| 1. |
- Brown, Shannon, et al.
(författare)
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Intarsia-sensorized band and textrodes for real-time myoelectric pattern recognition
- 2016
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Ingår i: Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the. - : Institute of Electrical and Electronics Engineers (IEEE). - 1557-170X. - 9781457702204 ; , s. 6074-6077
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Konferensbidrag (refereegranskat)abstract
- Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes. After a comprehending measurement and performance comparison of the sEMG recordings, no significant differences were found between the textile and the Ag-AgCl electrodes in SNR and prediction accuracy obtained from pattern recognition classifiers.
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| 2. |
- Hafid, Abdelakram, et al.
(författare)
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Full Impedance Cardiography Measurement Device Using Raspberry PI3 and System-on-Chip Biomedical Instrumentation Solutions
- 2018
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Ingår i: IEEE journal of biomedical and health informatics. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2168-2194 .- 2168-2208. ; 22:6, s. 1883-1894
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Tidskriftsartikel (refereegranskat)abstract
- Impedance cardiography (ICG) is a noninvasive method for monitoring cardiac dynamics using electrical bioimpedance (EBI) measurements. Since its appearance more than 40 years ago, ICG has been used for assessing hemodynamic parameters. This paper presents a measurement system based on two System on Chip (SoC) solutions and Raspberry PI, implementing both a full three-lead ECG recorder and an impedance cardiographer, for educational and research development purposes. Raspberry PI is a platform supporting Do-I t-Yourself project and education applications across the world. The development is part of Biosignal PI, an open hardware platform focusing in quick prototyping of physiological measurement instrumentation. The SoC used for sensing cardiac biopotential is the ADAS1000, and for the EBI measurement is the AD5933. The recordings were wirelessly transmitted through Bluetooth to a PC, where the waveforms were displayed, and hemodynamic parameters such as heart rate, stroke volume, ejection time and cardiac output were extracted from the ICG and ECG recordings. These results show how Raspberry PI can be used for quick prototyping using relatively widely available and affordable components, for supporting developers in research and engineering education. The design and development documents will be available on www.BiosignalPl.com, for open access under a Non Commercial-Share A like 4.0 International License.
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| 3. |
- Seoane, Fernando, 1976-, et al.
(författare)
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Textile-Friendly Interconnection between Wearable Measurement Instrumentation and Sensorized Garments-Initial Performance Evaluation for Electrocardiogram Recordings.
- 2019
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 19:20
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Tidskriftsartikel (refereegranskat)abstract
- The interconnection between hard electronics and soft textiles remains a noteworthy challenge in regard to the mass production of textile-electronic integrated products such as sensorized garments. The current solutions for this challenge usually have problems with size, flexibility, cost, or complexity of assembly. In this paper, we present a solution with a stretchable and conductive carbon nanotube (CNT)-based paste for screen printing on a textile substrate to produce interconnectors between electronic instrumentation and a sensorized garment. The prototype connectors were evaluated via electrocardiogram (ECG) recordings using a sensorized textile with integrated textile electrodes. The ECG recordings obtained using the connectors were evaluated for signal quality and heart rate detection performance in comparison to ECG recordings obtained with standard pre-gelled Ag/AgCl electrodes and direct cable connection to the ECG amplifier. The results suggest that the ECG recordings obtained with the CNT paste connector are of equivalent quality to those recorded using a silver paste connector or a direct cable and are suitable for the purpose of heart rate detection.
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| 4. |
- Lui, Hoi-Shun, et al.
(författare)
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On the matching medium for microwave stroke diagnosis
- 2019
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Ingår i: Biomedical Physics and Engineering Express. - : IOP Publishing. - 2057-1976. ; 5:4
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Tidskriftsartikel (refereegranskat)abstract
- The choice of matching medium can directly affect the amount of power transmitted into and through human bodies, which impacts on the quality of the reconstructed images in microwave-based medical imaging, and thus the diagnosis accuracies. In this paper, the amount of the transmitted and reflected power of multi-layer planar healthy and hemorrhagic stroke brain models under different choices of matching medium are determined. These multi-layer planar brain tissue models are made up of at least 17 tissue layers with realistic dielectric properties. A layer of blood with different thickness is introduced to model the case of hemorrhagic stroke. Our results show that matching medium with low relative permittivity provides better intrinsic contrast between healthy brain and hemorrhagic brain. Analysis on how the reflection coefficient and transmittance vary under different matching medium are included to provide better insights to the findings.
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| 5. |
- Rezaei Aghdam, Sina, 1989, et al.
(författare)
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Reducing Motion Artifacts in Microwave-Based Hemorrhagic Stroke Detection
- 2019
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Ingår i: 13th European Conference on Antennas and Propagation, EuCAP 2019.
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Konferensbidrag (refereegranskat)abstract
- The use of microwave technology for brain stroke detection opens up the opportunity for developing low-cost transportable devices which can be employed for rapid and prehospital detection of bleeding in patients with traumatic brain injury. Since the detection relies on changes in the scattering parameters of the tissues during pathological conditions, the movements in head or the antennas can deteriorate the detection accuracy. As a countermeasure to this problem, we introduce a technique for reducing the sensitivity of the detection system to motion artifacts. Via analyzing the scattering from an anatomically accurate model of human brain, we evidence that the channels between different pairs of antennas exhibit significantly different levels of sensitivity to the movement. Using this as a ground truth, we develop a generalized singular value decomposition (GSVD)-based approach for assigning appropriate weights to the channels between different antennas such that the probability of correct bleeding detection is maximized.
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| 6. |
- Tomasic, Ivan, et al.
(författare)
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Comparison of publicly available beat detection algorithms performances on the ECGs obtained by a patch ECG device
- 2019
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Ingår i: 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings. - : Institute of Electrical and Electronics Engineers Inc.. - 9789532330984 ; , s. 275-278
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Konferensbidrag (refereegranskat)abstract
- Eight ECG beat detection algorithms, from the PhysioNet's WFDB and Cardiovascular Signal toolboxes, were tested on twenty measurements, obtained by the Savvy patch ECG device, for their accuracy in beat detection. On each subject, one measurement is obtained while sitting and one while running. Each measurement lasted from thirty seconds to one minute. The measurements obtained while running were more challenging for all the algorithms, as most of them almost perfectly detected all the beats on the measurements obtained in sitting position. However, when applied on the measurements obtained while running, all the algorithms have performed with decreased accuracy. Considering overall percentage of the faulty detected peaks, the four best algorithms were jqrs, from the Cardiovascular Signal Toolbox, and ecgpuwave, gqrs, and wqrs, from the WFDB Toolbox, with percentages of faulty detected beats 1.7, 2.3, 2.9, and 3, respectively.
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| 7. |
- Enejder, Annika, 1969, et al.
(författare)
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SHG Imaging for Tissue Engineering Applications
- 2016
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Ingår i: Second Harmonic Generation Imaging. - : CRC Press. - 9781439849156 - 9781439849149 ; , s. 409-426
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Treatment of lost tissue oen relies on transplantations, either of donor or of autologous tissue. Both alternatives have limitations; there is for example a limited supply of donor transplants, which also require immunosuppression therapy with possible side eects. Transplanted autologous tissue may lack some of the functions of the original tissue and the procedure may also introduce complications at the donor site. In some cases, articial substitutes manufactured from nonbiological materials can be used, for example, synthetic polymer blood vessels or joint replacement prostheses. However, these replacements have drawbacks such as risk for infections, limited material durability, and lack of mechanisms for repair, growth, and remodeling. For these reasons, development of advanced articial tissue constructs with adaptive capabilities is desirable.
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| 8. |
- Fhager, Andreas, 1976, et al.
(författare)
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3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology
- 2019
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 19:16
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Tidskriftsartikel (refereegranskat)abstract
- Early, preferably prehospital, detection of intracranial bleeding after trauma or stroke would dramatically improve the acute care of these large patient groups. In this paper, we use simulated microwave transmission data to investigate the performance of a machine learning classification algorithm based on subspace distances for the detection of intracranial bleeding. A computational model, consisting of realistic human head models of patients with bleeding, as well as healthy subjects, was inserted in an antenna array model. The Finite-Difference Time-Domain (FDTD) method was then used to generate simulated transmission coefficients between all possible combinations of antenna pairs. These transmission data were used both to train and evaluate the performance of the classification algorithm and to investigate its ability to distinguish patients with versus without intracranial bleeding. We studied how classification results were affected by the number of healthy subjects and patients used to train the algorithm, and in particular, we were interested in investigating how many samples were needed in the training dataset to obtain classification results better than chance. Our results indicated that at least 200 subjects, i.e., 100 each of the healthy subjects and bleeding patients, were needed to obtain classification results consistently better than chance (p < 0.05 using Student's t-test). The results also showed that classification results improved with the number of subjects in the training data. With a sample size that approached 1000 subjects, classifications results characterized as area under the receiver operating curve (AUC) approached 1.0, indicating very high sensitivity and specificity.
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| 9. |
- Forcolin, Fabio, et al.
(författare)
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Comparison of outlier heartbeat identification and spectral transformation strategies for deriving heart rate variability indices for drivers at different stages of sleepiness
- 2018
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Ingår i: Traffic Injury Prevention. - : Taylor & Francis. - 1538-9588 .- 1538-957X. ; 19, s. S112-S119
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Appropriate preprocessing for detecting and removing outlier heartbeats and spectral transformation is essential for deriving heart rate variability (HRV) indices from cardiac monitoring data with high accuracy. The objective of this study is to evaluate agreement between standard preprocessing methods for cardiac monitoring data used to detect outlier heartbeats and perform spectral transformation, in relation to estimating HRV indices for drivers at different stages of sleepiness.Methods: The study analyzed more than 3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. Electrocardiography (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The Pan-Tompkins algorithm was used for peak detection of heartbeats from ECG data. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat interval deviating >30% from the mean of the 4 previous intervals, and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain; these methods were (1) the Fourier transform; (2) an autoregressive model; and (3) the Lomb-Scargle periodogram. The preprocessing methods were compared quantitatively and by assessing agreement between estimations of 13 common HRV indices using Bland-Altman plots and paired Student's t-tests.Results: The PC method detected more than 4times as many outliers (0.28%) than SD (0.065%). Most HRV indices derived using different preprocessing methods exhibited significant systematic (P <.05) and substantial random variations.Conclusions: The standard preprocessing methods for HRV data for outlier heartbeat detection and spectral transformation show low levels of agreement. This finding implies that, prior to designing algorithms for detection of sleepy drivers based on HRV analysis, the impact of different preprocessing methods and combinations thereof on driver sleepiness assessment needs to be studied.
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| 10. |
- Fredén Jansson, Karl-Johan, 1988
(författare)
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The Balanced Electromagnetic Separation Transducer for Bone Conduction Audiometry and Hearing Rehabilitation
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Hearing via air conduction (AC) and bone conduction (BC) are attributed to bethe natural ways of conducting sound to the cochlea. With AC hearing, air pressurevariations are transmitted to the cochlea via the ear canal, whereas with BChearing, sound vibrations are transmitted through the skull bone to the cochlea.Patients with a hearing loss in the cochlea or auditory nerve are commonly rehabilitatedwith conventional AC hearing aids in the ear canal, but also using cochlearimplants. If the pathway for AC sound to reach the cochlea is obstructed, patientscan often benet from bone conduction devices (BCDs). In order to determinethe type and degree of hearing loss, the BC hearing thresholds are measured usinga bone conduction vibrator, and then analyzed together with the AC hearingthresholds for the diagnosis and to suggest an appropriate rehabilitation alternative.The motor unit in conventional BCDs and bone vibrators are known togenerate high amount of distortion at low frequencies where the Balanced ElectromagneticSeparation Transducer (BEST) principle may oer a new era in BChearing rehabilitation and audiometry.This thesis combines two BC hearing related topics, where the rst topic is anevaluation of a new audiometric bone vibrator, Radioear B81, which is assumedto oer more accurate BC hearing threshold measurements. The second topic isrelated to a new type of active transcutaneous BCD, called the Bone ConductionImplant (BCI), which leaves the skin intact by using a wireless solution thatdoes not require a permanent skin penetration. Even though the applications aredierent, both devices use the BEST principle as motor unit in their design.The audiometric bone vibrator Radioear B81 was found to have an improvedperformance at low frequencies where it can produce higher output levels with lessharmonic distortion than the conventional Radioear B71. In a clinical study of therst six patients, the BCI was found as ecient as already commercially availableBCDs, and with the advantage of not needing a skin penetration. In a technicalevaluation of the BCI, it was shown to be a mechanically robust design and totolerate magnetic resonance imaging at 1.5 Tesla.
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