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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/28227994/development-of-a-high-sensitivity-and-portable-cell-using-helmholtz-resonance-for-noninvasive-blood-glucose-level-measurement-based-on-photoacoustic-spectroscopy
#2
K Tachibana, K Okada, R Kobayashi, Y Ishihara, K Tachibana, K Okada, R Kobayashi, Y Ishihara, R Kobayashi, Y Ishihara, K Okada, K Tachibana
We describe the possibility of high-sensitivity noninvasive blood glucose measurement based on photoacoustic spectroscopy (PAS). The demand for noninvasive blood glucose-level measurement has increased due to the explosive increase in diabetic patients. We have developed a noninvasive blood glucose-level measurement based on PAS. The conventional method uses a straight-type resonant cell. However, the cell volume is large, which results in a low detection sensitivity and difficult portability. In this paper, a small-sized Helmholtz-type resonant cell is proposed to improve detection sensitivity and portability by reducing the cell dead volume...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227990/using-computational-phantoms-to-improve-delivery-of-tumor-treating-fields-ttfields-to-patients
#3
Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Uri Weinberg, Cornelia Wenger, Noa Urman, Hadas Sara Hershkovich, Yoram Wasserman, Anders R Korshoej, Eilon D Kirson, Dario Garcia-Carracedo, Pedro Miranda, Aafia Chaudhry, Zeev Bomzon, Yoram
This paper reviews the state-of-the-art in simulation-based studies of Tumor Treating Fields (TTFields) and highlights major aspects of TTFields in which simulation-based studies could affect clinical outcomes. A major challenge is how to simulate multiple scenarios rapidly for TTFields delivery. Overcoming this challenge will enable a better understanding of how TTFields distribution is correlated with disease progression, leading to better transducer array designs and field optimization procedures, ultimately improving patient outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227988/liver-segmentation-using-location-and-intensity-probabilistic-atlases
#4
Negar Farzaneh, Shadrokh Samavi, S M Reza Soroushmehr, Hirenkumar Patel, Samuel Habbo-Gavin, David Paul Fessell, Kevin R Ward, Kayvan Najarian, Negar Farzaneh, Shadrokh Samavi, S M Reza Soroushmehr, Hirenkumar Patel, Samuel Habbo-Gavin, David Paul Fessell, Kevin R Ward, Kayvan Najarian, Kevin R Ward, S M Reza Soroushmehr, Hirenkumar Patel, Shadrokh Samavi, Samuel Habbo-Gavin, Kayvan Najarian, David Paul Fessell, Negar Farzaneh
In a variety of injuries and illnesses, internal organs in the abdominal and pelvic regions, in particular liver, may be compromised. In the current practice, CT scans of liver are visually inspected to investigate the integrity of the organ. However, the size and complexity of the CT images limits the reliability of visual inspection to accurately assess the health of liver. Computer-aided image analysis can create fast and quantitative assessment of liver from the CT, in particular in the environments where access to skilled radiologists may be limited...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227987/incorporating-shape-prior-into-active-contours-with-a-sparse-linear-combination-of-training-shapes-application-to-corpus-callosum-segmentation
#5
Mohammad M Farhangi, Hichem Frigui, Robert Bert, Amir A Amini, Mohammad M Farhangi, Hichem Frigui, Robert Bert, Amir A Amini, Robert Bert, Mohammad M Farhangi, Amir A Amini, Hichem Frigui
In this paper, a novel method of embedding shape information into level set image segmentation is proposed. Our method is based on inferring shape variations by a sparse linear combination of instances in the shape repository. Given a sufficient number of training shapes with variations, a new shape can be approximated by a linear span of training shapes associated with those variations. At each step of curve evolution the curve is moved to minimize Chan-Vese energy functional as well as toward the best approximation based on a linear combination of training samples...
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/28227962/personalization-of-noneeg-based-seizure-detection-systems
#11
D Cogan, M Heydarzadeh, M Nourani, D Cogan, M Heydarzadeh, M Nourani, M Heydarzadeh, D Cogan, M Nourani
Seizures affect each patient differently, so personalization is a vital part of developing a reliable nonEEG based seizure detection system. This personalization must be done while the patient is undergoing video EEG monitoring in an epilepsy monitoring unit (EMU) because seizure detection by EEG is considered to be the ground truth. We propose the use of confidence interval analysis for determining how many seizures must be captured from a patient before we can reliably personalize such a seizure detection system for him/her...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227960/automated-volumetry-for-unilateral-hippocampal-sclerosis-detection-in-patients-with-temporal-lobe-epilepsy
#12
Cristina Martins, Nadia Moreira da Silva, Guilherme Silva, Verena E Rozanski, Joao Paulo Silva Cunha, Cristina Martins, Nadia Moreira da Silva, Guilherme Silva, Verena E Rozanski, Joao Paulo Silva Cunha, Joao Paulo Silva Cunha, Guilherme Silva, Verena E Rozanski, Nadia Moreira da Silva, Cristina Martins
Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis. Manual volumetry is the traditional approach but it is time consuming and requires the physician to be familiar with neuroimaging software tools...
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
#13
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/28227956/a-wirelessly-powered-homecage-with-animal-behavior-analysis-and-closed-loop-power-control
#14
Yaoyao Jia, Zheyuan Wang, Daniel Canales, Morgan Tinkler, Chia-Chun Hsu, Teresa E Madsen, S Abdollah Mirbozorgi, Donald Rainnie, Maysam Ghovanloo, Yaoyao Jia, Zheyuan Wang, Daniel Canales, Morgan Tinkler, Chia-Chun Hsu, Teresa E Madsen, S Abdollah Mirbozorgi, Donald Rainnie, Maysam Ghovanloo, Donald Rainnie, Chia-Chun Hsu, Teresa E Madsen, Morgan Tinkler, Daniel Canales, Zheyuan Wang, S Abdollah Mirbozorgi, Maysam Ghovanloo, Yaoyao Jia
This paper presents a new EnerCage-homecage system, EnerCage-HC2, for longitudinal electrophysiology data acquisition experiments on small freely moving animal subjects, such as rodents. EnerCage-HC2 is equipped with multi-coil wireless power transmission (WPT), closed-loop power control, bidirectional data communication via Bluetooth Low Energy (BLE), and Microsoft Kinect® based animal behavior tracking and analysis. The EnerCage-HC2 achieves a homogeneous power transfer efficiency (PTE) of 14% on average, with ~42 mW power delivered to the load (PDL) at a nominal height of 7 cm by the closed-loop power control mechanism...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227952/smartstuff-a-case-study-of-a-smart-water-bottle
#15
Emil Jovanov, Vindhya R Nallathimmareddygari, Jonathan E Pryor, Emil Jovanov, Vindhya R Nallathimmareddygari, Jonathan E Pryor, Vindhya R Nallathimmareddygari, Emil Jovanov, Jonathan E Pryor
The rapid growth of Internet of Things (IoT) and miniature wearable biosensors have generated new opportunities for personalized eHealth and mHealth services. Smart objects equipped with physiological sensors can provide robust monitoring of activities of daily living and context for wearable physiological sensors. We present a case study of an intelligent water bottle that can precisely measure the amount of liquid in the bottle, monitor activity using inertial sensors, and physiological parameters using a touch and photoplethysmographic sensor...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227949/wrist-worn-heartbeat-monitoring-system-based-on-bio-impedance-analysis
#16
Jia Xu, Xiaomeng Gao, Alexander Lee, Shuhei Yamada, Ehsan Yavari, Victor Lubecke, Olga Boric-Lubecke, Jia Xu, Xiaomeng Gao, Alexander Lee, Shuhei Yamada, Ehsan Yavari, Victor Lubecke, Olga Boric-Lubecke, Olga Boric-Lubecke, Xiaomeng Gao, Shuhei Yamada, Ehsan Yavari, Jia Xu, Victor Lubecke, Alexander Lee
In this paper, a bio-impedance analysis (BIA) based wrist-worn heartbeat monitoring system is proposed. The system is able to estimate heart rate from a subject's wrist with only four electrodes. The design is achieved with a standard BIA device and off-the-shelf components for signal conditioning. The measured heartbeat-related impedance signal is compared with a reference heart rate signal obtained from piezoelectric finger pulse transducer. The BIA results agree with the reference, which validates the feasibility of the proposed system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227942/unified-phase-variables-of-relative-degree-two-for-human-locomotion
#17
Dario J Villarreal, Robert D Gregg, Dario J Villarreal, Robert D Gregg, Robert D Gregg, Dario J Villarreal
A starting point to achieve stable locomotion is synchronizing the leg joint kinematics during the gait cycle. Some biped robots parameterize a nonlinear controller (e.g., input-output feedback linearization) whose main objective is to track specific kinematic trajectories as a function of a single mechanical variable (i.e., a phase variable) in order to allow the robot to walk. A phase variable capable of parameterizing the entire gait cycle, the hip phase angle, has been used to control wearable robots and was recently shown to provide a robust representation of the phase of human gait...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227931/long-range-correlations-in-amplitude-variability-of-hf-and-lf-components-of-heart-rate-variability
#18
Yuki Miki, Yasuyuki Suzuki, Eiichi Watanabe, Junichiro Hayano, Yoshiharu Yamamoto, Taishin Nomura, Ken Kiyono, Yuki Miki, Yasuyuki Suzuki, Eiichi Watanabe, Junichiro Hayano, Yoshiharu Yamamoto, Taishin Nomura, Ken Kiyono
For the assessment of autonomic nervous system activity based on heart rate variability (HRV) analysis, characteristics of high-frequency (HF; 0.15 to 0.4 Hz) and low-frequency (LF; 0.04 to 0.15 Hz) components have been widely employed. HF and LF band powers quantified by power spectral analysis have most commonly been used in the conventional studies; the physiological significance of these measures has also been extensively studied. However, nonlinear characteristics of HF and LF components have not been well established...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227929/savitzky-golay-coupled-with-digital-bandpass-filtering-as-a-pre-processing-technique-in-the-quantitative-analysis-of-glucose-from-near-infrared-spectra
#19
Krishna Chaitanya Patchava, Osamah Alrezj, Mohammed Benaissa, Hatim Behairy, Krishna Chaitanya Patchava, Osamah Alrezj, Mohammed Benaissa, Hatim Behairy, Krishna Chaitanya Patchava, Mohammed Benaissa, Osamah Alrezj, Hatim Behairy
This paper proposes a novel pre-processing method based on combining bandpass with Savitzky-Golay filtering to further improve the prediction performance of the linear calibration models Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR) in near infrared spectroscopy. The proposed method is compared to the highly efficient RReliefF pre-processing technique for further evaluation. The developed calibration models have been validated to predict the glucose concentration from near infrared spectra of a mixture of glucose and human serum albumin in a phosphate buffer solution...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227913/online-learning-of-gait-models-for-calculation-of-gait-parameters
#20
Jamie L S Waugh, Anton Trinh, Ryan R Mohammed, William E McIlroy, Dana Kulic, Jamie L S Waugh, Anton Trinh, Ryan R Mohammed, William E McIlroy, Dana Kulic, Jamie L S Waugh, Dana Kulic, Anton Trinh, William E McIlroy, Ryan R Mohammed
This paper proposes a novel approach for gait analysis from wearable sensing, based on an adaptive periodic model of any gait signal. The proposed method learns a model of the gait cycle during online measurement, using a continuous representation that can adapt to inter and intra-personal variability by creating an individualized model. Once the algorithm has converged to the input signal, key gait events can be identified relative to the estimated gait phase; these events can then be used to calculate gait parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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