulse wave velocities derived from accelerometer and reflective photo-plethysmography signals placed at the carotid and femoral artery...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227982/analysis-of-the-sleep-eeg-in-the-complexity-domain
#4
Sara Mariani, Ana F T Borges, Teresa Henriques, Robert J Thomas, Samuel J Leistedt, Paul Linkowski, Jean-Pol Lanquart, Ary L Goldberger, Madalena D Costa, Sara Mariani, Ana F T Borges, Teresa Henriques, Robert J Thomas, Samuel J Leistedt, Paul Linkowski, Jean-Pol Lanquart, Ary L Goldberger, Madalena D Costa, Teresa Henriques, Robert J Thomas, Madalena D Costa, Samuel J Leistedt, Paul Linkowski, Ary L Goldberger, Jean-Pol Lanquart, Sara Mariani, Ana F T Borges
Conventional sleep analysis relies primarily on electroencephalogram (EEG) waveform features assessed in concert with eye movements, respiration and muscle tone. We explore a complementary "complexity domain" approach based on multiscale entropy (MSE) analysis of EEG signals and discuss its relationships to standard sleep analysis and to that based on electrocardiogram (ECG)-derived cardiopulmonary coupling (CPC). We observe a progressive decrease in complexity associated with decreased arousability, as measured by both conventional sleep scoring and CPC analysis...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227981/assessment-of-sedation-analgesia-by-means-of-poincare%C3%AC-analysis-of-the-electroencephalogram
#5
Jose D Bolanos, Montserrat Vallverdu, Pere Caminal, Daniel F Valencia, Xavi Borrat, Pedro L Gambus, Jose F Valencia, Jose D Bolanos, Montserrat Vallverdu, Pere Caminal, Daniel F Valencia, Xavi Borrat, Pedro L Gambus, Jose F Valencia, Jose D Bolanos, Xavi Borrat, Jose F Valencia, Montserrat Vallverdu, Pere Caminal, Pedro L Gambus, Daniel F Valencia
Monitoring the levels of sedation-analgesia may be helpful for managing patient stress on minimally invasive medical procedures. Monitors based on EEG analysis and designed to assess general anesthesia cannot distinguish reliably between a light and deep sedation. In this work, the Poincaré plot is used as a nonlinear technique applied to EEG signals in order to characterize the levels of sedation-analgesia, according to observed categorical responses that were evaluated by means of Ramsay Sedation Scale (RSS)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227980/motor-imagery-based-brain-computer-interface-using-transform-domain-features
#6
Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Ahmed M Elbaz, Ahmed T Ahmed, Ayman M Mohamed, Mohamed A Oransa, Khaled S Sayed, Ayman M Eldeib, Mohamed A Oransa, Khaled S Sayed, Ayman M Mohamed, Ahmed T Ahmed, Ahmed M Elbaz, Ayman M Eldeib
Brain Computer Interface (BCI) is a channel of communication between the human brain and an external device through brain electrical activity. In this paper, we extracted different features to boost the classification accuracy as well as the mutual information of BCI systems. The extracted features include the magnitude of the discrete Fourier transform and the wavelet coefficients for the EEG signals in addition to distance series values and invariant moments calculated for the reconstructed phase space of the EEG measurements...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227979/dispersion-entropy-for-the-analysis-of-resting-state-meg-regularity-in-alzheimer-s-disease
#7
Hamed Azami, Mostafa Rostaghi, Alberto Fernandez, Javier Escudero, Hamed Azami, Mostafa Rostaghi, Alberto Fernandez, Javier Escudero, Alberto Fernandez, Javier Escudero, Mostafa Rostaghi, Hamed Azami
Alzheimer's disease (AD) is a progressive degenerative brain disorder affecting memory, thinking, behaviour and emotion. It is the most common form of dementia and a big social problem in western societies. The analysis of brain activity may help to diagnose this disease. Changes in entropy methods have been reported useful in research studies to characterize AD. We have recently proposed dispersion entropy (DisEn) as a very fast and powerful tool to quantify the irregularity of time series. The aim of this paper is to evaluate the ability of DisEn, in comparison with fuzzy entropy (FuzEn), sample entropy (SampEn), and permutation entropy (PerEn), to discriminate 36 AD patients from 26 elderly control subjects using resting-state magnetoencephalogram (MEG) signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227977/surrogate-analysis-of-fractal-dimensions-from-semg-sensor-array-as-a-predictor-of-chronic-low-back-pain
#8
Manouane Caza-Szoka, Daniel Massicotte, Francois Nougarou, Martin Descarreaux, Manouane Caza-Szoka, Daniel Massicotte, Francois Nougarou, Martin Descarreaux, Manouane Caza-Szoka, Daniel Massicotte, Martin Descarreaux, Francois Nougarou
In this paper, a method based on nonlinear analysis of sEMG sensor array signals (2 arrays of 5×13 sensors) to detect chronic low back pain is presented. The use of an FFT based surrogate analysis method isolates the nonlinear structure of the signals from the effect of the power spectrum. The fractal dimension is used for the nonlinear characteristic. From the sensor arrays, a certain number of channels which exhibits the most nonlinearity for a subject are kept as input of a small neural network. A leave-one-out type cross-validation method shows a success rate of 80%...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227975/an-adaptive-deep-learning-approach-for-ppg-based-identification
#9
V Jindal, J Birjandtalab, M Baran Pouyan, M Nourani, V Jindal, J Birjandtalab, M Baran Pouyan, M Nourani, V Jindal, M Baran Pouyan, J Birjandtalab, M Nourani
Wearable biosensors have become increasingly popular in healthcare due to their capabilities for low cost and long term biosignal monitoring. This paper presents a novel two-stage technique to offer biometric identification using these biosensors through Deep Belief Networks and Restricted Boltzman Machines. Our identification approach improves robustness in current monitoring procedures within clinical, e-health and fitness environments using Photoplethysmography (PPG) signals through deep learning classification models...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227974/heart-rate-variability-as-a-biomarker-for-sedation-depth-estimation-in-icu-patients
#10
Sunil B Nagaraj, Sowmya M Ramaswamy, Siddharth Biswal, Emily J Boyle, David W Zhou, Lauren M Mcclain, Eric S Rosenthal, Patrick L Purdon, M Brandon Westover, Sunil B Nagaraj, Sowmya M Ramaswamy, Siddharth Biswal, Emily J Boyle, David W Zhou, Lauren M Mcclain, Eric S Rosenthal, Patrick L Purdon, M Brandon Westover, M Brandon Westover, Sunil B Nagaraj, Siddharth Biswal, Sowmya M Ramaswamy, Lauren M Mcclain, David W Zhou, Emily J Boyle, Patrick L Purdon, Eric S Rosenthal
An automated patient-specific system to classify the level of sedation in ICU patients using heart rate variability signal is presented in this paper. ECG from 70 mechanically ventilated adult patients with administered sedatives in an ICU setting were used to develop a support vector machine based system for sedation depth monitoring using several heart rate variability measures. A leave-one-subject-out cross validation was used for classifier training and performance evaluations. The proposed patient-specific system provided a sensitivity, specificity and an AUC of 64%, 84...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227972/support-vector-machine-classification-of-parkinson-s-disease-and-essential-tremor-subjects-based-on-temporal-fluctuation
#11
Decho Surangsrirat, Chusak Thanawattano, Ronachai Pongthornseri, Songphon Dumnin, Chanawat Anan, Roongroj Bhidayasiri, Decho Surangsrirat, Chusak Thanawattano, Ronachai Pongthornseri, Songphon Dumnin, Chanawat Anan, Roongroj Bhidayasiri, Ronachai Pongthornseri, Roongroj Bhidayasiri, Songphon Dumnin, Chanawat Anan, Chusak Thanawattano, Decho Surangsrirat
Tremor is a common symptom shared in both Parkinson's disease (PD) and Essential tremor (ET) subjects. The differential diagnosis of PD and ET tremor is important since the realization of treatment depends on specific medication. A novel feature is developed based on a hypothesis that tremor of PD subject has a larger fluctuation during resting than action task. Tremor signal is collected using a triaxial gyroscope sensor attached to subject's finger during kinetic and resting task. The angular velocity signal is analyzed by transforming a one-dimensional to two-dimensional signal using a relation of signal and its delay versions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227971/a-feature-exploration-methodology-for-learning-based-cuffless-blood-pressure-measurement-using-photoplethysmography
#12
Kefeng Duan, Zhiliang Qian, Mohamed Atef, Guoxing Wang, Kefeng Duan, Zhiliang Qian, Mohamed Atef, Guoxing Wang, Zhiliang Qian, Kefeng Duan, Guoxing Wang, Mohamed Atef
In this work, we propose a feature exploration method for learning-based cuffless blood pressure measurement. More specifically, to efficiently explore a large feature space from the photoplethysmography signal, we have applied several analytical techniques, including random error elimination, adaptive outlier removal, maximum information coefficient and Pearson's correlation coefficient based feature assessment methods. We evaluate fifty-seven possible feature candidates and propose three separate feature sets with each containing eleven features to predict the systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP), respectively...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227968/limb-position-robust-classification-of-myoelectric-signals-for-prosthesis-control-using-sparse-representations
#13
Joseph L Betthauser, Christopher L Hunt, Luke E Osborn, Rahul R Kaliki, Nitish V Thakor, Joseph L Betthauser, Christopher L Hunt, Luke E Osborn, Rahul R Kaliki, Nitish V Thakor, Luke E Osborn, Christopher L Hunt, Nitish V Thakor, Rahul R Kaliki, Joseph L Betthauser
The fundamental objective in non-invasive myoelectric prosthesis control is to determine the user's intended movements from corresponding skin-surface recorded electromyographic (sEMG) activation signals as quickly and accurately as possible. Linear Discriminant Analysis (LDA) has emerged as the de facto standard for real-time movement classification due to its ease of use, calculation speed, and remarkable classification accuracy under controlled training conditions. However, performance of cluster-based methods like LDA for sEMG pattern recognition degrades significantly when real-world testing conditions do not resemble the trained conditions, limiting the utility of myoelectrically controlled prosthesis devices...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227967/a-stimulation-driven-exoskeleton-for-walking-after-paraplegia
#14
Sarah R Chang, Mark J Nandor, Lu Li, Kevin M Foglyano, John R Schnellenberger, Rudi Kobetic, Roger D Quinn, Ronald J Triolo, Sarah R Chang, Mark J Nandor, Lu Li, Kevin M Foglyano, John R Schnellenberger, Rudi Kobetic, Roger D Quinn, Ronald J Triolo, Mark J Nandor, Rudi Kobetic, Roger D Quinn, John R Schnellenberger, Sarah R Chang, Kevin M Foglyano, Lu Li, Ronald J Triolo
An untethered version of a stimulation-driven exoskeleton was evaluated for its ability to restore walking after paralysis from spinal cord injury. The hybrid neuroprosthesis (HNP) combined a passive variable-constraint exoskeleton for stability and support with functional neuromuscular stimulation (FNS) to contract the paralyzed muscles to drive limb movement. This self-contained HNP was operated by an onboard controller that sampled sensor signals, generated appropriate commands to both the exoskeletal constraints and integrated stimulator, and transmitted data wirelessly via Bluetooth to an off-board computer for real-time monitoring and recording for offline analysis...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227965/multiscale-brain-machine-interface-decoders
#15
Han-Lin Hsieh, Maryam M Shanechi, Han-Lin Hsieh, Maryam M Shanechi, Han-Lin Hsieh, Maryam M Shanechi
Brain-machine interfaces (BMI) have vastly used a single scale of neural activity, e.g., spikes or electrocorticography (ECoG), as their control signal. New technology allows for simultaneous recording of multiple scales of neural activity, from spikes to local field potentials (LFP) and ECoG. These advances introduce the new challenge of modeling and decoding multiple scales of neural activity jointly. Such multi-scale decoding is challenging for two reasons. First, spikes are discrete-valued and ECoG/LFP are continuous-valued, resulting in fundamental differences in statistical characteristics...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227963/predicting-seizures-from-local-field-potentials-recorded-via-intracortical-microelectrode-arrays
#16
Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg
The need for new therapeutic interventions to treat pharmacologically resistant focal epileptic seizures has led recently to the development of closed-loop systems for seizure control. Once a seizure is predicted/detected by the system, electrical stimulation is delivered to prevent seizure initiation or spread. So far, seizure prediction/detection has been limited to tracking non-invasive electroencephalogram (EEG) or intracranial EEG (iEEG) signals. Here, we examine seizure prediction based on local field potentials (LFPs) from a small neocortical patch recorded via a 10×10 microelectrode array implanted in a patient with focal seizures...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227959/localizing-seizure-onset-zone-by-convolutional-transfer-entropy-from-ieeg
#17
Kang Lin, Yueming Wang, Kedi Xu, Junming Zhu, Jianmin Zhang, Xiaoxiang Zheng, Kang Lin, Yueming Wang, Kedi Xu, Junming Zhu, Jianmin Zhang, Xiaoxiang Zheng, Xiaoxiang Zheng, Junming Zhu, Yueming Wang, Kedi Xu, Kang Lin, Jianmin Zhang
Automatic localization of the seizure onset zone (SOZ) is able to output an objective result and help clinical doctors greatly in epilepsy therapy. Transfer entropy is one of the most frequently used measures based on information theory to localize the SOZ. However, if only using transfer entropy to localize the SOZ, different results can be obtained during different periods, thus humans still need to identify which one is most reasonable. This paper proposes a new method to output only a few (e.g. 1 or 2) results along a long time slot...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227958/design-considerations-for-neural-amplifiers
#18
Jeremy Holleman, Jeremy Holleman, Jeremy Holleman
The initial amplification stage is a critical element of a neural signal acquisition system, and the design of low-noise, low-power amplifiers has received a great deal of attention in recent publications. In this paper we discuss practical considerations for the design of amplifiers intended for neural interfaces. Noise is a major issue due to the low amplitude of neural signals. Practical system deployments also require adequate rejection of common-mode interference, such as that due to line power noise or muscle artifacts, and supply noise...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227954/a-short-impulse-uwb-bpsk-transmitter-for-large-scale-neural-recording-implants
#19
M Rezaei, H Bahrami, A Mirbozorgi, Leslie A Rusch, B Gosselin, M Rezaei, H Bahrami, A Mirbozorgi, Leslie A Rusch, B Gosselin, M Rezaei, Leslie A Rusch, H Bahrami, B Gosselin, A Mirbozorgi
In this paper, a short-impulse ultra-wide band (UWB) transmitter is introduced to enable large-scale neural recordings within miniature brain implants including thousands of channels. The proposed impulse radio UWB transmitter uses a BPSK modulation scheme, the carrier signal of which uses only two delayed impulses to encode the transmitted signal. The proposed UWB transmitter has been implemented into a CMOS 180 nm technology. It occupies 300 μm × 230 μm, and consumes only 6.7 pJ/bit from a 1.8-V supply...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227951/smartsock-a-wearable-platform-for-context-aware-assessment-of-ankle-edema
#20
Ramin Fallahzadeh, Mahdi Pedram, Hassan Ghasemzadeh, Ramin Fallahzadeh, Mahdi Pedram, Hassan Ghasemzadeh
Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment are conducted during clinical visits. In-clinic assessments, in addition to being burdensome and expensive, are sometimes not reliable and neglect important contextual factors such as patient's physical activity level and body posture...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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