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1.
Accid Anal Prev ; 133: 105296, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31563015

RESUMO

Risky driving states such as aggressive driving and unstable driving are the cause of many traffic accidents. Many studies have used either driving data or physiological data such as electroencephalography (EEG) to estimate and monitor driving states. However, few studies made comparison among those driving-feature-based, EEG-feature-based and hybrid-feature-based (combination of driving features and EEG features) models. Further, limited types of EEG features have been extracted and investigated in the existing studies. To fill these research gaps aforementioned, this study adopts two EEG analysis techniques (i.e., independent component analysis and brain source localization), two signal processing methods (i.e., power spectrum analysis and wavelets analysis) to extract twelve kinds of EEG features for the short-term driving state prediction. The prediction performance of driving features, EEG features and hybrid features of them was evaluated and compared. The results indicated that EEG-based model has better performance than driving-data-based model (i.e., 83.84% versus 71.59%) and the integrated model of driving features and the full brain regions features extracted by wavelet analysis outperforms other types of features with the highest accuracy of 86.27%.


Assuntos
Direção Agressiva/psicologia , Encéfalo/fisiologia , Eletroencefalografia/métodos , Processamento de Sinais Assistido por Computador/instrumentação , Adulto , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Análise Espectral , Análise de Ondaletas
2.
IEEE J Biomed Health Inform ; 23(6): 2276-2285, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31478880

RESUMO

Mental illnesses are vast and cause a lot of individual and social discomfort, with significant healthcare costs associated in terms of diagnosis and treatment. They can be triggered by a number of factors including stress, fatigue or anxiety. The associated physiological, cardiac and autonomic changes can be assessed, centrally, through brain imaging or, peripherally, by other signal recording modalities. With recent advances in wearable devices, these parameters can now be assessed in natural living conditions as associated mood disorders such as obsessive/compulsive behavior or depression are difficult to be examined in controlled settings. In this paper, we present a low-powered and flexible device with electrocardiogram (ECG), galvanic skin response (GSR), temperature and bio-motion detection channels, with signal accuracies of 62 µV for ECG, 6.6 kΩ for GSR, 0.13 °C for temperature and 0.04 g for acceleration. Potential applications include mental health assessment of patients during daily activities at home and/or work through non-continuous and multimodal sensing as demonstrated in this paper during exercise, rest and mental activities performed by healthy individuals only, achieving an overall accuracy of 89% in the classification of the different tasks executed by volunteers.


Assuntos
Resposta Galvânica da Pele/fisiologia , Frequência Cardíaca/fisiologia , Transtornos Mentais , Monitorização Fisiológica/instrumentação , Dispositivos Eletrônicos Vestíveis , Adulto , Algoritmos , Eletrocardiografia/instrumentação , Desenho de Equipamento , Humanos , Masculino , Transtornos Mentais/diagnóstico , Transtornos Mentais/fisiopatologia , Transtornos Mentais/terapia , Monitorização Fisiológica/métodos , Movimento/fisiologia , Processamento de Sinais Assistido por Computador/instrumentação , Termometria/instrumentação
3.
Sensors (Basel) ; 19(16)2019 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-31395828

RESUMO

The objective of our project is to develop an automatic survey system for road condition monitoring using smartphone devices. One of the main tasks of our project is the classification of paved and unpaved roads. Assuming recordings will be archived by using various types of vehicle suspension system and speeds in practice, hence, we use the multiple sensors found in smartphones and state-of-the-art machine learning techniques for signal processing. Despite usually not being paid much attention, the results of the classification are dependent on the feature extraction step. Therefore, we have to carefully choose not only the classification method but also the feature extraction method and their parameters. Simple statistics-based features are most commonly used to extract road surface information from acceleration data. In this study, we evaluated the mel-frequency cepstral coefficient (MFCC) and perceptual linear prediction coefficients (PLP) as a feature extraction step to improve the accuracy for paved and unpaved road classification. Although both MFCC and PLP have been developed in the human speech recognition field, we found that modified MFCC and PLP can be used to improve the commonly used statistical method.


Assuntos
Veículos Automotores , Processamento de Sinais Assistido por Computador , Aprendizado de Máquina , Processamento de Sinais Assistido por Computador/instrumentação , Smartphone
4.
Sensors (Basel) ; 19(13)2019 Jun 28.
Artigo em Inglês | MEDLINE | ID: mdl-31261726

RESUMO

This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor is a non-invasive technique. Recently, many hardware structures, signal processing approaches, and integrated systems have been introduced by researchers in this field. The purpose is to enhance the accuracy of vital signs' detection and location detection and reduce energy consumption. This work concentrates on the representative research on sensing systems that can find alive people under rubble when an earthquake or other disasters occur. In this paper, various operating principles and system architectures for finding survivors using the microwave radar sensors are reviewed. A comparison between these systems is also discussed.


Assuntos
Técnicas Biossensoriais , Desastres , Processamento de Sinais Assistido por Computador/instrumentação , Algoritmos , Frequência Cardíaca/fisiologia , Humanos , Radar , Taxa Respiratória/fisiologia
5.
Tomography ; 5(2): 248-259, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31245546

RESUMO

Matrix gradient coils with up to 84 coil elements were recently introduced for magnetic resonance imaging. Ideally, each element is driven by a dedicated amplifier, which may be technically and financially infeasible. Instead, several elements can be connected in series (called a "cluster") and driven by a single amplifier. In previous works, a set of clusters, called a "configuration," was sought to approximate a target field shape. Because a magnetic resonance pulse sequence requires several distinct field shapes, a mechanism to switch between configurations is needed. This can be achieved by a hypothetical switching circuit connecting all terminals of all elements with each other and with the amplifiers. For a predefined set of configurations, a switching circuit can be designed to require only a limited amount of switches. Here we introduce an algorithm to minimize the number of switches without affecting the ability of the configurations to accurately create the desired fields. The problem is modeled using graph theory and split into 2 sequential combinatorial optimization problems that are solved using simulated annealing. For the investigated cases, the results show that compared to unoptimized switching circuits, the reduction of switches in optimized circuits ranges from 8% to up to 44% (average of 31%). This substantial reduction is achieved without impeding circuit functionality. This study shows how technical effort associated with implementation and operation of a matrix gradient coil is related to different hardware setups and how to reduce this effort.


Assuntos
Amplificadores Eletrônicos , Imagem por Ressonância Magnética/instrumentação , Processamento de Sinais Assistido por Computador/instrumentação , Algoritmos , Desenho de Equipamento , Imagem por Ressonância Magnética/métodos
6.
Sensors (Basel) ; 19(13)2019 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-31248022

RESUMO

Photoplethysmography (PPG) is a commonly used in determining heart rate and oxygen saturation (SpO2). However, PPG measurements and its accuracy are heavily affected by the measurement procedure and environmental factors such as light, temperature, and medium. In this paper, we analyzed the effects of different mediums (water vs. air) and temperature on the PPG signal quality and heart rate estimation. To evaluate the accuracy, we compared our measurement output with a gold-standard PPG device (NeXus-10 MKII). The experimental results show that the average PPG signal amplitude values of the underwater environment decreased considerably (22% decrease) compared to PPG signals of dry environments, and the heart rate measurement deviated 7% (5 beats per minute on average. The experimental results also show that the signal to noise ratio (SNR) and signal amplitude decrease as temperature decreases. Paired t-test which compares amplitude and heart rate values between the underwater and dry environments was performed and the test results show statistically significant differences for both amplitude and heart rate values (p < 0.05). Moreover, experimental results indicate that decreasing the temperature from 45 °C to 5 °C or changing the medium from air to water decreases PPG signal quality, (e.g., PPG signal amplitude decreases from 0.560 to 0.112). The heart rate is estimated within 5.06 bpm deviation at 18 °C in underwater environment, while estimation accuracy decreases as temperature goes down.


Assuntos
Frequência Cardíaca/fisiologia , Monitorização Fisiológica , Fotopletismografia/métodos , Smartphone , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Feminino , Voluntários Saudáveis , Humanos , Masculino , Pessoa de Meia-Idade , Processamento de Sinais Assistido por Computador/instrumentação , Razão Sinal-Ruído
7.
Adv Neurobiol ; 22: 233-250, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31073939

RESUMO

The recent years have seen unprecedented growth in the manufacturing of neurotechnological tools. The latest technological advancements presented the neuroscientific community with neuronal probes containing thousands of recording sites. These next-generation probes are capable of simultaneously recording neuronal signals from a large number of channels. Numerically, a simple 128-channel neuronal data acquisition system equipped with a 16 bits A/D converter digitizing the acquired analog waveforms at a sampling frequency of 20 kHz will generate approximately 17 GB uncompressed data per hour. Today's biggest challenge is to mine this staggering amount of data and find useful information which can later be used in decoding brain functions, diagnosing diseases, and devising treatments. To this goal, many automated processing and analysis tools have been developed and reported in the literature. A good amount of them are also available as open source for others to adapt them to individual needs. Focusing on extracellularly recorded neuronal signals in vitro, this chapter provides an overview of the popular open-source tools applicable on these signals for spike trains and local field potentials analysis, and spike sorting. Towards the end, several future research directions have also been outlined.


Assuntos
Potenciais de Ação , Eletrofisiologia/métodos , Espaço Extracelular/metabolismo , Técnicas In Vitro , Neurônios/citologia , Neurônios/metabolismo , Processamento de Sinais Assistido por Computador , Humanos , Processamento de Sinais Assistido por Computador/instrumentação
8.
Comput Intell Neurosci ; 2019: 8613639, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30949201

RESUMO

A multiuser detection (MUD) algorithm based on deep learning network is proposed for the satellite mobile communication system. Due to relative motion between the satellite and users, multiple access interference (MUI) introduced by multipath fading channel reduces system performance. The proposed MUD algorithm based on deep learning network firstly establishes the CINR optimal loss function according to the multiuser access mode and then obtains the best multiuser detection weight through the steepest gradient iteration. Multilayer nonlinear learning obtains interference cancellation sharing weights to achieve maximum signal-to-noise ratio through gradient iteration, which is superior than the traditional serial interference cancellation algorithm and parallel interference cancellation algorithm. Then, the weights with multiuser detection through multilayer network forward learning iteration are obtained with traditional multiuser detecting quality characteristics. The proposed multiuser access detection based on deep learning network algorithm improves the MUD accuracy and reduces the number of traditional multiusers. The performance of the satellite multifading uplink system shows that the proposed deep learning network can provide high precision and better iteration times.


Assuntos
Algoritmos , Redes de Comunicação de Computadores , Aprendizado Profundo , Comunicações Via Satélite , Movimento (Física) , Processamento de Sinais Assistido por Computador/instrumentação , Razão Sinal-Ruído
9.
J Appl Clin Med Phys ; 20(6): 134-140, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31002482

RESUMO

PURPOSE: It is unclear if a 3D transducer with the special design of mechanical swing or 2D array could provide acceptable 2D grayscale image quality for the general diagnosis purpose. The aim of this study is to compare the 2D image quality of a 3D intracavitary transducer with a conventional 2D intracavitary transducer using clinically relevant phantom experiments. METHODS: All measurements were performed on a GE Logiq E9 scanner with both a 2D (IC5-9-D) and a 3D (RIC5-9-D) transducer used in 2D mode. Selection of phantom targets and acquisition parameters were determined from analysis of 33 clinical pelvic exams. Depth of penetration (DOP), contrast response, contrast of anechoic cylinders (diameter: 6.7 mm) at 1.5 and 4.5 cm depths in transverse planes, and in-plane resolution represented by full-width half-maximum of pin targets at multiple depths were measured with transmit frequencies of 7 and 8 MHz. Spherical signal-noise-ratio (SNR) (diameter: 4 and 2 mm) at multiple depths were measured at 8 MHz. RESULTS: RIC5-9-D demonstrated <8% decrease in DOP for both transmit frequencies (7 MHz: 69.7 ± 8.2 mm; 8 MHz: 64.3 ± 7.8 mm) compared with those from IC5-9-D (7 MHz: 73.9 ± 4.4 mm; 8 MHz: 69.4 ± 7.8 mm). A decreased anechoic contrast was observed with a 4.5 cm depth for RIC5-9-D (7 MHz: 23.2 ± 1.8 dB, P > 0.05; 8 MHz: 17.7 ± 0.9 dB, P < 0.01) compared with IC5-9-D (7 MHz: 25.9 ± 1.2 dB; 8 MHz: 21.5 ± 0.8 dB). The contrast response and spatial resolution performance were comparable between the two transducers. RIC5-9-D showed comparable SNR of anechoic spheres compared to IC5-9-D. CONCLUSIONS: 2D images from a 3D probe exhibited comparable overall image quality for routine clinical pelvic imaging.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Pelve/diagnóstico por imagem , Imagens de Fantasmas , Processamento de Sinais Assistido por Computador/instrumentação , Transdutores , Ultrassonografia/instrumentação , Desenho de Equipamento , Humanos , Razão Sinal-Ruído
10.
Sensors (Basel) ; 19(7)2019 Apr 11.
Artigo em Inglês | MEDLINE | ID: mdl-30978993

RESUMO

We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation processing. This system can handle 2016 cross-correlations at the sample frequency of 1GHz, and its power consumption is 48.75 W. The data readout interface makes it possible to read earlier data while simultaneously performing the next correlation when imaging at video rate. The longest integration time is up to 68.7 s, which can satisfy the requirements of video rate imaging and system calibration. The measured crosstalk between neighboring channels is less than 0.068%, and the stability is longer than 10 s. A correlation efficiency greater than 96% is achieved for input signal levels greater than -25 dBm.


Assuntos
Conversão Análogo-Digital , Violência com Arma de Fogo/prevenção & controle , Corpo Humano , Interferometria/métodos , Humanos , Aumento da Imagem/métodos , Interpretação de Imagem Assistida por Computador/métodos , Modelos Teóricos , Imagens de Fantasmas , Medidas de Segurança/tendências , Processamento de Sinais Assistido por Computador/instrumentação
12.
PLoS One ; 14(3): e0213235, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30840694

RESUMO

BACKGROUND: The aim of this study was to noninvasively measure regional contributions of vasculature in the human body using magnetohydrodynamic voltages (VMHD) obtained from electrocardiogram (ECG) recordings performed inside MRI's static magnetic field (B0). Integrating the regional VMHD over the Swave-Twave segment of the cardiac cycle (Vsegment) provides a non-invasive method for measuring regional blood volumes, which can be rapidly obtained during MRI without incurring additional cost. METHODS: VMHD was extracted from 12-lead ECG traces acquired during gradual introduction into a 3T MRI. Regional contributions were computed utilizing weights based on B0's strength at specified distances from isocenter. Vsegment mapping was performed in six subjects and validated against MR angiograms (MRA). RESULTS: Fluctuations in Vsegment, which presented as positive trace deflections, were found to be associated with aortic-arch flow in the thoracic cavity, the main branches of the abdominal aorta, and the bifurcation of the common iliac artery. The largest fluctuation corresponded to the location where the aortic arch was approximately orthogonal to B0. The smallest fluctuations corresponded to areas of vasculature that were parallel to B0. Significant correlations (specifically, Spearman's ranked correlation coefficients of 0.96 and 0.97 for abdominal and thoracic cavities, respectively) were found between the MRA and Vsegment maps (p < 0.001). CONCLUSIONS: A novel non-invasive method to extract regional blood volumes from ECGs was developed and shown to be a rapid means to quantify peripheral and abdominal blood volumes.


Assuntos
Eletrocardiografia/métodos , Corpo Humano , Hidrodinâmica , Imagem por Ressonância Magnética/métodos , Magnetometria/métodos , Fluxo Sanguíneo Regional/fisiologia , Processamento de Sinais Assistido por Computador/instrumentação , Adulto , Aorta Abdominal/fisiologia , Aorta Torácica/fisiologia , Velocidade do Fluxo Sanguíneo , Feminino , Humanos , Artéria Ilíaca/fisiologia , Masculino , Adulto Jovem
13.
J Med Syst ; 43(4): 81, 2019 Feb 20.
Artigo em Inglês | MEDLINE | ID: mdl-30788605

RESUMO

Body channel communications (BCC) have been researched while an allowing technology to improve necessities for the low power and high reconfiguration power in wireless telemetry systems used at wireless communication purpose. Conventional features on BCC are concentrated mostly on modeling of channels by using of an efficient measurement technique, wireless transceiver design and then by means of a transmission technique. Particularly, the wireless digital transmitting, developed as a personalized method intended for the body channel, offers wanted to develop flexible and low power BCC systems. With the developing level of wearable communication protocol and applications, there may be an increasingly reliable on an adaptable BCC transmitter that helps both data reconfigure power and power reduction condition. In this paper, an extremely reconfigurable Hamming Encoding Digital Transmitter (HEDT) which works with both reconfigurable data and power reduction condition that supports from two innovative operation conditions is suggested. In a HEDT device, the overall data rate is controlled by the level of Hamming codes designed to make use of in the perfect BCC band of 20-100 MHz. The proposed Hamming Encoded Transmission method achieves seven times improved data rate when compared with conventional BCC processors. The next unique implementation technique is based on the usage of Frequency Shift Keying (FSK) of a Hamming encoded HEDT approach. This approach permits the BCC transceiver to use the perfect channel with bandwidth among 40-100 MHz. Thereby half the clock rate reduces 40% of overall power utilization. The HEDT system is completely designed in a 65 nm CMOS procedure. It uses a primary area of 0.14 × 0.2 mm. When functioning below a data-rate of 60 Mb/s (low power) condition, the BCC transmitter utilizes only 1.00 mW.


Assuntos
Fontes de Energia Elétrica , Eletrocardiografia Ambulatorial/instrumentação , Processamento de Sinais Assistido por Computador/instrumentação , Telemetria/instrumentação , Tecnologia sem Fio/instrumentação , Desenho de Equipamento , Humanos , Telemetria/métodos , Dispositivos Eletrônicos Vestíveis
14.
IEEE J Biomed Health Inform ; 23(6): 2365-2374, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-30703050

RESUMO

OBJECTIVE: Systolic time intervals, such as the pre-ejection period (PEP), are important parameters for assessing cardiac contractility that can be measured non-invasively using seismocardiography (SCG). Recent studies have shown that specific points on accelerometer- and gyroscope-based SCG signals can be used for PEP estimation. However, the complex morphology and inter-subject variation of the SCG signal can make this assumption very challenging and increase the root mean squared error (RMSE) when these techniques are used to develop a global model. METHODS: In this study, we compared gyroscope- and accelerometer-based SCG signals, individually and in combination, for estimating PEP to show the efficacy of these sensors in capturing valuable information regarding cardiovascular health. We extracted general time-domain features from all the axes of these sensors and developed global models using various regression techniques. RESULTS: In single-axis comparison of gyroscope and accelerometer, angular velocity signal around head to foot axis from the gyroscope provided the lowest RMSE of 12.63 ± 0.49 ms across all subjects. The best estimate of PEP, with a RMSE of 11.46 ± 0.32 ms across all subjects, was achieved by combining features from the gyroscope and accelerometer. Our global model showed 30% lower RMSE when compared to algorithms used in recent literature. CONCLUSION: Gyroscopes can provide better PEP estimation compared to accelerometers located on the mid-sternum. Global PEP estimation models can be improved by combining general time domain features from both sensors. SIGNIFICANCE: This work can be used to develop a low-cost wearable heart-monitoring device and to generate a universal estimation model for systolic time intervals using a single- or multiple-sensor fusion.


Assuntos
Acelerometria/instrumentação , Testes de Função Cardíaca , Processamento de Sinais Assistido por Computador/instrumentação , Dispositivos Eletrônicos Vestíveis , Adulto , Algoritmos , Feminino , Coração/fisiologia , Testes de Função Cardíaca/instrumentação , Testes de Função Cardíaca/métodos , Humanos , Masculino , Monitorização Fisiológica , Adulto Jovem
15.
IEEE J Biomed Health Inform ; 23(6): 2347-2353, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-30640639

RESUMO

OBJECTIVE: Careful screening of bilirubin level in newborns is mandatory as per American Academy of Pediatrics (2004), to reduce incidents of kernicterus and acute bilirubin encephalopathy. Although, invasive capillary collection of blood and subsequent biochemical test is considered a gold standard for jaundice detection in neonates, transcutaneous bilirubin measurement using various non-invasive instruments is also used sporadically across the globe. The major aim of this study was to develop a non-invasive spectrometry-based technique for measurement of neonatal bilirubin level as an alternative of total serum bilirubin (TSB) test without limitations of other available bilirubinometers. METHODS: The instrument comprises of a light source and a spectroscopic detector. A light beam from source incident on the neonatal nail plate through optical fibers. The retro reflected light is acquired using the detector. An indigenously developed software is used to acquire and analyze the optical signal and to calculate the bilirubin value. The instrument was calibrated and validated in reference to TSB on 1033 subjects. MAJOR RESULTS: The result (r = 0.95 and P < 0.001) indicates a strong correlation between the bilirubin value obtained from our method and TSB. Time variant analysis of the subjects undergoing phototherapy provided a good correlation (r = 0.98). The repeatability test result shows the mean coefficient of variation is less than 5.0%. CONCLUSIONS: The indigenously developed non-invasive technique successfully detects the bilirubin level in newborns under various physiological conditions with high accuracy and precision.


Assuntos
Bilirrubina/sangue , Hiperbilirrubinemia Neonatal/diagnóstico , Processamento de Sinais Assistido por Computador/instrumentação , Análise Espectral/métodos , Desenho de Equipamento , Humanos , Recém-Nascido , Unhas/irrigação sanguínea , Análise Espectral/instrumentação
16.
IEEE J Biomed Health Inform ; 23(6): 2325-2334, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-30629523

RESUMO

Overweight and obesity are both associated with in-meal eating parameters such as eating speed. Recently, the plethora of available wearable devices in the market ignited the interest of both the scientific community and the industry toward unobtrusive solutions for eating behavior monitoring. In this paper, we present an algorithm for automatically detecting the in-meal food intake cycles using the inertial signals (acceleration and orientation velocity) from an off-the-shelf smartwatch. We use five specific wrist micromovements to model the series of actions leading to and following an intake event (i.e., bite). Food intake detection is performed in two steps. In the first step, we process windows of raw sensor streams and estimate their micromovement probability distributions by means of a convolutional neural network. In the second step, we use a long short-term memory network to capture the temporal evolution and classify sequences of windows as food intake cycles. Evaluation is performed using a challenging dataset of 21 meals from 12 subjects. In our experiments, we compare the performance of our algorithm against three state-of-the-art approaches, where our approach achieves the highest F1 detection score (0.913 in the leave-one-subject-out experiment). The dataset used in the experiments is available at https://mug.ee.auth.gr/intake-cycle-detection/.


Assuntos
Comportamento Alimentar/fisiologia , Processamento de Sinais Assistido por Computador/instrumentação , Dispositivos Eletrônicos Vestíveis , Algoritmos , Bases de Dados Factuais , Ingestão de Alimentos/fisiologia , Humanos , Refeições/fisiologia , Punho/fisiologia
17.
IEEE Trans Biomed Eng ; 66(3): 810-820, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30028688

RESUMO

This paper presents a wearable sensor architecture for frequency-multiplexed electrical impedance tomography (EIT) and synchronous multilead electrocardiogram (ECG) data acquisition. The system is based on a novel electronic sensing architecture, called cooperative sensors, that significantly reduces the cabling complexity and enables flexible EIT stimulation and measurement patterns. The cooperative-sensor architecture was initially designed for ECG and has been extended for multichannel bioimpedance measurement. This approach allows for an adjustable EIT stimulation pattern via frequency-division multiplexing. This paper also shows a calibration procedure as well as EIT system noise performance assessment. Preliminary measurements on a healthy volunteer showed the ability of the wearable system to measure EIT data synchronously with multilead ECG. Ventilation-related and heartbeat-related EIT images were reconstructed, demonstrating the feasibility of the proposed architecture for noninvasive cardiovascular monitoring.


Assuntos
Impedância Elétrica/uso terapêutico , Eletrocardiografia/instrumentação , Processamento de Sinais Assistido por Computador/instrumentação , Tomografia/instrumentação , Dispositivos Eletrônicos Vestíveis , Algoritmos , Eletrocardiografia/métodos , Eletrodos , Desenho de Equipamento , Humanos , Masculino , Telemetria/instrumentação , Tomografia/métodos
18.
IEEE Trans Biomed Eng ; 66(1): 150-158, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-29993415

RESUMO

OBJECTIVE: Ear-EEG is a recording method in which EEG signals are acquired from electrodes placed on an earpiece inserted into the ear. Thereby, ear-EEG provides a noninvasive and discreet way of recording EEG, and has the potential to be used for long-term brain monitoring in real-life environments. Whereas previously reported ear-EEG recordings have been performed with wet electrodes, the objective of this study was to develop and evaluate dry-contact electrode ear-EEG. METHODS: To achieve a well-functioning dry-contact interface, a new ear-EEG platform was developed. The platform comprised actively shielded and nanostructured electrodes embedded in an individualized soft-earpiece. The platform was evaluated in a study of 12 subjects and four EEG paradigms: auditory steady-state response, steady-state visual evoked potential, mismatch negativity, and alpha-band modulation. RESULTS: Recordings from the prototyped dry-contact ear-EEG platform were compared to conventional scalp EEG recordings. When all electrodes were referenced to a common scalp electrode (Cz), the performance was on par with scalp EEG measured close to the ear. With both the measuring electrode and the reference electrode located within the ear, statistically significant (p < 0.05) responses were measured for all paradigms, although for mismatch negativity, it was necessary to use a reference located in the opposite ear, to obtain a statistically significant response. CONCLUSION: The study demonstrated that dry-contact electrode ear-EEG is a feasible technology for EEG recording. SIGNIFICANCE: The prototyped dry-contact ear-EEG platform represents an important technological advancement of the method in terms of user-friendliness, because it eliminates the need for gel in the electrode-skin interface.


Assuntos
Orelha Externa/fisiologia , Eletroencefalografia/instrumentação , Monitorização Ambulatorial/instrumentação , Dispositivos Eletrônicos Vestíveis , Adulto , Eletrodos , Humanos , Irídio , Desenho de Prótese , Processamento de Sinais Assistido por Computador/instrumentação
19.
IEEE Trans Biomed Eng ; 66(1): 4-13, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-29993427

RESUMO

OBJECTIVE: Ventral hernia repairs using mesh prosthetics suffer from high recurrence rates, with 10%-20% of repairs failing within three years. Uneven distribution of stress within the implanted mesh prosthetic is thought to contribute to the high recurrence rate. We propose a method for providing quantitative guidance and monitoring of hernia repairs using an array of magnetoelastic strain sensors. METHODS: The magnetoelastic strain sensors presented here are based on a coupled design to achieve measurements with higher signal-to-noise ratio (SNR). A first magnetoelastic element (the transducer) is bonded to the mesh prosthetic and is characterized by a strain-dependent magnetic field. The resonance frequency of a second magnetoelastic element (the resonator) encased in a rigid casing is biased by the transducer element's magneticity and can be measured noninvasively using an external interrogation coil. The coupled magnetoelastic strain sensors are assembled using a combination of photochemical machining, patterning, and heat sealing. RESULTS: The dynamic range of the coupled sensors can be tuned by altering the transducer geometry. Additional spring elements are integrated onto the transducer element to achieve high dynamic range measurements saturating at 74 millistrains. CONCLUSION: A coupled magnetoelastic strain sensor combines a transducer with an encased resonator element to measure strain with high SNR on an implantable flexible hernia mesh substrate. SIGNIFICANCE: This study provides surgeons and researchers with a clinically relevant tool to quantify the strain distributions within implanted mesh prosthetics, with the ultimate goal of reducing the recurrence rate of ventral hernia repairs.


Assuntos
Fenômenos Biomecânicos/fisiologia , Herniorrafia/instrumentação , Processamento de Sinais Assistido por Computador/instrumentação , Cirurgia Assistida por Computador/instrumentação , Elasticidade , Desenho de Equipamento , Hérnia Ventral/cirurgia , Herniorrafia/métodos , Humanos , Magnetismo , Telas Cirúrgicas , Transdutores
20.
IEEE Trans Biomed Eng ; 66(2): 421-432, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-29993501

RESUMO

Epileptic seizure detection requires specialized approaches such as video/electroencephalography monitoring. However, these approaches are restricted mainly to hospital setting and requires video/EEG analysis by experts, which makes these approaches resource- and labor-intensive. In contrast, we aim to develop a wireless remote monitoring system based on a single wrist-worn accelerometer device, which is sensitive to multiple types of convulsive seizures and is capable of detecting seizures with short duration. Simple time domain features including a new set of Poincar´e plot based features were extracted from the active movement events recorded using a wrist-worn accelerometer device. The best features were then selected using the area under the ROC curve analysis. Kernelized support vector data description (SVDD) was then used to classify non-seizure and seizure events. The proposed algorithm was evaluated on 5;576h of recordings from 79 patients and detected 40 (86:95%) of 46 convulsive seizures (generalized tonic-clonic (GTCS), psychogenic non-epileptic (PNES), and complex partial seizures (CPS)) from twenty patients with a total of 270 false alarms (1:16=24h). Furthermore, the algorithm showed a comparable performance (sensitivity 95:23% and false alarm rate 0:64=24h) with respect to existing unimodal and multi-modal methods for GTCS detection. The promising results shows the potential to build an ambulatory monitoring convulsive seizure detection system. A wearable accelerometer based seizure detection system would aid in continuous assessment of convulsive seizures in a timely and non-invasive manner.


Assuntos
Acelerometria , Monitorização Ambulatorial/instrumentação , Convulsões/diagnóstico , Dispositivos Eletrônicos Vestíveis , Acelerometria/instrumentação , Acelerometria/métodos , Adulto , Algoritmos , Humanos , Pessoa de Meia-Idade , Processamento de Sinais Assistido por Computador/instrumentação , Punho/fisiologia , Adulto Jovem
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