Home Medicine The development of an experimental setup to measure acousto-electric interaction signal
Article Open Access

The development of an experimental setup to measure acousto-electric interaction signal

  • Gunnlaugsdóttir Kristín Inga EMAIL logo
Published/Copyright: September 12, 2015

Abstract

A new method is desirable for secure efficiency of FES treatment of degenerated denervated muscles. Degeneration of denervaed muscles as a consequence of spinal injuries are treated with functional electrical stimulation (FES). So far, no effective method to monitor the effectiveness of the treatment over the whole treated muscle is available. The most common method is placing finger on appropriate tendons and sense the movement. We suggest new approach. As pressure wave changes locally electrical conductivity in its propagation direction of the medium, a change in voltage is detected when electrical field is applied simultaneously at that location. This change in voltage is called acousto-electric interaction (AEI) signal. By recording AEI signal a distribution of electrical activity can be mapped, known as ultrasound current source density imaging (UCSDI). In this paper, an experimental setup to investigate the AEI signal is developed. The signal is measured and compared to calculated values. Debye effect and AEI signal is detected.

1 Introduction

Permanent denervation of the lower limbs can be caused by spinal injuries, such as injuries of the spinal cord below the twelfth vertebra, spinal roots or peripheral nerves. Subsequently, no electrical signals, like sensory information and motor commands can be transmitted between the neurons and muscles. In the absence of electrical stimulation, no contraction occurs in the muscle leading to weakening and diminishing the muscles, and results sometimes in atrophy [1, 2].

Electrical stimulation (FES) is used in order to generate a contraction in denervated muscles. In the absence of neuromuscular transmission, a depolarization of the muscle is generated by depolarizing the cellular membrane of each single muscle fiber above threshold potential. Researches have shown than where FES is applied, it tends stop muscle degeneration and promote regeneration of muscles [1, 3]. These effects are though not uniform over the whole muscle, leading to strengthening of some muscles or part of a muscle whereas other parts continue to degenerate [1, 4].

The most common method to monitor muscle contraction is to place a finger on tendons that are connected to the muscle being stimulated, like patella tendon. If movement of the tendon is sensed, it does not give information of which muscle is stimulated if many muscles are connected to the same tendon. Additionally it does neither inform if the whole muscle is contracting or just a part [4]. Another method is using ultrasound and analyse the echo, but it doesńt give information either on which part of the muscle is contracting [4].

For this purpose, acousto-electric effect could be used, as it is non-invasive and can give real-time information on electrical activity of a muscle. As pressure wave propagates into a muscle, with variations in pressure and temperature, the conductivity of the muscle changes locally. When current passes through this area, it causes changes in voltage. This voltage is called, the acousto-electric interaction (AEI) signal [5].

Acousto-electric interaction signal can be reconstructed and used in medical imaging. A real-time 3D image, so called Ultrasound Current Source Density Imaging (UCSDI) is capable of map electrical distribution by using acousto electric effect [6].

1.1 Principle

The change in conductivity, Δσ, due to acoustic pressure change, ΔP, is given by [5, 6]:

Δσσ0=-KIΔP

where σ0 is the conductivity of the medium and KI is the interaction coefficient of the solution. In a 0.9% NaCl solution, the value of KI is in the order of 0.1% per MPa (10−9) [5–7].

When an acoustic wave propagates through the medium, it changes the conductivity locally, and when convene with electrical current, their interaction will generate acousto-electric interaction signal. Based on Ohms law and the acousto electric effect, the voltage that will be recorded with recording electrodes is [6]:

V=(J¯iLJ¯I)(ρ0-ρ0KIΔP)dxdydz

where J¯I is the distributed current source, J¯iL is the lead field of recording lead i and ρ = (ρ0ρ0KIΔP) is the resistivity in a pressure field. This equation takes the shape of the volume conductor into account, as well as the field of current electrodes and the sensitivity field of the recording electrodes, or the lead field. The dot product of the fields of lead of the voltage electrode, J¯iL, and the one of current, J¯I, results in a number, which expresses the sensitivity distribution to conductivity change throughout the volume [8].

The signal can be expanded into two components:

V=J¯iLJ¯Iρ0dxdydzJ¯iLJ¯I(ρ0KIΔP)dxdydz

The first component expresses the low-frequency signal generated by the current source and the second one is the high-frequency signal or the AEI signal [6].

The signal can be further simplified, when measurements are performed in one direction and current field and lead field are the same [9]:

V=ρ0KIΔPJl

where J is current field and l is the distance between the recording electrodes. It can be seen from the above equations that the magnitude of the acousto electrical interactional signal is proportional both to the injected current and the pressure amplitude. This can give a rise to a signal of measurable magnitude. Special attention has to be taken measuring the acousto-electrical interaction signal, as it is of very low magnitude, several dozens of microvolts. Also, Debye effect has to be taken into account, but it is an increase in voltage due to separation of the ions because of frictional forces induced by pressure only [7]. The magnitude of averaged AEI signal in heart is 26 μV and can be up to 35 μV [10].

The goal of this project is to build measurement setup to measure Debye effect and the AEI signal.

2 Material and methods

The measurements were set up as shown in figure 1.

Figure 1 Measurement setup used to measure Debye effect and the AEI signal. Ultrasound transducer sends acoustic wave into the solution. Current injecting electrodes and recording electrodes are located at the point of highest pressure, orthogonal to the propagation of the acoustic wave. Amplifiers amplify the recorded signal before it is being visualized on the oscilloscope. The pressure is measured by hydrophone. Functional generator is used for triggering.
Figure 1

Measurement setup used to measure Debye effect and the AEI signal. Ultrasound transducer sends acoustic wave into the solution. Current injecting electrodes and recording electrodes are located at the point of highest pressure, orthogonal to the propagation of the acoustic wave. Amplifiers amplify the recorded signal before it is being visualized on the oscilloscope. The pressure is measured by hydrophone. Functional generator is used for triggering.

The measurements were made in 0.9% NaCl saline solution, a composition that is similar to extracellular fluid. A container, with dimension of 12.5 cm (width) × 20 cm (length) × 9 cm (depth), was used for the measurements. A pulser-receiver (5077PR from Olympus) generated electrical pulses to the ultrasound transducer. A focused immersion transducer (V325 SU from Olympus), with central frequency of 500 kHz, diameter of 19 mm and focus point at 2.6 mm, was located in a hole on one side of the container. At the opposite end sponges absorb the scattering waves of the ultrasound. The high frequency of the transducer is different from other frequencies of the body and is therefore easy to filter. The transducer was separated from the fluid with a flexible latex membrane. In order to diminish the effects of air, a transmission gel was used for the transducer. The pressure was measured by an ultrasonic hydrophone (MH28 from Force Technology) and amplified by matching preamplifier (PAN from Force Technology).

Two pairs of electrodes were placed where the highest pressure exists; one pair for injecting current, which creates constant current field and another pair for recording the voltage, midst in the current field. The electrodes were wires, made of stainless steel, with diameter of 0.46 mm. The current injecting wires had active length of 1.5 mm and were separated with a distance of 2.5 mm, while the recording wires were separated with 0.5 mm and had active length of 3 mm.

Function generator (HPG1 from Velleman) was used to generate electrical signal for current generator. In order to increase the output amplitude, a current generator was designed, which also has the function to form a floating ground to avoid creating a short circuit in the solution, between the injecting electrodes and the recording ones. The output was alternative square wave of frequency of 100 Hz. Using a low frequency square wave, the current can be considered constant, while the signal is detected, but avoids polarization of the electrode, as would happen with constant dc current.

For the recorded voltage, an amplifier (HVA from FEMTO) was used to amplify the signal. The amplifier has up to 60 dB gain. As it has low input impedance, a preamplifier was constructed, that has higher input impedance. The input impedance of the preamplifer is 1012 Ω and it has a high pass filter, with -6 dB cut-off frequency at 234 kHz. The signal is visualized with an oscilloscope (RTO1044 from Rhode&Schwarz).

Geometrical measurements are performed with the help of the compound table (KT70 from Prooxon) that can be turned in x- and y- dimensions with 1 revolution corresponding to 1mm and 0.05 mm respectively.

The function generator also provided the trigger for the measurement. Along with generating the current generator, its signal was conducted to the oscilloscope. With a delay of 1 ms, it was further transmitted to the pulser-receiver, which then triggered the transducer.

3 Results

This setup was used to measure Debye effect and the AEI signal. The recording electrodes were positioned in 5 cm distance from the ultrasound transducer, the location with the highest pressure amplitude. The focal length of the transducer appears to be at larger than stated in the datasheet, which results from modification because of the transducer gel has changed the beam shape. The orientation of the lead field was orthogonal to the propagation of the acoustic wave. The hydrophone. was placed directly behind the recording electrodes during measurements, in order to record the pressure amplitude. The pressure was 760 kPa, at the point of the measurements.

The signal was averaged, in order to reduce the background noise. The sampling frequency of the signal was of 2GHz.

As can be seen on figure 2, Debye effect can be clearly identified. From figure 3, it is shown, that the signal has the amplitude that equals to 71 μV at the input. The signal resembles the pressure amplitude, though some delay can be noticed. That can be explained by the fact, that the signal goes through series of two amplifiers, before being visualized on the oscilloscope.

Figure 2 Signal detection. The yellow signal is the pressure amplitude measured by the hydrophone. The green signal is the voltage at the recording signal and showing the Debye effect at the same time point as the hydrophone shows the pressure wave. Finally the blue signal represents the current waveform, that is constant during measurements and the orange is the echo detected by the transducer.
Figure 2

Signal detection. The yellow signal is the pressure amplitude measured by the hydrophone. The green signal is the voltage at the recording signal and showing the Debye effect at the same time point as the hydrophone shows the pressure wave. Finally the blue signal represents the current waveform, that is constant during measurements and the orange is the echo detected by the transducer.

Figure 3 Closer view of the pressure amplitude (yellow) and Debye signal (green). The amplitude of the pressure wave is indicated with the green vertical markers, which also can be seen on the lower graph. This is Debye effect.
Figure 3

Closer view of the pressure amplitude (yellow) and Debye signal (green). The amplitude of the pressure wave is indicated with the green vertical markers, which also can be seen on the lower graph. This is Debye effect.

Current electrodes were inserted, generating current field orthogonal to the propagation of the ultrasound wave, whereas the recording electrodes were located in the middle of the current field. 9 mA current was led to the current electrodes, while the signal was registered with the recording electrodes.

On figure 4, the signal can be seen, when current is applied simultaneously to the ultrasound wave. The current is kept constant during the measurements, so the only changing factor is the pressure amplitude. Disturbances are noticed on that signal, which makes it harder to isolate. This signal is a mixture of AEI signal and Debye effect and has the amplitude of 68 μV.

Figure 4 Signal generated as both ultrasound pressure wave and electrical current are passing the electrode plane.
Figure 4

Signal generated as both ultrasound pressure wave and electrical current are passing the electrode plane.

Numerical estimation of the AEI signal shows that these signals are in same dimensions as calculated values. Using the equation given above, along with given constants and values used in the measurement:

V=ρ0KIΔPJl

where

ρ=0.75Ωm(20C)l=0.05mJ=9mA/(0.02×0.03)m2=15A/m2KI=0.01/MPa1ΔP=0.76MPa

results in a signal of the magnitude of 43μV.

This result indicates that the measurement setup is qualified for measuring Debye effect and the AEI signal.

4 Discussion

In the present experiment, the measurement setup was constructed in order to measure the AEI signal. It is hard to detect the signal, as it is of small magnitude, only of several microvolts. These measurements showed that it is possible to measure Debye effect and the AEI signal with the existing setup and it was of right magnitude as compared to calculated values. More measurements are needed to evaluate different properties of the measurement setup. In order to get isolated AEI signal, Debye effect would need to be subtracted from the recorded signal, as it is not connected to electrical activities. Filtering and signal processing are necessary for the analysis. With appropriate signal processing, the disturbances arising could be eliminated and the signal would be clearer.

Good signal detection and signal processing is necessary when using ultrasound to detect electrical activities in muscles. In the tight, the muscles are surrounded by adipose tissues and skin, which are less conducting, and would thus reduce the magnitude of the signal and bring some disturbances. The frequency of the ultrasound is different from the low signals of the human body. It should thus be easy to filter. Suitable setup and adequate filtering are needed for measuring the biological current. These measurements should give information if there is actual current existing and if the whole muscle or only part of the muscle is activated.

Good signal detection and signal processing is necessary when using ultrasound to detect electrical activities in muscles. In the tight, the muscles are surrounded by adipose tissues and skin, which are less conducting, and would thus reduce the magnitude of the signal and bring some disturbances. The frequency of the ultrasound is different from the low signals of the human body. It should thus be easy to filter. Suitable setup and adequate filtering are needed for measuring the biological current. These measurements should give information if there is actual current existing and if the whole muscle or only part of the muscle is activated.

Author's Statement

  1. Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent has been obtained from all individuals included in this study. Ethical approval: The research related to human use has been complied with all the relevant national regulations, institutional policies and in accordance the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee.

References

[1] P. Gargiulo, “3D Modelling and monitoring of denervated muscle under Functional Electrical Stimulation treatment and associated bone structural changes,” Eur. J. Transl. Myol., vol. 21, no. 1–2, pp. 31–94, 2011.10.4081/bam.2011.1-2.31Search in Google Scholar

[2] H. Kern, R. Stramare, L. Martino, R. Zanato, P. Gargiulo, and U. Carraro, “Permanent LMN denervation of human skeletal muscle and recovery by hb FES: management and monitoring,” Eur. J. Transl. Myol., vol. 20, no. 3, pp. 91–104, 2010.10.4081/bam.2010.3.91Search in Google Scholar

[3] W. Mayr, C. Hofer, M. Bijak, D. Rafolt, E. Unger, S. Sauermann, H. Lanmueller, and H. Kern, “Functional Electrical Stimulation (FES) of denervated muscles: existing and prospective technological solutions,” Basic Appl Myol, vol. 12, no. 6, pp. 287–290, 2002.Search in Google Scholar

[4] B. Gudjonsdottir, P. Gargiulo, and T. Helgason, “Use of ultrasound current source density imaging (UCSDI) to monitor electrical stimulation of denervated muscles and fiber activity, some theoretical considerations,” presented at the 15th Annual Conference of the International Functional Electrical Stimulation Society, 2010.Search in Google Scholar

[5] B. Lavandier, J. Jossinet, and D. Cathignol, “Experimental measurement of the acousto-electric interaction signal in saline solution,” Ultrasonics, vol. 38, no. 9, pp. 929–936, 2000.10.1016/S0041-624X(00)00029-9Search in Google Scholar

[6] R. Olafsson, R. S. Witte, S.-W. Huang, and M. O’Donnell, “Ultrasound Current Source Density Imaging,” IEEE Trans. Biomed. Eng., vol. 55, no. 7, pp. 1840–1848, Jul. 2008.10.1109/TBME.2008.919115Search in Google Scholar

[7] J. Jossinet, B. Lavandier, and D. Cathignol, “The phemenology of acousto-electric interaction signal in aqueous solution of electrolytes,” Ultrasonics, vol. 36, pp. 607–613, 1998.10.1016/S0041-624X(97)00113-3Search in Google Scholar

[8] J. Malmivuo and R. Plonsey, Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. New York: Oxford University Press, 1995.10.1093/acprof:oso/9780195058239.001.0001Search in Google Scholar

[9] B. Guđjónsdóttir, “On using acousto-electric interaction effect for current mapping in denervated degenerated muscles: feasibility study design and testing of instrumentation,” Master of Science, University of Reykjavík, Reykjavík, 2011.Search in Google Scholar

[10] Q. Li, R. Olafsson, P. Ingram, Z. Wang, and R. Witte, “Measuring the acoustoelectric interaction constant using ultrasound current source density imaging,” Phys. Med. Biol., vol. 57, no. 19, pp. 5929–5941, Oct. 2012.10.1088/0031-9155/57/19/5929Search in Google Scholar PubMed PubMed Central

Published Online: 2015-9-12
Published in Print: 2015-9-1

© 2015 by Walter de Gruyter GmbH, Berlin/Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles in the same Issue

  1. Research Article
  2. Development and characterization of superparamagnetic coatings
  3. Research Article
  4. The development of an experimental setup to measure acousto-electric interaction signal
  5. Research Article
  6. Stability analysis of ferrofluids
  7. Research Article
  8. Investigation of endothelial growth using a sensors-integrated microfluidic system to simulate physiological barriers
  9. Research Article
  10. Energy harvesting for active implants: powering a ruminal pH-monitoring system
  11. Research Article
  12. New type of fluxgate magnetometer for the heart’s magnetic fields detection
  13. Research Article
  14. Field mapping of ballistic pressure pulse sources
  15. Research Article
  16. Development of a new homecare sleep monitor using body sounds and motion tracking
  17. Research Article
  18. Noise properties of textile, capacitive EEG electrodes
  19. Research Article
  20. Detecting phase singularities and rotor center trajectories based on the Hilbert transform of intraatrial electrograms in an atrial voxel model
  21. Research Article
  22. Spike sorting: the overlapping spikes challenge
  23. Research Article
  24. Separating the effect of respiration from the heart rate variability for cases of constant harmonic breathing
  25. Research Article
  26. Locating regions of arrhythmogenic substrate by analyzing the duration of triggered atrial activities
  27. Research Article
  28. Combining different ECG derived respiration tracking methods to create an optimal reconstruction of the breathing pattern
  29. Research Article
  30. Atrial and ventricular signal averaging electrocardiography in pacemaker and cardiac resynchronization therapy
  31. Research Article
  32. Estimation of a respiratory signal from a single-lead ECG using the 4th order central moments
  33. Research Article
  34. Compressed sensing of multi-lead ECG signals by compressive multiplexing
  35. Research Article
  36. Heart rate monitoring in ultra-high-field MRI using frequency information obtained from video signals of the human skin compared to electrocardiography and pulse oximetry
  37. Research Article
  38. Synchronization in wireless biomedical-sensor networks with Bluetooth Low Energy
  39. Research Article
  40. Automated classification of stages of anaesthesia by populations of evolutionary optimized fuzzy rules
  41. Research Article
  42. Effects of sampling rate on automated fatigue recognition in surface EMG signals
  43. Research Article
  44. Closed-loop transcranial alternating current stimulation of slow oscillations
  45. Research Article
  46. Cardiac index in atrio- and interventricular delay optimized cardiac resynchronization therapy and cardiac contractility modulation
  47. Research Article
  48. The role of expert evaluation for microsleep detection
  49. Research Article
  50. The impact of baseline wander removal techniques on the ST segment in simulated ischemic 12-lead ECGs
  51. Research Article
  52. Metal artifact reduction by projection replacements and non-local prior image integration
  53. Research Article
  54. A novel coaxial nozzle for in-process adjustment of electrospun scaffolds’ fiber diameter
  55. Research Article
  56. Processing of membranes for oxygenation using the Bellhouse-effect
  57. Research Article
  58. Inkjet printing of viable human dental follicle stem cells
  59. Research Article
  60. The use of an icebindingprotein out of the snowflea Hypogastrura harveyi as a cryoprotectant in the cryopreservation of mesenchymal stem cells
  61. Research Article
  62. New NIR spectroscopy based method to determine ischemia in vivo in liver – a first study on rats
  63. Research Article
  64. QRS and QT ventricular conduction times and permanent pacemaker therapy after transcatheter aortic valve implantation
  65. Research Article
  66. Adopting oculopressure tonometry as a transient in vivo rabbit glaucoma model
  67. Research Article
  68. Next-generation vision testing: the quick CSF
  69. Research Article
  70. Improving tactile sensation in laparoscopic surgery by overcoming size restrictions
  71. Research Article
  72. Design and control of a 3-DOF hydraulic driven surgical instrument
  73. Research Article
  74. Evaluation of endourological tools to improve the diagnosis and therapy of ureteral tumors – from model development to clinical application
  75. Research Article
  76. Frequency based assessment of surgical activities
  77. Research Article
  78. “Hands free for intervention”, a new approach for transoral endoscopic surgery
  79. Research Article
  80. Pseudo-haptic feedback in medical teleoperation
  81. Research Article
  82. Feasibility of interactive gesture control of a robotic microscope
  83. Research Article
  84. Towards structuring contextual information for workflow-driven surgical assistance functionalities
  85. Research Article
  86. Towards a framework for standardized semantic workflow modeling and management in the surgical domain
  87. Research Article
  88. Closed-loop approach for situation awareness of medical devices and operating room infrastructure
  89. Research Article
  90. Kinect based physiotherapy system for home use
  91. Research Article
  92. Evaluating the microsoft kinect skeleton joint tracking as a tool for home-based physiotherapy
  93. Research Article
  94. Integrating multimodal information for intraoperative assistance in neurosurgery
  95. Research Article
  96. Respiratory motion tracking using Microsoft’s Kinect v2 camera
  97. Research Article
  98. Using smart glasses for ultrasound diagnostics
  99. Research Article
  100. Measurement of needle susceptibility artifacts in magnetic resonance images
  101. Research Article
  102. Dimensionality reduction of medical image descriptors for multimodal image registration
  103. Research Article
  104. Experimental evaluation of different weighting schemes in magnetic particle imaging reconstruction
  105. Research Article
  106. Evaluation of CT capability for the detection of thin bone structures
  107. Research Article
  108. Towards contactless optical coherence elastography with acoustic tissue excitation
  109. Research Article
  110. Development and implementation of algorithms for automatic and robust measurement of the 2D:4D digit ratio using image data
  111. Research Article
  112. Automated high-throughput analysis of B cell spreading on immobilized antibodies with whole slide imaging
  113. Research Article
  114. Tissue segmentation from head MRI: a ground truth validation for feature-enhanced tracking
  115. Research Article
  116. Video tracking of swimming rodents on a reflective water surface
  117. Research Article
  118. MR imaging of model drug distribution in simulated vitreous
  119. Research Article
  120. Studying the extracellular contribution to the double wave vector diffusion-weighted signal
  121. Research Article
  122. Artifacts in field free line magnetic particle imaging in the presence of inhomogeneous and nonlinear magnetic fields
  123. Research Article
  124. Introducing a frequency-tunable magnetic particle spectrometer
  125. Research Article
  126. Imaging of aortic valve dynamics in 4D OCT
  127. Research Article
  128. Intravascular optical coherence tomography (OCT) as an additional tool for the assessment of stent structures
  129. Research Article
  130. Simple concept for a wide-field lensless digital holographic microscope using a laser diode
  131. Research Article
  132. Intraoperative identification of somato-sensory brain areas using optical imaging and standard RGB camera equipment – a feasibility study
  133. Research Article
  134. Respiratory surface motion measurement by Microsoft Kinect
  135. Research Article
  136. Improving image quality in EIT imaging by measurement of thorax excursion
  137. Research Article
  138. A clustering based dual model framework for EIT imaging: first experimental results
  139. Research Article
  140. Three-dimensional anisotropic regularization for limited angle tomography
  141. Research Article
  142. GPU-based real-time generation of large ultrasound volumes from freehand 3D sweeps
  143. Research Article
  144. Experimental computer tomograph
  145. Research Article
  146. US-tracked steered FUS in a respiratory ex vivo ovine liver phantom
  147. Research Article
  148. Contribution of brownian rotation and particle assembly polarisation to the particle response in magnetic particle spectrometry
  149. Research Article
  150. Preliminary investigations of magnetic modulated nanoparticles for microwave breast cancer detection
  151. Research Article
  152. Construction of a device for magnetic separation of superparamagnetic iron oxide nanoparticles
  153. Research Article
  154. An IHE-conform telecooperation platform supporting the treatment of dementia patients
  155. Research Article
  156. Automated respiratory therapy system based on the ARDSNet protocol with systemic perfusion control
  157. Research Article
  158. Identification of surgical instruments using UHF-RFID technology
  159. Research Article
  160. A generic concept for the development of model-guided clinical decision support systems
  161. Research Article
  162. Evaluation of local alterations in femoral bone mineral density measured via quantitative CT
  163. Research Article
  164. Creating 3D gelatin phantoms for experimental evaluation in biomedicine
  165. Research Article
  166. Influence of short-term fixation with mixed formalin or ethanol solution on the mechanical properties of human cortical bone
  167. Research Article
  168. Analysis of the release kinetics of surface-bound proteins via laser-induced fluorescence
  169. Research Article
  170. Tomographic particle image velocimetry of a water-jet for low volume harvesting of fat tissue for regenerative medicine
  171. Research Article
  172. Wireless medical sensors – context, robustness and safety
  173. Research Article
  174. Sequences for real-time magnetic particle imaging
  175. Research Article
  176. Speckle-based off-axis holographic detection for non-contact photoacoustic tomography
  177. Research Article
  178. A machine learning approach for planning valve-sparing aortic root reconstruction
  179. Research Article
  180. An in-ear pulse wave velocity measurement system using heart sounds as time reference
  181. Research Article
  182. Measuring different oxygenation levels in a blood perfusion model simulating the human head using NIRS
  183. Research Article
  184. Multisegmental fusion of the lumbar spine a curse or a blessing?
  185. Research Article
  186. Numerical analysis of the biomechanical complications accompanying the total hip replacement with NANOS-Prosthetic: bone remodelling and prosthesis migration
  187. Research Article
  188. A muscle model for hybrid muscle activation
  189. Research Article
  190. Mathematical, numerical and in-vitro investigation of cooling performance of an intra-carotid catheter for selective brain hypothermia
  191. Research Article
  192. An ideally parameterized unscented Kalman filter for the inverse problem of electrocardiography
  193. Research Article
  194. Interactive visualization of cardiac anatomy and atrial excitation for medical diagnosis and research
  195. Research Article
  196. Virtualizing clinical cases of atrial flutter in a fast marching simulation including conduction velocity and ablation scars
  197. Research Article
  198. Mesh structure-independent modeling of patient-specific atrial fiber orientation
  199. Research Article
  200. Accelerating mono-domain cardiac electrophysiology simulations using OpenCL
  201. Research Article
  202. Understanding the cellular mode of action of vernakalant using a computational model: answers and new questions
  203. Research Article
  204. A java based simulator with user interface to simulate ventilated patients
  205. Research Article
  206. Evaluation of an algorithm to choose between competing models of respiratory mechanics
  207. Research Article
  208. Numerical simulation of low-pulsation gerotor pumps for use in the pharmaceutical industry and in biomedicine
  209. Research Article
  210. Numerical and experimental flow analysis in centifluidic systems for rapid allergy screening tests
  211. Research Article
  212. Biomechanical parameter determination of scaffold-free cartilage constructs (SFCCs) with the hyperelastic material models Yeoh, Ogden and Demiray
  213. Research Article
  214. FPGA controlled artificial vascular system
  215. Research Article
  216. Simulation based investigation of source-detector configurations for non-invasive fetal pulse oximetry
  217. Research Article
  218. Test setup for characterizing the efficacy of embolic protection devices
  219. Research Article
  220. Impact of electrode geometry on force generation during functional electrical stimulation
  221. Research Article
  222. 3D-based visual physical activity assessment of children
  223. Research Article
  224. Realtime assessment of foot orientation by Accelerometers and Gyroscopes
  225. Research Article
  226. Image based reconstruction for cystoscopy
  227. Research Article
  228. Image guided surgery innovation with graduate students - a new lecture format
  229. Research Article
  230. Multichannel FES parameterization for controlling foot motion in paretic gait
  231. Research Article
  232. Smartphone supported upper limb prosthesis
  233. Research Article
  234. Use of quantitative tremor evaluation to enhance target selection during deep brain stimulation surgery for essential tremor
  235. Research Article
  236. Evaluation of adhesion promoters for Parylene C on gold metallization
  237. Research Article
  238. The influence of metallic ions from CoCr28Mo6 on the osteogenic differentiation and cytokine release of human osteoblasts
  239. Research Article
  240. Increasing the visibility of thin NITINOL vascular implants
  241. Research Article
  242. Possible reasons for early artificial bone failure in biomechanical tests of ankle arthrodesis systems
  243. Research Article
  244. Development of a bending test procedure for the characterization of flexible ECoG electrode arrays
  245. Research Article
  246. Tubular manipulators: a new concept for intracochlear positioning of an auditory prosthesis
  247. Research Article
  248. Investigation of the dynamic diameter deformation of vascular stents during fatigue testing with radial loading
  249. Research Article
  250. Electrospun vascular grafts with anti-kinking properties
  251. Research Article
  252. Integration of temperature sensors in polyimide-based thin-film electrode arrays
  253. Research Article
  254. Use cases and usability challenges for head-mounted displays in healthcare
  255. Research Article
  256. Device- and service profiles for integrated or systems based on open standards
  257. Research Article
  258. Risk management for medical devices in research projects
  259. Research Article
  260. Simulation of varying femoral attachment sites of medial patellofemoral ligament using a musculoskeletal multi-body model
  261. Research Article
  262. Does enhancing consciousness for strategic planning processes support the effectiveness of problem-based learning concepts in biomedical education?
  263. Research Article
  264. SPIO processing in macrophages for MPI: The breast cancer MPI-SNLB-concept
  265. Research Article
  266. Numerical simulations of airflow in the human pharynx of OSAHS patients
Downloaded on 25.12.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cdbme-2015-0002/html
Scroll to top button