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"Signal Processing, Computer-Assisted"
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Accuracy of a novel auto-CPAP device to evaluate the residual apnea-hypopnea index in patients with obstructive sleep apnea
Background
Patients under treatment with continuous positive airway pressure (CPAP) may have residual sleep apnea (RSA).
Objective
The main objective of our study was to evaluate a novel auto-CPAP for the diagnosis of RSA.
Methods
All patients referred to the sleep laboratory to undergo CPAP polysomnography were evaluated. Patients treated with oxygen or noninvasive ventilation and split-night polysomnography (PSG), PSG with artifacts, or total sleep time less than 180 min were excluded. The PSG was manually analyzed before generating the automatic report from auto-CPAP. PSG variables (respiratory disturbance index (RDI), obstructive apnea index, hypopnea index, and central apnea index) were compared with their counterparts from auto-CPAP through Bland–Altman plots and intraclass correlation coefficient. The diagnostic accuracy of autoscoring from auto-CPAP using different cutoff points of RDI (≥5 and 10) was evaluated by the receiver operating characteristics (ROCs) curve.
Results
The study included 114 patients (24 women; mean age and BMI, 59 years old and 33 kg/m
2
; RDI and apnea/hypopnea index (AHI)-auto median, 5 and 2, respectively). The average difference between the AHI-auto and the RDI was −3.5 ± 3.9. The intraclass correlation coefficient (ICC) between the total number of central apneas, obstructive, and hypopneas between the PSG and the auto-CPAP were 0.69, 0.16, and 0.15, respectively. An AHI-auto >2 (RDI ≥ 5) or >4 (RDI ≥ 10) had an area under the ROC curve, sensitivity, specificity, positive likelihood ratio, and negative for diagnosis of residual sleep apnea of 0.84/0.89, 84/81 %, 82/91 %, 4.5/9.5, and 0.22/0.2, respectively.
Conclusions
The automatic analysis from auto-CPAP (S9 Autoset) showed a good diagnostic accuracy to identify residual sleep apnea. The absolute agreement between PSG and auto-CPAP to classify the respiratory events correctly varied from very low (obstructive apneas, hypopneas) to moderate (central apneas).
Journal Article
Data mining in biomedical imaging, signaling, and systems
\"Data mining has rapidly emerged as an enabling, robust, and scalable technique to analyze data for novel patterns, trends, anomalies, structures, and features that can be employed for a variety of biomedical and clinical domains. Approaching the techniques and challenges of image mining from a multidisciplinary perspective, this book presents data mining techniques, methodologies, algorithms, and strategies to analyze biomedical signals and images. Written by experts, the text addresses data mining paradigms for the development of biomedical systems. It also includes special coverage of knowledge discovery in mammograms and emphasizes both the diagnostic and therapeutic fields of eye imaging\"--Provided by publisher.
Book
An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information
Background
Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent.
Methods
In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7–30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine.
Results
The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets.
Conclusions
Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.
Journal Article
Opto-VLSI devices and circuits for biomedical and healthcare applications
\"The text comprehensively discusses the latest Opto-VLSI devices and circuits useful for healthcare and biomedical applications. It further emphasizes the importance of smart technologies such as artificial intelligence, machine learning, and the internet of things for the biomedical and healthcare industries\"-- Provided by publisher.
BOOK
Measurement of Pulse Wave Signals and Blood Pressure by a Plastic Optical Fiber FBG Sensor
Fiber Bragg grating (FBG) sensors fabricated in silica optical fiber (Silica-FBG) have been used to measure the strain of human arteries as pulse wave signals. A variety of vital signs including blood pressure can be derived from these signals. However, silica optical fiber presents a safety risk because it is easily fractured. In this research, an FBG sensor fabricated in plastic optical fiber (POF-FBG) was employed to resolve this problem. Pulse wave signals were measured by POF-FBG and silica-FBG sensors for four subjects. After signal processing, a calibration curve was constructed by partial least squares regression, then blood pressure was calculated from the calibration curve. As a result, the POF-FBG sensor could measure the pulse wave signals with an signal to noise (SN) ratio at least eight times higher than the silica-FBG sensor. Further, the measured signals were substantially similar to those of an acceleration plethysmograph (APG). Blood pressure is measured with low error, but the POF-FBG APG correlation is distributed from 0.54 to 0.72, which is not as high as desired. Based on these results, pulse wave signals should be measured under a wide range of reference blood pressures to confirm the reliability of blood pressure measurement uses POF-FBG sensors.
Journal Article
The Efficacy of LUCAS in Prehospital Cardiac Arrest Scenarios: A Crossover Mannequin Study
High-quality cardiopulmonary resuscitation (CPR) is critical for successful cardiac arrest outcomes. Mechanical devices may improve CPR quality. We simulated a prehospital cardiac arrest, including patient transport, and compared the performance of the LUCAS™ device, a mechanical chest compression-decompression system, to manual CPR. We hypothesized that because of the movement involved in transporting the patient, LUCAS would provide chest compressions more consistent with high-quality CPR guidelines.
We performed a crossover-controlled study in which a recording mannequin was placed on the second floor of a building. An emergency medical services (EMS) crew responded, defibrillated, and provided either manual or LUCAS CPR. The team transported the mannequin through hallways and down stairs to an ambulance and drove to the hospital with CPR in progress. Critical events were manually timed while the mannequin recorded data on compressions.
Twenty-three EMS providers participated. Median time to defibrillation was not different for LUCAS compared to manual CPR (p=0.97). LUCAS had a lower median number of compressions per minute (112/min vs. 125/min; IQR = 102-128 and 102-126 respectively; p<0.002), which was more consistent with current American Heart Association CPR guidelines, and percent adequate compression rate (71% vs. 40%; IQR = 21-93 and 12-88 respectively; p<0.002). In addition, LUCAS had a higher percent adequate depth (52% vs. 36%; IQR = 25-64 and 29-39 respectively; p<0.007) and lower percent total hands-off time (15% vs. 20%; IQR = 10-22 and 15-27 respectively; p<0.005). LUCAS performed no differently than manual CPR in median compression release depth, percent fully released compressions, median time hands off, or percent correct hand position.
In our simulation, LUCAS had a higher rate of adequate compressions and decreased total hands-off time as compared to manual CPR. Chest compression quality may be better when using a mechanical device during patient movement in prehospital cardiac arrest patient.
Journal Article
Giant room-temperature magnetoresistance in single-crystal Fe/MgO/Fe magnetic tunnel junctions
The tunnel magnetoresistance (TMR) effect in magnetic tunnel junctions (MTJs)
1
,
2
is the key to developing magnetoresistive random-access-memory (MRAM), magnetic sensors and novel programmable logic devices
3
,
4
,
5
. Conventional MTJs with an amorphous aluminium oxide tunnel barrier, which have been extensively studied for device applications, exhibit a magnetoresistance ratio up to 70% at room temperature
6
. This low magnetoresistance seriously limits the feasibility of spintronics devices. Here, we report a giant MR ratio up to 180% at room temperature in single-crystal Fe/MgO/Fe MTJs. The origin of this enormous TMR effect is coherent spin-polarized tunnelling, where the symmetry of electron wave functions plays an important role. Moreover, we observed that their tunnel magnetoresistance oscillates as a function of tunnel barrier thickness, indicating that coherency of wave functions is conserved across the tunnel barrier. The coherent TMR effect is a key to making spintronic devices with novel quantum-mechanical functions, and to developing gigabit-scale MRAM.
Journal Article
Bit storage and bit flip operations in an electromechanical oscillator
The Parametron was first proposed as a logic-processing system almost 50 years ago
1
. In this approach the two stable phases of an excited harmonic oscillator provide the basis for logic operations
2
,
3
,
4
,
5
,
6
. Computer architectures based on LC oscillators were developed for this approach, but high power consumption and difficulties with integration meant that the Parametron was rendered obsolete by the transistor. Here we propose an approach to mechanical logic based on nanoelectromechanical systems
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,
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,
9
that is a variation on the Parametron architecture and, as a first step towards a possible nanomechanical computer
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,
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,
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, we demonstrate both bit storage and bit flip operations.
Journal Article
Reproducible on–off switching of solid-state luminescence by controlling molecular packing through heat-mode interconversion
Organic luminescent solids are attracting increasing interest in various fields of application
1
,
2
,
3
. Modification or alteration of the chemical structures of their component molecules is the most common approach for tuning their luminescence properties. However, for dynamic tuning or switching of solid-state luminescence with high efficiency and reproducibility successful examples are limited
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,
4
as chemical reactions in the solid state frequently encounter insufficient conversion, one-way reactions or loss of their luminescence properties. One promising approach is to control the luminescence properties by altering the mode of solid-state molecular packing without chemical reactions. Here, we show that 2,2′:6′,2′′-terpyridine
5
, practically non-luminescent in the form of amorphous solid or needle crystal
6
, shows strong blue luminescence upon formation of a plate crystal. Efficient and reproducible on–off switching of solid-state luminescence is demonstrated by heat-mode interconversion between the plate and needle crystals. Because alteration of the mode of molecular packing does not require chemical reactions, the present findings would open the way for the development of novel organic luminescent solids that can be switched on and off by external thermal stimuli.
Journal Article