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ABSTRACT: This brief presents a first-order low-pass filter topology capable of providing cutoff frequencies down to 2 mHz with power consumption of 5 nW. The circuit is intended for signal conditioning applications, particularly for use with very low frequency physiological signals in low-power portable medical equipment. To achieve a low-frequency cutoff, the filter is based around the use of a clocked transconductor, which provides low transconductance while using a relatively high bias current level. The circuit is implemented in a 0.35-μm technology with a 1-V supply and has 32- μV<sub>RMS</sub> measured noise and a 64-dB dynamic range. In terms of power consumption and cutoff frequency the reported filter outperforms previous filters from the literature.
Circuits and Systems II: Express Briefs, IEEE Transactions on 07/2011; · 1.41 Impact Factor
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ABSTRACT: This paper presents a low power, low voltage and low frequency bandpass filter implementation of a continuous wavelet transform (CWT) for use with physiological signals in the electroencephalogram (EEG) range (1-150 μV, 1-70 Hz bandwidth). Experimental results are presented for a 1 V, 7th order g<sub>m</sub>C filter based CWT with filter center frequencies ranging from 1 to 64 Hz. Low power and low frequency operation is achieved by biasing the transconductor transistors at low current levels in the deep weak inversion region. The resulting increased mismatch and reduced bandwidth are compensated for at the topology level. The filter has a 43 dB dynamic range and a 60 pW power consumption. This power consumption is three orders of magnitude lower than existing CWT implementations and assessed via a suitable figure of merit the performance is better than all considered bandpass filters. The improvement in the state-of-the-art originates from the close integration of the application requirements, CWT theory, bandpass filter design theory, and low transconductance transconductor design. These topics are described in detail.
IEEE Journal of Solid-State Circuits 07/2011; · 3.23 Impact Factor
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ABSTRACT: Compressive sensing is a new data compression paradigm that has shown significant promise in fields such as MRI. However, the practical performance of the theory very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Electroencephalography (EEG) is a fundamental tool for the investigation of many neurological disorders and is increasingly also used in many non-medical applications, such as Brain-Computer Interfaces. This paper characterises in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals for the first time. The results are of particular interest for wearable EEG communication systems requiring low power, real-time compression of the EEG data.
Applied Sciences in Biomedical and Communication Technologies (ISABEL), 2010 3rd International Symposium on; 12/2010
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ABSTRACT: Analogue domain implementations of the Continuous Wavelet Transform (CWT) have proved popular in recent years as they can be implemented at very low power consumption levels. This is essential for use in wearable, long term physiological monitoring systems. Present analogue CWT implementations rely on taking mathematical a approximation of the wanted mother wavelet function to give a filter transfer function that is suitable for circuit implementation. This paper investigates the use of standard filter approximations (Butterworth, Chebyshev, Bessel) as an alternative wavelet approximation technique. This extends the number of approximation techniques available for generating analogue CWT filters. An example ECG analysis shows that signal information can be successfully extracted using these CWT approximations.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: Custom designed microchips, known as Application Specific Integrated Circuits (ASICs), offer the lowest possible power consumption electronics. However, this comes at the cost of a longer, more complex and more costly design process compared to one using generic, off-the-shelf components. Nevertheless, their use is essential in future truly wearable medical devices that must operate for long periods of time from physically small, energy limited batteries. This presentation will demonstrate the state-of-the-art in ASIC technology for providing online signal processing for use in these wearable medical devices.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: This talk will provide an introduction to the “Towards future truly wearable medical devices: from application to ASIC” mini-symposium. For user comfort and acceptance long term physiological sensors must be discrete, comfortable and easy to use. These requirements place stringent limits on all aspects of the system design: from the overall application aim, to power generation issues, to low power electronic design techniques. For successful devices design issues in all of these areas must be solved simultaneously. The work here presents an overview and introduction to these topics.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brainwaves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time [see Figure 1(a) and (b)]. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsyand the medical applications of wearable EEG, as this is the historical background of the EEG, our area of exper-
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tise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.
IEEE Engineering in Medicine and Biology Magazine 07/2010; · 2.06 Impact Factor
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ABSTRACT: Portable EEG units are key tools in epilepsy diagnosis. Current systems could be made physically smaller and longer lasting by the inclusion of online data reduction methods to reduce the power required for storage or transmission of the EEG data. This paper presents a real-time data reduction algorithm based upon the discontinuous recording of the EEG: noninteresting background sections of EEG are discarded online, with only potentially diagnostically interesting sections being saved. MATLAB simulations of the algorithm on an EEG dataset containing 982 expert marked events in 4 days of data show that 90% of events can be correctly recorded while achieving a 50% data reduction. The described algorithm is formulated to have a direct, low power, hardware implementation and similar data reduction strategies could be employed in a range of body-area-network-type applications.
IEEE Transactions on Biomedical Engineering 01/2010; · 2.28 Impact Factor
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ABSTRACT: This paper presents the novel design of a second-order continuous-time low-power and low-voltage SigmaDelta modulator. The modulator illustrates a design philosophy based on taking advantage of the extended number of degrees of freedom of the floating-gate MOS transistor. The transistor is simultaneously used to fulfill the following: simplify the topology; accurately implement the modulator coefficients; compensate for gain losses in the integrator and several nonidealities in the comparator; increase the signal range; reduce distortion; shift signal levels according to the specific requirements of individual devices; implement an easy common-mode sensing and feedback strategy; and tune the loop filter and reset the comparator. The modulator operates at 1 V and consumes just over 5 muW of power for a signal-to-noise-and-distortion ratio of 60 dB and a maximum bandwidth of 2 kHz, which are typical of many biomedical applications.
Circuits and Systems I: Regular Papers, IEEE Transactions on 08/2009; · 1.97 Impact Factor
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ABSTRACT: This paper presents a second-order Sigma-Delta modulator for electroencephalogram applications with 10 bits of resolution, 1.2 V of supply voltage, and only 140 nW of power consumption over a bandwidth of 25 Hz. Low-voltage operation has been achieved using quasi-floating-gate-based circuits. The use of a new class-AB operational amplifier in weak inversion allows very low power consumption. Experimental results show an energy efficiency of 1.6 pJ per quantization level, making it the most energy-efficient converter reported to date in the very low signal bandwidth range.
IEEE Transactions on Biomedical Circuits and Systems 10/2008; · 2.03 Impact Factor
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ABSTRACT: This work considers continuous time filter design for the inverse continuous wavelet transform (ICWT) allowing the ICWT to be carried out for an arbitrary bandpass filter forward transform. The design procedure illustrates how application specific information can be used to guide the design process, for example to achieve good reconstruction from coefficients at just one analysis scale. Simulations of the filter design show that good reconstruction accuracy can be achieved.
Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on; 06/2008
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ABSTRACT: This paper presents a nanopower programmable bandpass filter suitable to process biomedical signals. The filter proves to be very robust to mismatch and process variations even when it has been implemented using MOS transistors biased in the weak inversion region. The paper analyses design issues associated to matching and process variations for the chosen filter topology and constituent transconductor block. The design equations justify the choice of both when the main constraints are robustness and power. The sixth order, bandpass filter prototype consumes 70 nW of power, with a dynamic range greater than 47 dB and operates at 1-V power supply. The filter was designed as part of a wearable breathing detector but its wide programmability range makes it suitable for many other biomedical sensor interfaces that require steep low frequency rejection band as well as ultralow power and low voltage operation.
IEEE Transactions on Biomedical Circuits and Systems 10/2007; · 2.03 Impact Factor
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ABSTRACT: This paper presents a novel low voltage and low power continuous time sigma-delta modulator based on the floating gate MOS (FGMOS) transistors. The performance of the two main building blocks in the modulator, the continuous time integrator and the comparator, are achieved by exploiting the benefits of the FGMOS devices. It is proven that using FGMOS devices improves the circuit linearity and hence increases the dynamic range. The modulator, designed in AMS 0.35 mum technology, works at a supply voltage of 1 V, exhibits a dynamic range (DR) of 67 dB, signal-to-noise- ratio (SNR) of 63 dB and signal-to-noise-and-distortion-ratio (SNDR) of 60 dB of 2 kHz Bandwidth (BW), with a power consumption of 5 muW.
Circuit Theory and Design, 2007. ECCTD 2007. 18th European Conference on; 09/2007
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ABSTRACT: The Continuous Wavelet Transform (CWT) is a highly useful signal processing technique for which low power implementations are desirable, for example to allow the transform to be used in battery powered, portable devices. This paper describes a Low Power CWT (LPCWT) implementation that is based around the mathematical approximation of a mother wavelet and uses application specific information to guide the approximation process. Simulations comparing the LPCWT and CWT are carried out with the two giving equivalent signal processing performance. The LPCWT is suitable for realisation in any desired circuit topology.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: High quality, wireless ambulatory EEG (AEEG) systems that can operate over extended periods of time are not currently feasible due to the high power consumption of wireless transmitters. Previous work has thus proposed data reduction by only transmitting sections of data that contain candidate epileptic activity. This paper investigates algorithms by which this data selection can be carried out. It is essential that the algorithm is low power and that all possible features are identified, even at the expense of more false detections. Given this, a brief review of spike detection algorithms is carried out with a view to using these algorithms to drive the data reduction process. A CWT based algorithm is deemed most suitable for use and an algorithm is described in detail and its performance tested. It is found that over 90 % of expert marked spikes are identified whilst giving a 40 % reduction in the amount of data to be transmitted and analysed. The performance varies with the recording duration in response to each detection and this effect is also investigated. The proposed algorithm will form the basis of new a AEEG system that allows wireless and longer term epilepsy monitoring.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: A low-voltage and low-power front-end for miniaturized, wearable EEG systems is presented. The instrumentation amplifier, which removes the electrode drift and conditions the signal for a 10-bit A/D converter, combines a chopping strategy with quasi-FGMOS (QFG) transistors to minimize low frequency noise whilst enabling operation at 1 V supply. QFG devices are also key to the A/D converter operating at 1.2 V with 70 dB of SNR and an oversampling ratio of 64. The whole system consumes less than 2 muW at 1.2 V.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: Wireless ambulatory EEG (AEEG) monitoring over long periods of time is currently infeasible due to battery limitations and the EEG analysis time required. A detailed comparison of methods for reducing the amount of AEEG data is presented. It is concluded that a discontinuous recording scheme can alleviate both of the above problems. Discontinuous monitoring introduces data interpretation and practical issues which are discussed. With suitable low power algorithm implementations and realistic system expectations such systems are deemed to be feasible.
Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on; 06/2007
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ABSTRACT: The development of wireless ambulatory EEG is crucial in enabling the longer term monitoring of a patient in their everyday environment. The analysis presented here will aid the designer of a wireless EEG headset in improving the ratio of battery lifetime to battery size, with the aim of minimising the size and weight of the device. Data compression is proposed as a method to reduce the power used by the wireless transceiver, shown to dominate the system power budget. Graphs are presented which show the power available to perform varying degrees of compression in order to achieve the required lifetime or battery volume
Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on; 06/2007
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ABSTRACT: A low-voltage and low-power front-end for miniaturized, wearable EEG systems is presented. The instrumentation amplifier, which removes the electrode drift and conditions the signal for a 10-bit A/D converter, combines a chopping strategy with quasi-FGMOS (QFG) transistors to minimize low frequency noise whilst enabling operation at 1 V supply. QFG devices are also key to the A/D converter operating at 1.2 V with 70dB of SNR and an oversampling ratio of 64. The whole system consumes less than 2uW at 1.2V.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2007; 2007:5282-5.
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ABSTRACT: A low power, low voltage rectifier circuit is proposed, designed in a CMOS process. It achieves a power consumption of less than 600 nW and a dynamic range of 60 dB from a power supply of 1 V. The rectifier has a bandwidth of 20 kHz. Practical issues concerning the design of low power, low voltage rectifiers are discussed.
Circuits and Systems, 2006. MWSCAS '06. 49th IEEE International Midwest Symposium on; 09/2006
