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]:
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]:
where
The signal can be expanded into two components:
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]:
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.

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.

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.

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.

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:
where
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
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
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- Introducing a frequency-tunable magnetic particle spectrometer
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- Imaging of aortic valve dynamics in 4D OCT
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- Intravascular optical coherence tomography (OCT) as an additional tool for the assessment of stent structures
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- Simple concept for a wide-field lensless digital holographic microscope using a laser diode
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- Intraoperative identification of somato-sensory brain areas using optical imaging and standard RGB camera equipment – a feasibility study
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- Respiratory surface motion measurement by Microsoft Kinect
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- Improving image quality in EIT imaging by measurement of thorax excursion
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- A clustering based dual model framework for EIT imaging: first experimental results
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- Three-dimensional anisotropic regularization for limited angle tomography
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- GPU-based real-time generation of large ultrasound volumes from freehand 3D sweeps
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- Experimental computer tomograph
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- US-tracked steered FUS in a respiratory ex vivo ovine liver phantom
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- Contribution of brownian rotation and particle assembly polarisation to the particle response in magnetic particle spectrometry
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- Preliminary investigations of magnetic modulated nanoparticles for microwave breast cancer detection
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- Construction of a device for magnetic separation of superparamagnetic iron oxide nanoparticles
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- An IHE-conform telecooperation platform supporting the treatment of dementia patients
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- Automated respiratory therapy system based on the ARDSNet protocol with systemic perfusion control
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- Identification of surgical instruments using UHF-RFID technology
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- A generic concept for the development of model-guided clinical decision support systems
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- Evaluation of local alterations in femoral bone mineral density measured via quantitative CT
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- Creating 3D gelatin phantoms for experimental evaluation in biomedicine
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- Influence of short-term fixation with mixed formalin or ethanol solution on the mechanical properties of human cortical bone
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- Analysis of the release kinetics of surface-bound proteins via laser-induced fluorescence
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- Tomographic particle image velocimetry of a water-jet for low volume harvesting of fat tissue for regenerative medicine
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- Wireless medical sensors – context, robustness and safety
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- Sequences for real-time magnetic particle imaging
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- Speckle-based off-axis holographic detection for non-contact photoacoustic tomography
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- A machine learning approach for planning valve-sparing aortic root reconstruction
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- An in-ear pulse wave velocity measurement system using heart sounds as time reference
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- Measuring different oxygenation levels in a blood perfusion model simulating the human head using NIRS
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- Multisegmental fusion of the lumbar spine a curse or a blessing?
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- Numerical analysis of the biomechanical complications accompanying the total hip replacement with NANOS-Prosthetic: bone remodelling and prosthesis migration
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- A muscle model for hybrid muscle activation
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- Mathematical, numerical and in-vitro investigation of cooling performance of an intra-carotid catheter for selective brain hypothermia
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- An ideally parameterized unscented Kalman filter for the inverse problem of electrocardiography
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- Interactive visualization of cardiac anatomy and atrial excitation for medical diagnosis and research
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- Virtualizing clinical cases of atrial flutter in a fast marching simulation including conduction velocity and ablation scars
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- Mesh structure-independent modeling of patient-specific atrial fiber orientation
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- Accelerating mono-domain cardiac electrophysiology simulations using OpenCL
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- Understanding the cellular mode of action of vernakalant using a computational model: answers and new questions
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- A java based simulator with user interface to simulate ventilated patients
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- Evaluation of an algorithm to choose between competing models of respiratory mechanics
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- Numerical simulation of low-pulsation gerotor pumps for use in the pharmaceutical industry and in biomedicine
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- Numerical and experimental flow analysis in centifluidic systems for rapid allergy screening tests
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- Biomechanical parameter determination of scaffold-free cartilage constructs (SFCCs) with the hyperelastic material models Yeoh, Ogden and Demiray
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- FPGA controlled artificial vascular system
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- Simulation based investigation of source-detector configurations for non-invasive fetal pulse oximetry
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- Test setup for characterizing the efficacy of embolic protection devices
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- Impact of electrode geometry on force generation during functional electrical stimulation
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- 3D-based visual physical activity assessment of children
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- Realtime assessment of foot orientation by Accelerometers and Gyroscopes
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- Image based reconstruction for cystoscopy
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- Image guided surgery innovation with graduate students - a new lecture format
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- Multichannel FES parameterization for controlling foot motion in paretic gait
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- Smartphone supported upper limb prosthesis
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- Use of quantitative tremor evaluation to enhance target selection during deep brain stimulation surgery for essential tremor
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- Evaluation of adhesion promoters for Parylene C on gold metallization
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- The influence of metallic ions from CoCr28Mo6 on the osteogenic differentiation and cytokine release of human osteoblasts
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- Increasing the visibility of thin NITINOL vascular implants
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- Possible reasons for early artificial bone failure in biomechanical tests of ankle arthrodesis systems
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- Development of a bending test procedure for the characterization of flexible ECoG electrode arrays
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- Tubular manipulators: a new concept for intracochlear positioning of an auditory prosthesis
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- Investigation of the dynamic diameter deformation of vascular stents during fatigue testing with radial loading
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- Electrospun vascular grafts with anti-kinking properties
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- Integration of temperature sensors in polyimide-based thin-film electrode arrays
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- Use cases and usability challenges for head-mounted displays in healthcare
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- Device- and service profiles for integrated or systems based on open standards
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- Risk management for medical devices in research projects
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- Simulation of varying femoral attachment sites of medial patellofemoral ligament using a musculoskeletal multi-body model
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- Does enhancing consciousness for strategic planning processes support the effectiveness of problem-based learning concepts in biomedical education?
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- SPIO processing in macrophages for MPI: The breast cancer MPI-SNLB-concept
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- Numerical simulations of airflow in the human pharynx of OSAHS patients