Medical Instrumentation
Zahra-Sadat Fatemi; Mohammad Mahdi Ahmadi
Volume 12, Issue 3 , November 2018, , Pages 221-234
Abstract
The use of smart medical implants to study the human brain and the interaction of neurons with each other has recently gained much attention. These implants contain microelectrode arrays in which the size of an electrode is in the order of the size of a neuron; therefore they allow recording signals ...
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The use of smart medical implants to study the human brain and the interaction of neurons with each other has recently gained much attention. These implants contain microelectrode arrays in which the size of an electrode is in the order of the size of a neuron; therefore they allow recording signals from single neuron or stimulating a single neuron with considerable precision. Design of such implants entails many challenges, one of which is the design of power and data recovery blocks. In this paper, we describe the design of a new power and data recovery unit for an implantable neural stimulating microsystem. The power recovery unit generates two supply voltages: a 1.8-V supply for the core circuits and a higher supply voltage for the stimulation front-end. An active rectifier is used to generate the 1.8-V supply. The active rectifier achives a 89% power conversion efficiency and 150mV voltage drop with a 3-V sinusoidal input voltage. In order to maximize the efficiency of the stimulation front-end, the supply voltage of that circuit should be adaptively adjusted according to the amplitude of the stimulation current. As a result, a phase-controlled active rectifier is utilized to generate the supply voltage for the neural stimulation front-end. The phase-controlled active rectifier can generate out voltages ranging from 1.8V to 2.5V. Using phase-controlled active rectifier can increase the power conversion efficiency up to 50%. In addition to power recovery, neuroelectrical stimulation microsystems should receive stimulation data from outside of the body. Hence, this paper also circuits required for clock and daterecovery. The data recovery block is able to demodulate the ASK-modulated signal with 3-V to 5-V amplitude and 5% to 25% modulation index.
Medical Instrumentation
Farnaz Fahimi Hanzaee; Mohammad Mehdi Ahmadi
Volume 12, Issue 2 , September 2018, , Pages 147-159
Abstract
Nowadays, implantable electrical neural stimulation is extensively used to treat or alleviate certain brain-related health conditions, such as in deep brain stimulation (DBS) or in vagus nerve stimulation (VNS). In this paper, we present a digital controller block, designed for a neuroelectrical stimulator ...
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Nowadays, implantable electrical neural stimulation is extensively used to treat or alleviate certain brain-related health conditions, such as in deep brain stimulation (DBS) or in vagus nerve stimulation (VNS). In this paper, we present a digital controller block, designed for a neuroelectrical stimulator chip dedicated for a brain implant.The presented design is very power and area-efficient and provides a great flexibibity in programming the specifications of the stimulation pulses. The duration of each stimulation pulse can programmed to be from 4 µs to 4 ms, and the amplitude of each pulse could be from 4 µA to 1 mA. The stimulation pulses could be either monophasic or biphasic, In addition, in biphasic stimulation, the priority of the cathodic pulse over the anodic pulse, or vice versa, could be pragrammed. The interphase delay between the anodic and cathodic phases could be programmed to be between 4 µs and 512 µs. The controller controls 16 stimulation sites, four of which can be stimulated simoultaneualy. The 16 stimulation sites are divided into four groups, each of which is stimulated by a current-controlled stimulation circuit. Each stimulation circuit is controlled by a local digital controller (LDC), which receives its data from a global digital controller (GDC). The designed controller blocks have been implemented and tested on a Spartan-6 field-programmable gate array (FPGA) board, before being implemented as an application-specific integrated circuit (ASIC) layout. The ASIC circuit has been designed using 0.18-µm CMOS technology. Based on the layout, each LDC occupies an area of 19,160 µm2 and consumes 12 µW of power from a 1.8V supply. On the other hand, the GDC takes up an area of 4,246 µm2 and consumes 8.2 µW of power. We have also created a graphical user interface (GUI) to be able to program the stinulation chip.
Medical Instrumentation
Reza Hosseini-Ara; Amir Hossein Karamrezaei; Ali Mokhtarian
Volume 12, Issue 1 , June 2018, , Pages 41-49
Abstract
This study presents a Silicon nano bio-sensor based on modified continuum mechanics model of Euler-Bernoulli beam theory. This cantilever resonant nano-sensor works based on the shift of resonant frequency due to the adsorption of very small particles such as viruses and bacteria. To this end, the surface ...
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This study presents a Silicon nano bio-sensor based on modified continuum mechanics model of Euler-Bernoulli beam theory. This cantilever resonant nano-sensor works based on the shift of resonant frequency due to the adsorption of very small particles such as viruses and bacteria. To this end, the surface of nano bio-sensor is impregnated into a biologically active substance such as Myosin as an adsorbate layer. However, most conducted studies have ignored the effects of mass and stiffness of this adsorbate layer and nonlocal parameter, whereas these factors play a major role in changing the resonant frequency at nano-scale and the precision of mechanical nano bio-sensors. By calculating and regarding all of the mentioned effects, in this study a Silicon nano bio-sensor with a full coverage of the adsorbate layer is precisely analyzed. The results show that the calculation of nonlocal effect reduces the resonant frequency of the nano sensor, and this effect cannot be ignored in the nano-scale. It is also observed that considering the effects of the mass and stiffness of the adsorbate layer separately, may not lead to the exact answer, but the result of both of these effects should be taken into account. In fact, simultaneously considering these effects, it reduces the resonant frequency of nano sensor, which can be useful in designing and analyzing mechanical Silicon nano bio-sensors and increasing the accuracy of their detection. Finally, for the purpose of verification assessment, the numerical results were compared with the results of other studies in the full coverage of the myosin adsorbate layer, which showed complete agreement with them.
Medical Instrumentation
Mohammad Saeed Zare Dehabadi; Mehran Jahed
Volume 10, Issue 3 , October 2016, , Pages 231-244
Abstract
Wireless Body Area Networks (WBAN) consist of a collection of biosensors utilized to remotely monitor the health status of patients. High accuracy anomaly detection and distinguishing between faults and physiological anomalies play a key role in proper detection of real emergency situations and is cruicial ...
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Wireless Body Area Networks (WBAN) consist of a collection of biosensors utilized to remotely monitor the health status of patients. High accuracy anomaly detection and distinguishing between faults and physiological anomalies play a key role in proper detection of real emergency situations and is cruicial in lowering False Alarm Rate (FAR) cases. In this work, a univariate, unsupervised and real-time anomaly detection algorithm is proposed based on Hampel identifier and its performance is compared with previous and reported methods. Furthermore, a novel prediction method is introduced and utilized in order to correct for transient faults that are quite probable in WBANs, due to inherent noise and artifact of physiological sensors. Proposed method is shown to be faster than reported approaches while providing comparable. Final validation of the proposed method is performed by a real experimental dataset along with intentionally added faults and physiological anomalies. The results illustrate appropriate anomaly detection ability of the proposed approach.
Medical Instrumentation
Rasool Baghbani; Mohammad Hasan Moradi
Volume 10, Issue 2 , August 2016, , Pages 149-160
Abstract
In this paper a new idea is suggested for designing an appropriate bio-impedance sensor in the form of a biopsy forceps to measure the electrical properties of the tissues inside the body. First, by analytically solving the Laplace equation for wedge-shaped tissue in the mouth of the forceps, the relationship ...
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In this paper a new idea is suggested for designing an appropriate bio-impedance sensor in the form of a biopsy forceps to measure the electrical properties of the tissues inside the body. First, by analytically solving the Laplace equation for wedge-shaped tissue in the mouth of the forceps, the relationship between electric potential (results from excitation current) in different points on the tissue surface and the electrical properties of the tissue are obtained. Then, to evaluate the designed bio-impedance forceps using the finite element method and the experimental data obtained for different tissues by Gabriel et al., modeling and simulation were done and it was found that the voltages obtained for all of the tissues inside the mouth of the forceps at different frequencies from 50 Hz to 5 MHz, are consistent with that of the analytical method. To investigate the influence of the opening angle of the forceps, measurements were done at different angles and it was found that for small opening angles, measurements are more accurate. Also, electrical properties were measured by changing the size and shape of the tissue and it was found that the designed forceps is non-sensitive and robust to the changes of the volume and shape of the tissue. A prototype of the designed bio-impedance forceps was fabricated. The forceps was experimentally validated by measuring conductivity of the Phosphate Buffered Saline (PBS) solution with different concentrations at frequency range of 50KHz to 1MHz using an impedance analyzer system. To examine the accuracy of measured conductivity values, the Van Der Pauw method was implemented and electrical conductivity of the PBS was measured again. Results showed that measured conductivities by means of the bio-impedance forceps were accurate with an error less than 4%.
