Pub Date : 2008-11-20DOI: 10.1109/BIOCAS.2008.4696908
T. Constandinou, J. Georgiou
This paper describes a novel analogue circuit for extracting the tilt angle from the output of a standard MEMS accelerometer. The circuit uses the accelerometer signal together with the gravitational acceleration vector to generate the tilt signal. Using a current-mode representation with devices operated in subthreshold, the appropriate trigonometric function has been realised to compute tilt. Furthermore, implementing a long-time constant filter to extract the mean tilt level provides adaptation to the static tilt level. Specifically, this circuit has been designed as part of an implantable vestibular prosthesis to provide inclination signals for bypassing dysfunctional otolith end-organs. The hardware has been implemented in AMS 0.35 mum 2P4M CMOS technology.
本文描述了一种从标准MEMS加速度计输出中提取倾斜角度的新型模拟电路。该电路利用加速度计信号与重力加速度矢量一起产生倾斜信号。使用电流模式表示与设备在亚阈值操作,适当的三角函数已经实现计算倾斜。此外,实现一个长时间的恒定滤波器来提取平均倾斜水平提供了对静态倾斜水平的适应。具体来说,该电路被设计为植入式前庭假体的一部分,为绕过功能失调的耳石末端器官提供倾斜信号。硬件采用AMS 0.35 μ m 2P4M CMOS技术实现。
{"title":"A micropower tilt processing circuit","authors":"T. Constandinou, J. Georgiou","doi":"10.1109/BIOCAS.2008.4696908","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696908","url":null,"abstract":"This paper describes a novel analogue circuit for extracting the tilt angle from the output of a standard MEMS accelerometer. The circuit uses the accelerometer signal together with the gravitational acceleration vector to generate the tilt signal. Using a current-mode representation with devices operated in subthreshold, the appropriate trigonometric function has been realised to compute tilt. Furthermore, implementing a long-time constant filter to extract the mean tilt level provides adaptation to the static tilt level. Specifically, this circuit has been designed as part of an implantable vestibular prosthesis to provide inclination signals for bypassing dysfunctional otolith end-organs. The hardware has been implemented in AMS 0.35 mum 2P4M CMOS technology.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124131112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-20DOI: 10.1109/BIOCAS.2008.4696879
E. Mangieri, A. Ahmadi, K. Maharatna, S. Ahmad, P. Chappell
This paper presents a compact analogue circuit for the controlling of prosthetic hands. The circuit captures directly surface EMG signals as the input by which the user will be able to select different postures. The proposed circuit is able to work using only one EMG source targeting patients with different levels of amputation. It is also adaptable for different users with different EMG amplitude signals and the motion of each finger can be varied in the circuit even with the single EMG. Real captured EMG signals are applied to the design and simulation results demonstrate the capability of the circuit in processing EMG signals and controlling the prosthetic hand in an efficient way. The circuit is designed and implemented with 0.12 mum CMOS technology and consumes 4 mW power for a set of sample postures.
本文提出了一种用于假肢控制的小型模拟电路。电路直接捕获表面肌电信号作为输入,用户将能够选择不同的姿势。所提出的电路能够仅使用针对不同截肢程度患者的一个肌电图源工作。它还可以适应不同的用户,具有不同的肌电信号振幅信号,即使是单个肌电信号,也可以在电路中改变每个手指的运动。将实际捕获的肌电信号应用于设计,仿真结果验证了该电路对肌电信号的处理能力和对假手的有效控制。该电路采用0.12 μ m CMOS技术设计和实现,一组采样姿势功耗为4 mW。
{"title":"A novel analogue circuit for controlling prosthetic hands","authors":"E. Mangieri, A. Ahmadi, K. Maharatna, S. Ahmad, P. Chappell","doi":"10.1109/BIOCAS.2008.4696879","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696879","url":null,"abstract":"This paper presents a compact analogue circuit for the controlling of prosthetic hands. The circuit captures directly surface EMG signals as the input by which the user will be able to select different postures. The proposed circuit is able to work using only one EMG source targeting patients with different levels of amputation. It is also adaptable for different users with different EMG amplitude signals and the motion of each finger can be varied in the circuit even with the single EMG. Real captured EMG signals are applied to the design and simulation results demonstrate the capability of the circuit in processing EMG signals and controlling the prosthetic hand in an efficient way. The circuit is designed and implemented with 0.12 mum CMOS technology and consumes 4 mW power for a set of sample postures.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115700098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696947
Holger Harms, Oliver Amft, G. Tröster
Several smart sensing garments have been proposed for postural and movement rehabilitation. Existing systems require a tight-fitting of the garment at body segments and precise sensor positioning. In this work, we analyzed errors of a loose-fitting sensing garment on the automatic recognition of 21 postures, relevant in shoulder and elbow-rehabilitation. The recognition performance of garment-attached acceleration sensors and additional skin-attached references was compared to discuss challenges in a garment-based classification of postures. The analysis was done with one fixed-size shirt worn by seven participants of varying body proportions. The classification accuracy using data from garment-integrated sensors was on average 13% lower compared to that of skin-attached reference sensors. This relation remained constant even after selecting an optimal input feature set. For garment-attached sensors, we observed that the loss in classification accuracy decreased, if the body dimension increased. Moreover, the alignment error of individual postures was analyzed, to identify movements and postures that are particularly affected by garment fitting aspects. Contrarily, we showed that 14 of the 21 rehabilitation-relevant postures result in a low sensor alignment error. We believe that these results indicate critical design aspects for the deployment of comfortable garments in movement rehabilitation and should be considered in garment and posture selection.
{"title":"Influence of a loose-fitting sensing garment on posture recognition in rehabilitation","authors":"Holger Harms, Oliver Amft, G. Tröster","doi":"10.1109/BIOCAS.2008.4696947","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696947","url":null,"abstract":"Several smart sensing garments have been proposed for postural and movement rehabilitation. Existing systems require a tight-fitting of the garment at body segments and precise sensor positioning. In this work, we analyzed errors of a loose-fitting sensing garment on the automatic recognition of 21 postures, relevant in shoulder and elbow-rehabilitation. The recognition performance of garment-attached acceleration sensors and additional skin-attached references was compared to discuss challenges in a garment-based classification of postures. The analysis was done with one fixed-size shirt worn by seven participants of varying body proportions. The classification accuracy using data from garment-integrated sensors was on average 13% lower compared to that of skin-attached reference sensors. This relation remained constant even after selecting an optimal input feature set. For garment-attached sensors, we observed that the loss in classification accuracy decreased, if the body dimension increased. Moreover, the alignment error of individual postures was analyzed, to identify movements and postures that are particularly affected by garment fitting aspects. Contrarily, we showed that 14 of the 21 rehabilitation-relevant postures result in a low sensor alignment error. We believe that these results indicate critical design aspects for the deployment of comfortable garments in movement rehabilitation and should be considered in garment and posture selection.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696936
Y. Xie, Y. Wang, F. Azizi, C. Mastrangelo
We have fabricated and tested minimum sized (25times25 mum2) pneumatic valves that can be easily integrated within two-level PDMS microfluidic chips. Minimum valve footprint is achieved through the reduction of the valve gap (0-3 mum) and the incorporation of an anti-stiction teflon valve seat that prevents the bonding of the valve diaphragm during chip assembly. The pneumatic teflon-seated valves can be actuated with a pressure differential of 25 PSI using conventional PDMS control valve hardware. The microvalve flow resistance of 3.5 PSImiddotsmiddotL-1 was estimated from flow visualization measurements The microvalves can switch flows up to 5 Hz frequencies.
{"title":"Teflon-seated one-lambda microvalves for PDMS chips","authors":"Y. Xie, Y. Wang, F. Azizi, C. Mastrangelo","doi":"10.1109/BIOCAS.2008.4696936","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696936","url":null,"abstract":"We have fabricated and tested minimum sized (25times25 mum2) pneumatic valves that can be easily integrated within two-level PDMS microfluidic chips. Minimum valve footprint is achieved through the reduction of the valve gap (0-3 mum) and the incorporation of an anti-stiction teflon valve seat that prevents the bonding of the valve diaphragm during chip assembly. The pneumatic teflon-seated valves can be actuated with a pressure differential of 25 PSI using conventional PDMS control valve hardware. The microvalve flow resistance of 3.5 PSImiddotsmiddotL-1 was estimated from flow visualization measurements The microvalves can switch flows up to 5 Hz frequencies.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122513804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696901
P. Hafliger, E. Johannessen
We have developed an ultra low power integrated circuit control module that will be incorporated into a micro machined pill-sized medical implant that continuously monitors blood-sugar levels for patients with Diabetes mellitus. The circuit converts a piezoresistive sensor signal to an inter-pulse interval suited for digital transmission through a wire-less inductive link. Instead of a full analog-to-digital conversion, this analog-to-analog conversion is much simpler and more power conservative. The circuit is entirely asynchronous, requiring no energy consuming clock and operates on sub-threshold currents. A first prototype, produced with the STM 90 nm CMOS process, consumes 1.7muW. A compact on-chip resistive element is employed in a feedback loop to cancel 1/f-noise and offsets in both the sensor and the initial amplification stage. The resistive element is implemented using the quantum effect of gate-leakage, achieving an equivalent resistance of several GOmega with minimal consumption of layout space. The effectiveness of this noise reduction has been asserted in a 62 hour recording with fixed input. The measured noise spectrum appears completely white down to the minimal frequency of the recording, i.e. 4.5muHz. The standard deviation of single pulse intervals (dynamic range from 4.3ms to 15.4 ms) restricts the reconstruction of the sensor value to an accuracy equivalent to 4.41 bits. Averaging over the samples during 1 second increases this accuracy to 7.84 bits. Longer averaging will further improve that figure at the cost of longer periods of active power consumption of the implant, which will be woken up only once every 5 minutes.
{"title":"Analog to interval encoder with active use of gate leakage for an implanted blood-sugar sensor","authors":"P. Hafliger, E. Johannessen","doi":"10.1109/BIOCAS.2008.4696901","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696901","url":null,"abstract":"We have developed an ultra low power integrated circuit control module that will be incorporated into a micro machined pill-sized medical implant that continuously monitors blood-sugar levels for patients with Diabetes mellitus. The circuit converts a piezoresistive sensor signal to an inter-pulse interval suited for digital transmission through a wire-less inductive link. Instead of a full analog-to-digital conversion, this analog-to-analog conversion is much simpler and more power conservative. The circuit is entirely asynchronous, requiring no energy consuming clock and operates on sub-threshold currents. A first prototype, produced with the STM 90 nm CMOS process, consumes 1.7muW. A compact on-chip resistive element is employed in a feedback loop to cancel 1/f-noise and offsets in both the sensor and the initial amplification stage. The resistive element is implemented using the quantum effect of gate-leakage, achieving an equivalent resistance of several GOmega with minimal consumption of layout space. The effectiveness of this noise reduction has been asserted in a 62 hour recording with fixed input. The measured noise spectrum appears completely white down to the minimal frequency of the recording, i.e. 4.5muHz. The standard deviation of single pulse intervals (dynamic range from 4.3ms to 15.4 ms) restricts the reconstruction of the sensor value to an accuracy equivalent to 4.41 bits. Averaging over the samples during 1 second increases this accuracy to 7.84 bits. Longer averaging will further improve that figure at the cost of longer periods of active power consumption of the implant, which will be woken up only once every 5 minutes.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123019622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696919
F. Tenore, R. Etienne-Cummings
Rhythmic motions of lower and upper limb prostheses for patients suffering from spinal cord injury (SCI) and amputees can be controlled and modulated using silicon neurons, designed in very large scale integration (VLSI) technology, that mimic pattern generation circuits found in the human spinal cord. Furthermore, synchronized patterns with arbitrarily phase delays, can easily be implemented using this technology. This allows locomotory gaits of any kind to be programmed in silico to control bipedal robotic locomotion. We argue that it is possible to use these circuits to control hand movements in prosthetic upper limbs using the same approach: the neuronspsila oscillatory behavior can trigger rhythmic movements that can be started or stopped at any phase, thus enabling the production of discrete movements in upper limb prosthesis. The bold endeavor of discovering an all-encompassing solution for control of upper and lower limbs will open up new perspectives in the fields of both robotics and prosthetics. In the process of doing so, we have shown how to successfully decode myoelectric signals from able bodied subjects and a transradial amputee, and how the technology developed is suitable for real-time applications, particularly multi-DoF upper limb prostheses. The systems developed in this work have been validated on different platforms dependent on the type of prosthesis required. For lower limb prostheses, a bipedal robot with servomotors actuating its hips and knees was used to prototype walking motions generated by silicon neurons. Upper limb (finger) control was achieved on a Virtual Integration Environment (VIE), developed by JHU's Applied Physics Laboratory (JHUAPL), characterized by real-time processing and visualization of any upper limb motion.
{"title":"Biomorphic circuits and systems: Control of robotic and prosthetic limbs","authors":"F. Tenore, R. Etienne-Cummings","doi":"10.1109/BIOCAS.2008.4696919","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696919","url":null,"abstract":"Rhythmic motions of lower and upper limb prostheses for patients suffering from spinal cord injury (SCI) and amputees can be controlled and modulated using silicon neurons, designed in very large scale integration (VLSI) technology, that mimic pattern generation circuits found in the human spinal cord. Furthermore, synchronized patterns with arbitrarily phase delays, can easily be implemented using this technology. This allows locomotory gaits of any kind to be programmed in silico to control bipedal robotic locomotion. We argue that it is possible to use these circuits to control hand movements in prosthetic upper limbs using the same approach: the neuronspsila oscillatory behavior can trigger rhythmic movements that can be started or stopped at any phase, thus enabling the production of discrete movements in upper limb prosthesis. The bold endeavor of discovering an all-encompassing solution for control of upper and lower limbs will open up new perspectives in the fields of both robotics and prosthetics. In the process of doing so, we have shown how to successfully decode myoelectric signals from able bodied subjects and a transradial amputee, and how the technology developed is suitable for real-time applications, particularly multi-DoF upper limb prostheses. The systems developed in this work have been validated on different platforms dependent on the type of prosthesis required. For lower limb prostheses, a bipedal robot with servomotors actuating its hips and knees was used to prototype walking motions generated by silicon neurons. Upper limb (finger) control was achieved on a Virtual Integration Environment (VIE), developed by JHU's Applied Physics Laboratory (JHUAPL), characterized by real-time processing and visualization of any upper limb motion.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114517165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696950
Chulgyu Song, Keo-Sik Kim, Y. An, Jeong-Hwan Seo
A conventional voiding cystometry involves artificially filling the bladder with saline and reproduce their symptoms, while making precise measurements in order to identify their underlying causes. However, it is difficult to evaluate physiological functions during storage and voiding of the bladder. In this study, we constructed a portable cystometry device based on hand-held mobile computer, personal digital assistance (PDA), and evaluated its clinical utilities while applying this device to natural filling cystometry study. The range of errors of the pressure signals measured our constructed device was less than 1 cm H2O, and the reproducibility of two pressure channels were 2.32 plusmn 2.97 and 3.67 plusmn 5.31 %, respectively. Also, the clinical assessment of our device showed that the system has the capability to accurately monitor the types of information that contribute to the diagnosis and management of patients.
传统的排尿膀胱术包括人工地用生理盐水填充膀胱并重现其症状,同时进行精确的测量以确定其潜在原因。然而,膀胱在储存和排尿过程中的生理功能难以评估。在本研究中,我们构建了一种基于手持移动计算机、个人数字辅助(PDA)的便携式膀胱造口仪,并评估了其在自然充盈膀胱造口研究中的临床应用。该装置测得的压力信号误差范围小于1 cm H2O,两个压力通道的重现性分别为2.32±2.97和3.67±5.31%。此外,对我们设备的临床评估表明,该系统具有准确监测有助于患者诊断和管理的信息类型的能力。
{"title":"Development of portable cystometry device based on hand-held mobile computer","authors":"Chulgyu Song, Keo-Sik Kim, Y. An, Jeong-Hwan Seo","doi":"10.1109/BIOCAS.2008.4696950","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696950","url":null,"abstract":"A conventional voiding cystometry involves artificially filling the bladder with saline and reproduce their symptoms, while making precise measurements in order to identify their underlying causes. However, it is difficult to evaluate physiological functions during storage and voiding of the bladder. In this study, we constructed a portable cystometry device based on hand-held mobile computer, personal digital assistance (PDA), and evaluated its clinical utilities while applying this device to natural filling cystometry study. The range of errors of the pressure signals measured our constructed device was less than 1 cm H2O, and the reproducibility of two pressure channels were 2.32 plusmn 2.97 and 3.67 plusmn 5.31 %, respectively. Also, the clinical assessment of our device showed that the system has the capability to accurately monitor the types of information that contribute to the diagnosis and management of patients.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129165382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696871
M. Mollazadeh, K. Murari, H. Schwerdt, Xinghua Wang, N. Thakor, G. Cauwenberghs
Implantable brain-machine interfaces for disease diagnosis and motor prostheses control require low-power acquisition of neuropotentials spanning a wide range of amplitudes and frequencies. Here, we present a 16-channel VLSI neuropotential acquisition system with tunable gain and bandwidth, and variable rate digital transmission over an inductive link which further supplies power. The neuropotential interface chip is composed of an amplifier, incremental ADC and bit-serial readout circuitry. The front-end amplifier has a midband gain of 40 dB and offers NEF of less than 3 for all bandwidth settings. It also features adjustable low-frequency cut-off from 0.2 to 94 Hz, and independent high-frequency cut-off from 140 Hz to 8.2 kHz. The Gm-C incremental DeltaSigma ADC offers digital gain up to 4096 and 8-12 bits resolution. The interface circuit is powered by a telemetry chip which harvests power through inductive coupling from a 4 MHz link, provides a 1 MHz clock for ADC operation and transmits the bit-serial data of the neurpotential interface across 4 cm at up to 32 kbps with a BER less than 10-5. Experimental EEG recordings using the neuropotential interface and wireless module are presented.
{"title":"Wireless multichannel acquisition of neuropotentials","authors":"M. Mollazadeh, K. Murari, H. Schwerdt, Xinghua Wang, N. Thakor, G. Cauwenberghs","doi":"10.1109/BIOCAS.2008.4696871","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696871","url":null,"abstract":"Implantable brain-machine interfaces for disease diagnosis and motor prostheses control require low-power acquisition of neuropotentials spanning a wide range of amplitudes and frequencies. Here, we present a 16-channel VLSI neuropotential acquisition system with tunable gain and bandwidth, and variable rate digital transmission over an inductive link which further supplies power. The neuropotential interface chip is composed of an amplifier, incremental ADC and bit-serial readout circuitry. The front-end amplifier has a midband gain of 40 dB and offers NEF of less than 3 for all bandwidth settings. It also features adjustable low-frequency cut-off from 0.2 to 94 Hz, and independent high-frequency cut-off from 140 Hz to 8.2 kHz. The Gm-C incremental DeltaSigma ADC offers digital gain up to 4096 and 8-12 bits resolution. The interface circuit is powered by a telemetry chip which harvests power through inductive coupling from a 4 MHz link, provides a 1 MHz clock for ADC operation and transmits the bit-serial data of the neurpotential interface across 4 cm at up to 32 kbps with a BER less than 10-5. Experimental EEG recordings using the neuropotential interface and wireless module are presented.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696923
A. Bonfanti, T. Borghi, R. Gusmeroli, G. Zambra, A. Spinelli, Andriy Oliynyk, L. Fadiga, G. Baranauskas
Since the proof of viability of prosthetic devices directly controlled by neurons, there is a huge increase in the interest on integrated multichannel recording systems to register neural signals with implanted chronic electrodes. One of the bottlenecks in such compact systems is the limited rate of data transmission by the wireless link, requiring some sort of data compression/reduction. We propose an analog low power integrated system for action potential (AP) detection and sorting that reduces the output data rate ~100 times. In this system, AP detection is performed by a double threshold method that reduces the probability of false detections while AP sorting is based on the measurement of peak and trough amplitudes and peak width. The circuit has been implemented in 0.35 - mum CMOS technology with power consumption of 70 muW per channel including the pre-amplifier. The system was tested with real recorded traces: compared to standard AP sorting techniques, the proposed simple AP sorter was able to correctly assign to single units over 90% of detected APs.
由于证明了由神经元直接控制的假肢装置的可行性,人们对集成多通道记录系统的兴趣大大增加,该系统可以用植入的慢性电极记录神经信号。这种紧凑系统的瓶颈之一是无线链路的数据传输速率有限,需要某种形式的数据压缩/缩减。我们提出了一种模拟低功耗集成系统,用于动作电位(AP)检测和分类,可将输出数据速率降低约100倍。在该系统中,AP检测采用双阈值方法,降低了误检的概率,而AP排序则基于峰谷幅度和峰宽的测量。该电路采用0.35 μ m CMOS技术实现,包括前置放大器在内的每通道功耗为70 μ w。用真实记录的轨迹对系统进行了测试:与标准AP分选技术相比,所提出的简单AP分选器能够正确地将超过90%的检测到的AP分配到单个单元。
{"title":"A low-power integrated circuit for analog spike detection and sorting in neural prosthesis systems","authors":"A. Bonfanti, T. Borghi, R. Gusmeroli, G. Zambra, A. Spinelli, Andriy Oliynyk, L. Fadiga, G. Baranauskas","doi":"10.1109/BIOCAS.2008.4696923","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696923","url":null,"abstract":"Since the proof of viability of prosthetic devices directly controlled by neurons, there is a huge increase in the interest on integrated multichannel recording systems to register neural signals with implanted chronic electrodes. One of the bottlenecks in such compact systems is the limited rate of data transmission by the wireless link, requiring some sort of data compression/reduction. We propose an analog low power integrated system for action potential (AP) detection and sorting that reduces the output data rate ~100 times. In this system, AP detection is performed by a double threshold method that reduces the probability of false detections while AP sorting is based on the measurement of peak and trough amplitudes and peak width. The circuit has been implemented in 0.35 - mum CMOS technology with power consumption of 70 muW per channel including the pre-amplifier. The system was tested with real recorded traces: compared to standard AP sorting techniques, the proposed simple AP sorter was able to correctly assign to single units over 90% of detected APs.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128852816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/BIOCAS.2008.4696872
W. Plishker, O. Dandekar, S. Bhattacharyya, R. Shekhar
For the past decade, improving the performance and accuracy of medical image registration has been a driving force of innovation in medical imaging. The ultimate goal of accurate, robust, real-time image registration will enhance diagnoses of patients and enable new image-guided intervention techniques. With such a computationally intensive and multifaceted problem, improvements have been found in high performance platforms such as graphics processors (GPUs) and general purpose clusters, but there has yet to be a solution fast enough and effective enough to gain widespread clinical use. In this study, we examine the differences in accuracy and speed of implementations of the same image registration algorithm on a general purpose uniprocessor, a GPU, and a cluster of GPUs. We utilize a novel domain specific framework that allows us to simultaneously exploit parallelism on a heterogeneous platform. Using a set of representative images, we examine implementations with speedups of up to two orders of magnitude and accuracy varying from sub-millimeter to 2.6 millimeters of average error.
{"title":"Towards systematic exploration of tradeoffs for medical image registration on heterogeneous platforms","authors":"W. Plishker, O. Dandekar, S. Bhattacharyya, R. Shekhar","doi":"10.1109/BIOCAS.2008.4696872","DOIUrl":"https://doi.org/10.1109/BIOCAS.2008.4696872","url":null,"abstract":"For the past decade, improving the performance and accuracy of medical image registration has been a driving force of innovation in medical imaging. The ultimate goal of accurate, robust, real-time image registration will enhance diagnoses of patients and enable new image-guided intervention techniques. With such a computationally intensive and multifaceted problem, improvements have been found in high performance platforms such as graphics processors (GPUs) and general purpose clusters, but there has yet to be a solution fast enough and effective enough to gain widespread clinical use. In this study, we examine the differences in accuracy and speed of implementations of the same image registration algorithm on a general purpose uniprocessor, a GPU, and a cluster of GPUs. We utilize a novel domain specific framework that allows us to simultaneously exploit parallelism on a heterogeneous platform. Using a set of representative images, we examine implementations with speedups of up to two orders of magnitude and accuracy varying from sub-millimeter to 2.6 millimeters of average error.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116198855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}