Pub Date : 2016-04-25DOI: 10.1109/TBCAS.2016.2515541
Ahmed Ibrahim, M. Kiani
Power transmission efficiency (PTE) has been the key parameter for wireless power transmission (WPT) to biomedical implants with millimeter (mm) dimensions. It has been suggested that for mm-sized implants increasing the power carrier frequency (fp) of the WPT link to hundreds of MHz improves PTE. However, increasing fp significantly reduces the maximum allowable power that can be transmitted under the specific absorption rate (SAR) constraints. This paper presents a new figure-of-merit (FoM) and a design methodology for optimal WPT to mm-sized implants via inductive coupling by striking a balance between PTE and maximum delivered power under SAR constraints (PL,SAR). First, the optimal mm-sized receiver (Rx) coil geometry is identified for a wide range of fp to maximize the Rx coil quality factor (Q). Secondly, the optimal transmitter (Tx) coil geometry and fp are found to maximize the proposed FoM under a low-loss Rx matched-load condition. Finally, proper Tx coil and tissue spacing is identified based on FoM at the optimal fp. We demonstrate that fp in order of tens of MHz still offer higher PL,SAR and FoM, which is key in applications that demand high power such as optogenetics. An inductive link to power a 1 mm 3 implant was designed based on our FoM and verified through full-wave electromagnetic field simulations and measurements using de-embedding method. In our measurements, an Rx coil with 1 mm diameter, located 10 mm inside the tissue, achieved PTE and PL,SAR of 1.4% and 2.2 mW at fp of 20 MHz, respectively.
{"title":"A Figure-of-Merit for Design and Optimization of Inductive Power Transmission Links for Millimeter-Sized Biomedical Implants","authors":"Ahmed Ibrahim, M. Kiani","doi":"10.1109/TBCAS.2016.2515541","DOIUrl":"https://doi.org/10.1109/TBCAS.2016.2515541","url":null,"abstract":"Power transmission efficiency (PTE) has been the key parameter for wireless power transmission (WPT) to biomedical implants with millimeter (mm) dimensions. It has been suggested that for mm-sized implants increasing the power carrier frequency (fp) of the WPT link to hundreds of MHz improves PTE. However, increasing fp significantly reduces the maximum allowable power that can be transmitted under the specific absorption rate (SAR) constraints. This paper presents a new figure-of-merit (FoM) and a design methodology for optimal WPT to mm-sized implants via inductive coupling by striking a balance between PTE and maximum delivered power under SAR constraints (PL,SAR). First, the optimal mm-sized receiver (Rx) coil geometry is identified for a wide range of fp to maximize the Rx coil quality factor (Q). Secondly, the optimal transmitter (Tx) coil geometry and fp are found to maximize the proposed FoM under a low-loss Rx matched-load condition. Finally, proper Tx coil and tissue spacing is identified based on FoM at the optimal fp. We demonstrate that fp in order of tens of MHz still offer higher PL,SAR and FoM, which is key in applications that demand high power such as optogenetics. An inductive link to power a 1 mm 3 implant was designed based on our FoM and verified through full-wave electromagnetic field simulations and measurements using de-embedding method. In our measurements, an Rx coil with 1 mm diameter, located 10 mm inside the tissue, achieved PTE and PL,SAR of 1.4% and 2.2 mW at fp of 20 MHz, respectively.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"1100-1111"},"PeriodicalIF":5.1,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2016.2515541","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-18DOI: 10.1109/TBCAS.2016.2579164
S. Friedmann, J. Schemmel, Andreas Grübl, Andreas Hartel, Matthias Hock, K. Meier
We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a general-purpose processor with full-custom analog elements. This processor is operating in parallel with a fully parallel neuromorphic system consisting of an array of synapses connected to analog, continuous time neuron circuits. Novel analog correlation sensor circuits process spike events for each synapse in parallel and in real-time. The processor uses this pre-processing to compute new weights possibly using additional information following its program. Therefore, to a certain extent, learning rules can be defined in software giving a large degree of flexibility. Synapses realize correlation detection geared towards Spike-Timing Dependent Plasticity (STDP) as central computational primitive in the analog domain. Operating at a speed-up factor of 1000 compared to biological time-scale, we measure time-constants from tens to hundreds of micro-seconds. We analyze variability across multiple chips and demonstrate learning using a multiplicative STDP rule. We conclude that the presented approach will enable flexible and efficient learning as a platform for neuroscientific research and technological applications.
{"title":"Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System","authors":"S. Friedmann, J. Schemmel, Andreas Grübl, Andreas Hartel, Matthias Hock, K. Meier","doi":"10.1109/TBCAS.2016.2579164","DOIUrl":"https://doi.org/10.1109/TBCAS.2016.2579164","url":null,"abstract":"We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a general-purpose processor with full-custom analog elements. This processor is operating in parallel with a fully parallel neuromorphic system consisting of an array of synapses connected to analog, continuous time neuron circuits. Novel analog correlation sensor circuits process spike events for each synapse in parallel and in real-time. The processor uses this pre-processing to compute new weights possibly using additional information following its program. Therefore, to a certain extent, learning rules can be defined in software giving a large degree of flexibility. Synapses realize correlation detection geared towards Spike-Timing Dependent Plasticity (STDP) as central computational primitive in the analog domain. Operating at a speed-up factor of 1000 compared to biological time-scale, we measure time-constants from tens to hundreds of micro-seconds. We analyze variability across multiple chips and demonstrate learning using a multiplicative STDP rule. We conclude that the presented approach will enable flexible and efficient learning as a platform for neuroscientific research and technological applications.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"11 1","pages":"128-142"},"PeriodicalIF":5.1,"publicationDate":"2016-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2016.2579164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62966029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.1109/TBCAS.2015.2431272
Jeeun Kang, Changhan Yoon, Jae Jin Lee, Sang-Bum Kye, Yongbae Lee, J. Chang, Gi-Duck Kim, Y. Yoo, T. Song
In this paper, we present a novel system-on-chip (SOC) solution for a portable ultrasound imaging system (PUS) for point-of-care applications. The PUS-SOC includes all of the signal processing modules (i.e., the transmit and dynamic receive beamformer modules, mid- and back-end processors, and color Doppler processors) as well as an efficient architecture for hardware-based imaging methods (e.g., dynamic delay calculation, multi-beamforming, and coded excitation and compression). The PUS-SOC was fabricated using a UMC 130-nm NAND process and has 16.8 GFLOPS of computing power with a total equivalent gate count of 12.1 million, which is comparable to a Pentium-4 CPU. The size and power consumption of the PUS-SOC are 27×27 mm2 and 1.2 W, respectively. Based on the PUS-SOC, a prototype hand-held US imaging system was implemented. Phantom experiments demonstrated that the PUS-SOC can provide appropriate image quality for point-of-care applications with a compact PDA size ( 200×120×45 mm3) and 3 hours of battery life.
{"title":"A System-on-Chip Solution for Point-of-Care Ultrasound Imaging Systems: Architecture and ASIC Implementation","authors":"Jeeun Kang, Changhan Yoon, Jae Jin Lee, Sang-Bum Kye, Yongbae Lee, J. Chang, Gi-Duck Kim, Y. Yoo, T. Song","doi":"10.1109/TBCAS.2015.2431272","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2431272","url":null,"abstract":"In this paper, we present a novel system-on-chip (SOC) solution for a portable ultrasound imaging system (PUS) for point-of-care applications. The PUS-SOC includes all of the signal processing modules (i.e., the transmit and dynamic receive beamformer modules, mid- and back-end processors, and color Doppler processors) as well as an efficient architecture for hardware-based imaging methods (e.g., dynamic delay calculation, multi-beamforming, and coded excitation and compression). The PUS-SOC was fabricated using a UMC 130-nm NAND process and has 16.8 GFLOPS of computing power with a total equivalent gate count of 12.1 million, which is comparable to a Pentium-4 CPU. The size and power consumption of the PUS-SOC are 27×27 mm2 and 1.2 W, respectively. Based on the PUS-SOC, a prototype hand-held US imaging system was implemented. Phantom experiments demonstrated that the PUS-SOC can provide appropriate image quality for point-of-care applications with a compact PDA size ( 200×120×45 mm3) and 3 hours of battery life.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"412-423"},"PeriodicalIF":5.1,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2431272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.1109/TBCAS.2015.2420117
Zhaohong Chen, Yongdong Chen, Qinghua Huang
Ultrasound elastography is an important medical imaging tool for characterization of lesions. In this paper, we present a wireless and near real-time 3D ultrasound strain imaging system. It uses a 3D translating device to control a commercial linear ultrasound transducer to collect pre-compression and post-compression radio-frequency (RF) echo signal frames. The RF frames are wirelessly transferred to a high-performance server via a local area network (LAN). A dynamic programming strain estimation algorithm is implemented with the compute unified device architecture (CUDA) on the graphic processing unit (GPU) in the server to calculate the strain image after receiving a pre-compression RF frame and a post-compression RF frame at the same position. Each strain image is inserted into a strain volume which can be rendered in near real-time. We take full advantage of the translating device to precisely control the probe movement and compression. The GPU-based parallel computing techniques are designed to reduce the computation time. Phantom and in vivo experimental results demonstrate that our system can generate strain volumes with good quality and display an incrementally reconstructed volume image in near real-time.
{"title":"Development of a Wireless and Near Real-Time 3D Ultrasound Strain Imaging System","authors":"Zhaohong Chen, Yongdong Chen, Qinghua Huang","doi":"10.1109/TBCAS.2015.2420117","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2420117","url":null,"abstract":"Ultrasound elastography is an important medical imaging tool for characterization of lesions. In this paper, we present a wireless and near real-time 3D ultrasound strain imaging system. It uses a 3D translating device to control a commercial linear ultrasound transducer to collect pre-compression and post-compression radio-frequency (RF) echo signal frames. The RF frames are wirelessly transferred to a high-performance server via a local area network (LAN). A dynamic programming strain estimation algorithm is implemented with the compute unified device architecture (CUDA) on the graphic processing unit (GPU) in the server to calculate the strain image after receiving a pre-compression RF frame and a post-compression RF frame at the same position. Each strain image is inserted into a strain volume which can be rendered in near real-time. We take full advantage of the translating device to precisely control the probe movement and compression. The GPU-based parallel computing techniques are designed to reduce the computation time. Phantom and in vivo experimental results demonstrate that our system can generate strain volumes with good quality and display an incrementally reconstructed volume image in near real-time.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"227 1","pages":"394-403"},"PeriodicalIF":5.1,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2420117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.1109/TBCAS.2015.2435256
Md. Shamsul Arefin, Jean-Michel Redouté, M. Yuce
This paper presents an interface circuit for capacitive and inductive MEMS biosensors using an oscillator and a charge pump based frequency-to-voltage converter. Frequency modulation using a differential crossed coupled oscillator is adopted to sense capacitive and inductive changes. The frequency-to-voltage converter is designed with a negative feedback system and external controlling parameters to adjust the sensitivity, dynamic range, and nominal point for the measurement. The sensitivity of the frequency-to-voltage converter is from 13.28 to 35.96 mV/MHz depending on external voltage and charging current. The sensitivity ranges of the capacitive and inductive interface circuit are 17.08 to 54.4 mV/pF and 32.11 to 82.88 mV/mH, respectively. A capacitive MEMS based pH sensor is also connected with the interface circuit to measure the high acidic gastric acid throughout the digestive tract. The sensitivity for pH from 1 to 3 is 191.4 mV/pH with 550 μV pp noise. The readout circuit is designed and fabricated using the UMC 0.18 μm CMOS technology. It occupies an area of 0.18 mm 2 and consumes 11.8 mW.
{"title":"A MEMS Interface IC With Low-Power and Wide-Range Frequency-to-Voltage Converter for Biomedical Applications","authors":"Md. Shamsul Arefin, Jean-Michel Redouté, M. Yuce","doi":"10.1109/TBCAS.2015.2435256","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2435256","url":null,"abstract":"This paper presents an interface circuit for capacitive and inductive MEMS biosensors using an oscillator and a charge pump based frequency-to-voltage converter. Frequency modulation using a differential crossed coupled oscillator is adopted to sense capacitive and inductive changes. The frequency-to-voltage converter is designed with a negative feedback system and external controlling parameters to adjust the sensitivity, dynamic range, and nominal point for the measurement. The sensitivity of the frequency-to-voltage converter is from 13.28 to 35.96 mV/MHz depending on external voltage and charging current. The sensitivity ranges of the capacitive and inductive interface circuit are 17.08 to 54.4 mV/pF and 32.11 to 82.88 mV/mH, respectively. A capacitive MEMS based pH sensor is also connected with the interface circuit to measure the high acidic gastric acid throughout the digestive tract. The sensitivity for pH from 1 to 3 is 191.4 mV/pH with 550 μV pp noise. The readout circuit is designed and fabricated using the UMC 0.18 μm CMOS technology. It occupies an area of 0.18 mm 2 and consumes 11.8 mW.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"455-466"},"PeriodicalIF":5.1,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2435256","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-24DOI: 10.1109/TBCAS.2015.2512443
Zhicong Luo, M. Ker
This paper presents a 4 × VDD neuro-stimulator in a 0.18- μm 1.8 V/3.3 V CMOS process. The self-adaption bias technique and stacked MOS configuration are used to prevent transistors from the electrical overstress and gate-oxide reliability issue. A high-voltage-tolerant level shifter with power-on protection is used to drive the neuro-stimulator The reliability measurement of up to 100 million periodic cycles with 3000- μA biphasic stimulations in 12-V power supply has verified that the proposed neuro-stimulator is robust. Precise charge balance is achieved by using a novel current memory cell with the dual calibration loops and leakage current compensation. The charge mismatch is down to 0.25% over all the stimulus current ranges (200-300 μA) The residual average dc current is less than 6.6 nA after shorting operation.
{"title":"A High-Voltage-Tolerant and Precise Charge-Balanced Neuro-Stimulator in Low Voltage CMOS Process","authors":"Zhicong Luo, M. Ker","doi":"10.1109/TBCAS.2015.2512443","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2512443","url":null,"abstract":"This paper presents a 4 × VDD neuro-stimulator in a 0.18- μm 1.8 V/3.3 V CMOS process. The self-adaption bias technique and stacked MOS configuration are used to prevent transistors from the electrical overstress and gate-oxide reliability issue. A high-voltage-tolerant level shifter with power-on protection is used to drive the neuro-stimulator The reliability measurement of up to 100 million periodic cycles with 3000- μA biphasic stimulations in 12-V power supply has verified that the proposed neuro-stimulator is robust. Precise charge balance is achieved by using a novel current memory cell with the dual calibration loops and leakage current compensation. The charge mismatch is down to 0.25% over all the stimulus current ranges (200-300 μA) The residual average dc current is less than 6.6 nA after shorting operation.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"1087-1099"},"PeriodicalIF":5.1,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2512443","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-26DOI: 10.1109/TBCAS.2016.2514522
H. Ando, K. Takizawa, Takeshi Yoshida, Kojiro Matsushita, M. Hirata, Takafumi Suzuki
Simultaneous recordings of neural activity at large scale, in the long term and under bio-safety conditions, can provide essential data. These data can be used to advance the technology for brain-machine interfaces in clinical applications, and to understand brain function. For this purpose, we present a new multichannel neural recording system that can record up to 4096-channel (ch) electrocorticogram data by multiple connections of customized application-specific integrated circuits (ASICs). The ASIC includes 64-ch low-noise amplifiers, analog time-division multiplexers, and 12-bit successive approximation register ADCs. Recorded data sampled at a rate of 1 kS/s are multiplexed with time division via an integrated multiplex board, and in total 51.2 Mbps of raw data for 4096 ch are generated. This system has an ultra-wideband (UWB) wireless unit for transmitting the recorded neural signals. The ASICs, multiplex boards, and UWB transmitter unit are designed with the aim of implanting them. From preliminary experiments with a human body-equivalent liquid phantom, we confirmed 4096-ch UWB wireless data transmission at 128 Mbps for distances below 20 mm .
{"title":"Wireless Multichannel Neural Recording With a 128-Mbps UWB Transmitter for an Implantable Brain-Machine Interfaces","authors":"H. Ando, K. Takizawa, Takeshi Yoshida, Kojiro Matsushita, M. Hirata, Takafumi Suzuki","doi":"10.1109/TBCAS.2016.2514522","DOIUrl":"https://doi.org/10.1109/TBCAS.2016.2514522","url":null,"abstract":"Simultaneous recordings of neural activity at large scale, in the long term and under bio-safety conditions, can provide essential data. These data can be used to advance the technology for brain-machine interfaces in clinical applications, and to understand brain function. For this purpose, we present a new multichannel neural recording system that can record up to 4096-channel (ch) electrocorticogram data by multiple connections of customized application-specific integrated circuits (ASICs). The ASIC includes 64-ch low-noise amplifiers, analog time-division multiplexers, and 12-bit successive approximation register ADCs. Recorded data sampled at a rate of 1 kS/s are multiplexed with time division via an integrated multiplex board, and in total 51.2 Mbps of raw data for 4096 ch are generated. This system has an ultra-wideband (UWB) wireless unit for transmitting the recorded neural signals. The ASICs, multiplex boards, and UWB transmitter unit are designed with the aim of implanting them. From preliminary experiments with a human body-equivalent liquid phantom, we confirmed 4096-ch UWB wireless data transmission at 128 Mbps for distances below 20 mm .","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"1068-1078"},"PeriodicalIF":5.1,"publicationDate":"2016-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2016.2514522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-03DOI: 10.1109/TBCAS.2015.2502538
Rene Harder, A. Diedrich, Jonathan S. Whitfield, M. Buchowski, J. Pietsch, F. Baudenbacher
Bioelectrical impedance analysis (BIA) is a noninvasive and commonly used method for the assessment of body composition including body water. We designed a small, portable and wireless multi-frequency impedance spectrometer based on the 12 bit impedance network analyzer AD5933 and a precision wide-band constant current source for tetrapolar whole body impedance measurements. The impedance spectrometer communicates via Bluetooth with mobile devices (smart phone or tablet computer) that provide user interface for patient management and data visualization. The export of patient measurement results into a clinical research database facilitates the aggregation of bioelectrical impedance analysis and biolectrical impedance vector analysis (BIVA) data across multiple subjects and/or studies. The performance of the spectrometer was evaluated using a passive tissue equivalent circuit model as well as a comparison of body composition changes assessed with bioelectrical impedance and dual-energy X-ray absorptiometry (DXA) in healthy volunteers. Our results show an absolute error of 1% for resistance and 5% for reactance measurements in the frequency range of 3 kHz to 150 kHz. A linear regression of BIA and DXA fat mass estimations showed a strong correlation (r2=0.985) between measures with a maximum absolute error of 6.5%. The simplicity of BIA measurements, a cost effective design and the simple visual representation of impedance data enables patients to compare and determine body composition during the time course of a specific treatment plan in a clinical or home environment.
{"title":"Smart Multi-Frequency Bioelectrical Impedance Spectrometer for BIA and BIVA Applications","authors":"Rene Harder, A. Diedrich, Jonathan S. Whitfield, M. Buchowski, J. Pietsch, F. Baudenbacher","doi":"10.1109/TBCAS.2015.2502538","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2502538","url":null,"abstract":"Bioelectrical impedance analysis (BIA) is a noninvasive and commonly used method for the assessment of body composition including body water. We designed a small, portable and wireless multi-frequency impedance spectrometer based on the 12 bit impedance network analyzer AD5933 and a precision wide-band constant current source for tetrapolar whole body impedance measurements. The impedance spectrometer communicates via Bluetooth with mobile devices (smart phone or tablet computer) that provide user interface for patient management and data visualization. The export of patient measurement results into a clinical research database facilitates the aggregation of bioelectrical impedance analysis and biolectrical impedance vector analysis (BIVA) data across multiple subjects and/or studies. The performance of the spectrometer was evaluated using a passive tissue equivalent circuit model as well as a comparison of body composition changes assessed with bioelectrical impedance and dual-energy X-ray absorptiometry (DXA) in healthy volunteers. Our results show an absolute error of 1% for resistance and 5% for reactance measurements in the frequency range of 3 kHz to 150 kHz. A linear regression of BIA and DXA fat mass estimations showed a strong correlation (r2=0.985) between measures with a maximum absolute error of 6.5%. The simplicity of BIA measurements, a cost effective design and the simple visual representation of impedance data enables patients to compare and determine body composition during the time course of a specific treatment plan in a clinical or home environment.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"912-919"},"PeriodicalIF":5.1,"publicationDate":"2016-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2502538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-01-22DOI: 10.1109/TBCAS.2015.2495272
A. Mansano, Yongjia Li, S. Bagga, W. Serdijn
The design of a 13.56 MHz/402 MHz autonomous wireless sensor node with asynchronous ECG monitoring for near field communication is presented. The sensor node consists of an RF energy harvester (RFEH), a power management unit, an ECG readout, a data encoder and an RF backscattering transmitter. The energy harvester supplies the system with 1.25 V and offers a power conversion efficiency of 19% from a -13 dBm RF source at 13.56 MHz. The power management unit regulates the output voltage of the RFEH to supply the ECG readout with VECG = 0.95 V and the data encoder with VDE = 0.65 V . The ECG readout comprises an analog front-end (low noise amplifier and programmable voltage to current converter) and an asynchronous level crossing ADC with 8 bits resolution. The ADC output is encoded by a pulse generator that drives a backscattering transmitter at 402 MHz. The total power consumption of the sensor node circuitry is 9.7 μW for a data rate of 90 kb/s and a heart rate of 70 bpm. The chip has been designed in a 0.18 μm CMOS process and shows superior RF input power sensitivity and lower power consumption when compared to previous works.
{"title":"An Autonomous Wireless Sensor Node With Asynchronous ECG Monitoring in 0.18 $mu$ m CMOS","authors":"A. Mansano, Yongjia Li, S. Bagga, W. Serdijn","doi":"10.1109/TBCAS.2015.2495272","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2495272","url":null,"abstract":"The design of a 13.56 MHz/402 MHz autonomous wireless sensor node with asynchronous ECG monitoring for near field communication is presented. The sensor node consists of an RF energy harvester (RFEH), a power management unit, an ECG readout, a data encoder and an RF backscattering transmitter. The energy harvester supplies the system with 1.25 V and offers a power conversion efficiency of 19% from a -13 dBm RF source at 13.56 MHz. The power management unit regulates the output voltage of the RFEH to supply the ECG readout with VECG = 0.95 V and the data encoder with VDE = 0.65 V . The ECG readout comprises an analog front-end (low noise amplifier and programmable voltage to current converter) and an asynchronous level crossing ADC with 8 bits resolution. The ADC output is encoded by a pulse generator that drives a backscattering transmitter at 402 MHz. The total power consumption of the sensor node circuitry is 9.7 μW for a data rate of 90 kb/s and a heart rate of 70 bpm. The chip has been designed in a 0.18 μm CMOS process and shows superior RF input power sensitivity and lower power consumption when compared to previous works.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"602-611"},"PeriodicalIF":5.1,"publicationDate":"2016-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2495272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-01-20DOI: 10.1109/TBCAS.2015.2496420
J. Schachtele
In-stent restenosis is a frequent complication after stent implantation. This article investigates the design of a passive sensor system to be integrated into a stent for the detection of an in-stent restenosis by measuring the local pulse wave velocity (PWV). The proposed system uses two resonant circuits consisting of a capacitive pressure sensor and a coil as transponders. The pressure sensors are located at the proximal and distal end of the stent. An alternating external magnetic field with a constant frequency is applied such that the resonance frequencies of the transponders cross the excitation frequency when the pulse wave passes. The time delay between the resonances at the transponders can be captured to obtain the PWV. A model for the measurement system and a correlation between transponder design parameters and minimal resolvable time delay are derived. This correlation is based on the criterion that the 3 dB bandwidth of the transponder resonances may not overlap in the measurement time interval. This correlation can be used to design and analyze a transponder system for the proposed measurement system. In an experiment, in which the pressure sensors have been emulated by varactor diodes, it could be shown that the model is valid and that the criterion is suitable. Finally, the relevant design parameters of the transponders have been identified and their limitations investigated.
{"title":"On the Design of Passive Resonant Circuits to Measure Local Pulse Wave Velocity in a Stent","authors":"J. Schachtele","doi":"10.1109/TBCAS.2015.2496420","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2496420","url":null,"abstract":"In-stent restenosis is a frequent complication after stent implantation. This article investigates the design of a passive sensor system to be integrated into a stent for the detection of an in-stent restenosis by measuring the local pulse wave velocity (PWV). The proposed system uses two resonant circuits consisting of a capacitive pressure sensor and a coil as transponders. The pressure sensors are located at the proximal and distal end of the stent. An alternating external magnetic field with a constant frequency is applied such that the resonance frequencies of the transponders cross the excitation frequency when the pulse wave passes. The time delay between the resonances at the transponders can be captured to obtain the PWV. A model for the measurement system and a correlation between transponder design parameters and minimal resolvable time delay are derived. This correlation is based on the criterion that the 3 dB bandwidth of the transponder resonances may not overlap in the measurement time interval. This correlation can be used to design and analyze a transponder system for the proposed measurement system. In an experiment, in which the pressure sensors have been emulated by varactor diodes, it could be shown that the model is valid and that the criterion is suitable. Finally, the relevant design parameters of the transponders have been identified and their limitations investigated.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"612-622"},"PeriodicalIF":5.1,"publicationDate":"2016-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2496420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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