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A Novel Low-Power-Implantable Epileptic Seizure-Onset Detector

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A Novel Low-Power-Implantable Epileptic Seizure-Onset Detector
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  568 IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, VOL. 5, NO. 6, DECEMBER 2011 A Novel Low-Power-ImplantableEpileptic Seizure-Onset Detector Muhammad Tariqus Salam, Mohamad Sawan  , Fellow, IEEE  , and Dang Khoa Nguyen  Abstract— A novel implantable low-power integrated circuit isproposed for real-time epileptic seizure detection. The presentedchip is part of an epilepsy prosthesis device that triggers focaltreatment to disrupt seizure progression. The proposed chipintegrates a front-end preamplifier, voltage-level detectors, digitaldemodulators, and a high-frequency detector. The preamplifieruses a new chopper stabilizer topology that reduces instru-mentation low-frequency and ripple noises by modulating thesignal in the analog domain and demodulating it in the digitaldomain. Moreover, each voltage-level detector consists of anultra-low-power comparator with an adjustable threshold voltage.The digitally integrated high-frequency detector is tunable torecognize the high-frequency activities for the unique detection of seizure patterns specific to each patient. The digitally controlledcircuits perform accurate seizure detection. A mathematicalmodel of the proposed seizure detection algorithm was validatedin Matlab and circuits were implemented in a 2 mm    chip usingthe CMOS 0.18- m process. The proposed detector was tested byusing intracerebral electroencephalography (icEEG) recordingsfrom seven patients with drug-resistant epilepsy. The seizuresignals were assessed by the proposed detector and the averageseizure detection delay was 13.5 s, well before the onset of clinicalmanifestations. The measured total power consumption of thedetector is 51 W.  Index Terms— Algorithm, epilepsy, low noise, low power, micro-electronics, seizure detector. I. I NTRODUCTION E PILEPSY is a common medical condition characterizedby a predisposition to unprovoked recurrent seizures. Aseizure is the manifestation of an abnormal, hypersynchronousdischargeofapopulationofcorticalneurons[1].Approximately30%ofpatients,themajorityofwhichsufferfrompartial(focal)seizureswithorwithoutsecondarygeneralization,arerefractoryto anticonvulsants. Not all refractory patients are good epilepsysurgery candidates due to an extensive area of epileptogenic-zone (EZ), multifocal, inability to localize the EZ, and an EZoverlying eloquent areas (language, primary motor, or visualareas) that cannot be resected without permanent sequelae [1]. Manuscript received October 04, 2010; revised January 19, 2011; acceptedMay 13, 2011. Date of publication June 23, 2011; date of current version De-cember 29, 2011. This paper was recommended by Associate Editor R. Genov.M. T. Salam and M. Sawan are with the Polystim Neurotechnologies Labo-ratory, École Polytechnique de Montréal, Montréal, QC H3T 1J4, Canada.D.K.NguyeniswiththeNeurologyService,DepartmentofMedicine,Notre-Dame Hospital (Centre Hospitalier de l’Université de Montréal), Montréal, QCH2L 4M1 Canada (e-mail: tariqus.salam@polymtl.ca).Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.Digital Object Identifier 10.1109/TBCAS.2011.2157153 As a result, the uncontrolled seizures bring a devastating impacton their quality of life.Proof-of-concept experiments conducted in animals andhumans with epilepsy have demonstrated that focal electrical,thermal, or pharmacological manipulations of the EZ cansuppress seizure activity [2]–[5]. Over the last few years, therehas been growing interest in the development of implantabledevices as an adjunctive treatment for patients with refractorypartial epilepsy. So far, the vagus nerve stimulator (VNS)is the only Food and Drug Administration (FDA)-approvedmedical device for the treatment of epilepsy. This scheduled(open-loop) stimulation device provides a reduction in seizurefrequency; however, the overall effectiveness is modest [2],[3]. A cranially implanted responsive neurostimulator thattriggers stimulation only upon detection of a seizure holds thepromise of better seizure control, lower systemic, peripheraland central nervous system side effects, as well as lower batteryconsumption [2], [3], [5]–[7]. Preliminary results on a newresponsive device for the treatment of epilepsy (RNS system,Neuropace Inc.), Mountain View, CA, have been promising [2].Several issues remain to be addressed, such as the necessityof a reliable seizure detection system that is sensitive enoughto detect seizures early on but also specific enough to preventunwarranted triggering of focal intervention.The initial steps required for the development of any re-sponsive focal therapy device for epilepsy are the recordingof intracerebral electroencephalography (icEEG) followed bythe automated detection of seizures. IcEEG recordings aregenerally performed using subdural strip and/or depth electrodecontacts. The recorded icEEG represents synchronous firing of many neurons throughout a region across the diameter of anelectrode contact. It is generally characterized by a low-am-plitude signal (microvolts) and low-frequency bandwidth.Due to the microvolt-level range, the neural signal must beamplified very carefully before further analysis (e.g., detectionand digitization). CMOS technology has relatively poor noiseperformance and the low-amplitude amplification requiresa CMOS amplifier with low input-referred noise [8]–[15].However, the restrictions on the power consumption and sizeof an implantable device limit increasing the biasing current.Therefore, design tradeoffs between the biasing current andnoise are required to optimize the performance of a device.Thechallengesofseizuredetectionare variabilityinepilepticseizure onset pattern, signal amplitude, and spectral content.Over the past few decades, many seizure detection and pre-diction algorithms have been proposed [16]–[20]. However,these algorithms are carried out offline using high-performancecomputers. These types of algorithms cannot be employed 1932-4545/$26.00 © 2011 IEEE  SALAM  et al. : A NOVEL LOW-POWER-IMPLANTABLE EPILEPTIC SEIZURE-ONSET DETECTOR 569 Fig. 1. IEEG recordings of two patients with refractory focal epilepsy and signal analyses. (a)Start ofseizure activity characterized by low-amplitude fast activity.(b) Frequency analysis      of (a). (c) Mean absolute amplitude      analysis of (a). (d) Seizure activity of the second patient with an initial brief electricalseizures (BES) followed by an electroclinical seizure. (e)    of (d), and        of (d). in a low-power implantable microchip. More recently, a fewimplantable integrated seizure detectors have been proposed[8]–[10] and [21]–[26]. The earlier design of our seizure detec-tors [8]–[10] is based on several detection criteria in differentamplitude levels. The details will be explained in Sections IIand IV. The detection algorithm presented in [21] is based onclassifying icEEG data into events, and the events are relatedto a threshold voltage in the icEEG during high-frequencydischarges at seizure state. Since the detector [21] relies onlyon two threshold voltages (positive and negative), there isa high risk for false positive detections. The support vectorseizure detection machine [22] needs a high number of supportvectors in order to define the complex decision boundarybetween a patient’s seizure and nonseizure activity, explainingits high power consumption and cost. Similarly, the detectorbased on the linear-discriminant analysis classifier requireshigher complexity in digital signal processor (DSP) and ap-plication-specific integrated-circuit (ASIC) implementation toimprove sensitivity and specificity [23].In this paper, we present a low-power-implantable CMOS in-tegrated seizure onset detector (SOD) for patients with medi-cally intractable epilepsy. The detector is part of an epilepsyprosthesis that triggers focal treatment to disrupt seizure pro-gression. This SOD includes implanted electrodes, a data-ac-quisition system, as well as analog and digital signal processorsin order to acquire and process real-time icEEG. The proposedSOD chip uses the specific seizure onset features of a patient inorder to detect their progressive increase of low-voltage fast-ac-tivity ictal pattern. The system is designed to have tunable pa-rameters,whichwouldallowforthetradeoffbetweensensitivity(SXT), false detection (FD), and detection delay (DTD). Thetunability of the SOD provides higher accuracy on seizure de-tection. The adjustable gain of an amplifier can emphasize theamplitudelevelofinterest,andvariablethresholdvoltagesofthevoltage level detectors (VLD) delimit the detected signal loca-tions and extract the information of frequency as well as a pro-gressive increase in amplitude. The SOD chip was tested offlineonsevenpatientswithrefractoryepilepsy.Themeasuredresultshave shown that the SOD maximizes the SXT and minimizesthe FD, which would tradeoff for the longer DTD, but prior tothe first clinical manifestations of the patients. The detection isexpected to be reliable in an implantable device without riskingfalse detections of physiological rhythms (e.g., sleep spindles).The epileptic seizure detection algorithm is described in Sec-tionIIandtheglobalsysteminSectionIII.Theproposedcircuitsand their implementations are the subject of Section IV. Exper-imental results are presented in Section V, and conclusions aresummarized in the last section of this paper.II. E PILEPTIC  S EIZURE  D ETECTION  A LGORITHM Partial seizures srcinate primarily within discretely local-izedormorewidelydistributednetworkslimitedtoonecerebralhemisphere. They may subsequently generalize as the epilepticdischarge spreads contralaterally. Seizure onsets may vary frompatient to patient in terms of onset morphology, discharge fre-quency, focality, and spread pattern. Electrographically, severalpatterns can be seen at seizure onset, such as low-voltage andhigh-voltage fast activities or rhythmic spiking [1]. Fig. 1(a)shows the sudden appearance of the typical low-voltage fastactivity recorded from two intracerebral contacts positionedover the EZ, increasing in frequency [Fig. 1(b)], and am-plitude [Fig. 1(c)]. The icEEG is analyzed over the seizure  570 IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, VOL. 5, NO. 6, DECEMBER 2011 Fig. 2. Seizure detection algorithm. (a) Input signal    . (b) Modulated signalof     . (c) Output of VLDs    . (d) Digital demodulation    . onset [Fig. 1(a)–(c)] and the SOD detects the high-frequencydischarge in icEEG, which may suggest an upcoming electro-clinical seizure. However, as seen in many icEEG recordings,some of these high-frequency discharges [e.g., Fig. 1(d)] can bevery brief (few seconds), remain very focal (without spread), donot evolve in time or frequency, and are clinically silent (elec-trical seizures). For most patients, it is probably not necessarytotargetthemas“seizures”warranting focaltreatment, theycansimply be ignored. For this reason, the seizure onset detectioncriteria are preferably set as a high-frequency activity [Fig. 1(b)and (e)] showing a progressive increase in amplitude [Fig. 1(c)and (f)]. This should avoid false detections of interictal spikesand polyspikes, movement artifacts, physiological rhythms(e.g., sleep spindles), and brief asymptomatic high-frequencyvoltage activities or very brief electrical seizures which woulderroneously trigger unwarranted focal treatment.The proposed seizure detector is specialized to detect veryspecific types of seizures characterized by their progressive in-crease of low-voltage fast activity. In this algorithm, the inputsignal [ in Fig. 2(a)] is modulated into high frequencyso that the instrumentation’s low-frequency noise doesnot affect the signal. Moreover, this modulation (1) convertsnegative signal amplitudes to positive amplitudes [Fig. 2(b)].Thus, positive hyper-excited threshold voltages of a VLD are sufficient to detect the high frequency of . Thediscrete modulated signal confined to a time framepasses through number of VLDs to detect the specific fea-tures (2) characterized by a progressive increase in amplitudeand high-frequency variation. Fig. 2(c) shows the output of aVLD when it detects fast activities following (2):(1)where ,'` for'` for otherwise(2)where . , and are tuned tothe specific seizure onset frequency of a patient so thatno false alarms occur during seizure detection. Due to the mod-ulation, VLDs detect a burst of pulses and unwanted high-fre-quency samples [Fig. 2(c)]. The following equation shows theelimination of false positive detections for the unwanted high-frequency samples:'` for'` for otherwise (3)where is the pulsewidth of . The detected burstpulses are converted to a single pulse by'` for and'` for otherwise. (4)The signal frequency is defined by the total numberof identified pulses confined to as follows:(5)Thus,seizureonset willbe declaredbasedonthefollowingcon-ditions (6):'` Seizure,'` No Seizure otherwise. (6)The SXT of the algorithm is enhanced, and several decisionboundaries are introduced to reduce the number of FDs forthe patient’s specific seizure onset pattern. The signal analysisof this algorithm demonstrates that the early modulation andproper rectification of icEEG can identify the seizure onsetefficiently.III. P ROPOSED  S YSTEM The proposed implantable SOD provides continuous long-term monitoring of icEEG from the EZ. Fig. 3(a) illustrates theimplant configuration of the SOD, and the functional block dia-gramofFig.3(b)presentsitsarchitecture.Thedevicewillbeim-plantedwithintheskullandinterfacedirectlywiththerecordingsite using standard subdural/depth electrodes (diameter/size: 5mm and interelectrode spacing: 10 mm). This SOD consists of a preamplifier, voltage-level detectors (VLD), digital demodu-lators (DD), and a high-frequency detector (HFD). In this SOD,several variable parameters ( , , and ) are in-troduced to facilitate higher accuracy in real-time seizure onsetdetection. controls the amplification of neural signals,are used to adjust the threshold voltages of VLDs,and in HFD sets the tunability of the frequency detection.Fig. 3(b) shows that most of the signal processing in the SODis accomplished in the digital domain because of the relativelypoor noise performance of CMOS technology. The preampli-fier initially modulates the neural signal in and amplifies theinput amplitude level of interest. Subsequently, the VLDs con-vert the amplified signal to a digital signal . Oncethe signal is digitalized, there is little further possibility to add  SALAM  et al. : A NOVEL LOW-POWER-IMPLANTABLE EPILEPTIC SEIZURE-ONSET DETECTOR 571 Fig. 3. Proposed integrated SOD. (a) Implant configuration which shows the devices and two sets of electrodes—the sensing subdural electrodes and depth elec-trodes. (b) Block diagram of the proposed SOD chip.Fig. 4. Dedicated chopper stabilizer circuit and corresponding frequency analysis of signals in different nodes. noises in this signal. Then, the is demodulated to the orig-inal digital signal . Finally, the HFD determines the seizureonset frequency from processed signals and declares a seizuredetection without false alarm.IV. C IRCUIT  I MPLEMENTATION As illustrated in Fig. 3, the SOD consists of four main func-tional blocks. The details are given below.  A. Preamplification A dedicated chopper preamplification method was intro-ducedinourpreviouswork[10].Fig.4showstheblockdiagramof the preamplifier and the frequency analysis of signals indifferent nodes. This figure demonstrates that the preamplifierinput signal is modulated by a signal with frequency , and theflicker noise and dc-offset voltage noise of the amplifierare attenuated by the high-pass filter, while the finite bandwidthof the amplifier and buffer band limit thethermal noise . Theproposed preamplifier is advantageous over the conventionalchopper preamplifier for the detection of epileptic seizures.The comparison of the preamplifiers is shown in Table I.Fig.5(a)illustratesthepreamplifierconstruction,whichconsistsof an operational transconductance amplifier (OTA) [Fig. 5(b)],high-pass filter, and a buffer. These circuits provide a band-pass frequency response, which is produced by the preamplifier[Fig. 5(a)] and the bandpass filter that has a maximum of 80-dBmidband gain and 17 kHz (2 kHz to 19 kHz) bandwidth with6 input-referred noise. Moreover, the OTA has variable TABLE IC OMPARISON OF THE  C ONVENTIONAL AND THE  P ROPOSED C HOPPER  P REAMPLIFIER gain that can emphasize a specific amplitude range of the neuralsignal.  B. Voltage-Level Detector  Avoltageleveldetector(VLD)consistsofcomparators,logicgates, DFF, and a buffer [Fig. 6(a) and (b)]. A low-power com-parator has been reported in [27] that includes two cascadedCMOS inverters, with the threshold voltage set by the aspect ra-tiosofthetransistors.Themaindisadvantageofthiscomparatoris the fixed threshold voltage in an integrated device. However,  572 IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, VOL. 5, NO. 6, DECEMBER 2011 Fig. 5. Preamplification front end. (a) Bandpass filter comprising an OTA, ahigh-pass filter, and a buffer. (b) Circuit of the OTA used in the preamplifier.Fig. 6. Construction of VLDs: (a) Block diagram of VLDs. (b) Schematic of aVLD. (c) Circuit of a comparator. a modified version of the comparator [Fig. 6(c)] provides vari-able threshold voltages(7)where and are the threshold voltage of the NMOS andPMOSdevices,respectively; isthesourcetogatevoltageof the Mcp1 transistor; and and. Equation (7) shows that is the only vari-able parameter that can adjust the value of in an inte-grated circuit (IC). The variation of is proportional tothe bias voltage . The other advantages of the mod-ified comparator are: 1) negligible static power consumption,2) no hysteresis effect, and 3) relatively small transistor area.In order to construct a VLD, two modified comparatorsare used. Fig. 6(a) shows several VLDs. The bias voltagesand set the variable lower andupper threshold voltages, respectively. The DFFcircuit removes unnecessary high-frequency samples. C. Digital Demodulator  A digital demodulator (DD) includes an RC circuit and aVLD [Fig. 7(a)] that converts a burst of pulses to a single pulse.During a seizure, the VLD (Fig. 6) detects the abnormalities in Fig. 7. Digital demodulator (DD). (a) Circuit. (b) Burst of pulses detected byVLD. (c) Voltage    across the RC circuit. (d) Output    .Fig. 8. Microphotograph of the fabricated SOD chip. signalsandgeneratesseveralburstsofpulses duetomod-ulationinthepreamplificationstage.IntheDD,eachinputpulse[Fig. 7(b)] charges the capacitor (Ceb) quickly, but the dis-charging time of Ceb is longer than the duration be-tween two consequent pulses of clock [Fig. 7(c)]. Thus, the Cebcannot be discharged completely during a burst of pulses. How-ever,aVLDconnectedtoanRCcircuitdetectstheendofaburst,where the Ceb discharges completely through a diode connec-tionoftheMeb1transistorandgeneratesapulse [Fig.7(d)].  D. High-Frequency Detector  The high-frequency detector (HFD) [Fig. 7(b)] has two mainbuilding blocks: 1) a time frame selector (TFS) and 2) threefrequency detectors (FD). The TFS is based on a 14-b counterthat generates two different time frames andin13thand14thb,respectively.TheFDcountsthe number of pulses received from the DD and resets allFDs at the end of every . Finally, the logic gates analyze theoutputs of FD and declare an upcoming seizure .V. E XPERIMENTAL  R ESULTS The SOD was fabricated in a CMOS 0.18- m process andoccupies 2 mm 1 mm of silicon area. A photograph of thefabricated chip is shown in Fig. 8.  A. IC Measured Performance The test bench measurements were performed on five sam-ples of the fabricated chip and were presented consistently in
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