A Battery-Free Multi-Channel Digital Neural/EMG Telemetry System

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A Battery-Free Multi-Channel Digital Neural/EMG Telemetry System for Flying Insects Stewart J. Thomas * , Reid R. Harrison , Anthony Leonardo , Matthew S. Reynolds * * Department of Electrical and Computer Engineering, Duke University, Durham, NC Intan Technologies LLC, Los Angeles, CA Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA Abstract—Most recently reported multi-channel wireless neu- ral telemetry systems are not suitable for studying insects in flight because of mass and battery limitations. We present preliminary results toward the development of a digital neural/EMG teleme- try system with a measured flight package mass of only 38 mg. This system includes a single-chip telemetry system employing RF power harvesting for battery-free operation, with communication via modulated backscatter in the UHF (902–928 MHz) band. An on-chip 11-bit ADC digitizes 10 neural channels with a sampling rate of 26.1 kSps and 4 EMG channels at 1.63 kSps. We also present a companion base station transceiver including an RF transmitter of +36 dBm (4 W) output power to wirelessly power the IC, and a digital receiver with a threshold sensitivity of -70 dBm for 10 -5 BER at 5.0 Mbps to receive the data stream. The chip was fabricated in a commercial 0.35 μm 4M1P (4 metal, 1 poly) CMOS process. The die measures 2.36 x 1.88 mm, and is 250 μm thick. Measurements to date indicate that the chip is fully functional as designed. I. I NTRODUCTION The study of neural activity during behavior is a topic of intense interest in neuroscience, but progress is often slowed by difficulty in measuring the activity of multiple neurons in a moving animal. For example, dragonflies are predatory insects that catch prey on the wing, intercepting their targets over flights 0.5–1.0 m in distance. Dragonflies of the species Libellula lydia, which initiate foraging flights from a perch, weigh about 400 mg, and can maintain their interception behavior with payloads of up to 33% of their body weight, or about 130 mg. This small payload capacity presents severe challenges for designing instrumentation that can measure the electrical activity of one or more neurons in the dragonfly nervous system during flight. While much successful work has occurred using tethers [1], these devices can hinder movement. Most existing wireless multi-channel neural telemetry systems have masses in the 30–60 g range and require a large battery pack for extended operation [2]– [4]. This work represents a continuation of earlier efforts [5] to develop wireless instrumentation that allows less kinematically invasive measurements for very small animals. Power requirements present the greatest obstacle to achiev- ing successful data capture from a flying insect. Even state- of-the-art ultra-lightweight battery powered systems are fairly heavy (170 mg) with the bulk of this weight (130 mg) being associated with a 1.5 V silver oxide battery [5]. We have addressed this challenge by developing an on-chip UHF (902– 928 MHz) power harvesting subsystem that extracts the chip’s operating power (1.23 mW) from incident RF energy supplied Fig. 1: Layout diagram of the 14 channel digital telemetry IC. The die is 2.36 mm x 1.88 mm x 250 μm thick. Fig. 2: Assembled chip-on-flex flight package. Package mass is 38 mg including all necessary external components. by a transmitter and antenna mounted beneath the dragonfly’s perch. By eliminating the battery and almost all external components, the complete telemetry system, shown in Figure 2, has a mass of only 38 mg. In contrast to commonly used inductive power, UHF power harvesting can operate with small dragonfly-sized dipole an- tennas at distances of several meters, depending on telemetry system power consumption and available transmitter power. Related work in biotelemetry powered by UHF energy har- vesting includes [6], [7]. While payload mass provides one significant constraint on the design of any flight telemetry system, a second equally important requirement is the telemetered bandwidth

Transcript of A Battery-Free Multi-Channel Digital Neural/EMG Telemetry System

Page 1: A Battery-Free Multi-Channel Digital Neural/EMG Telemetry System

A Battery-Free Multi-Channel Digital Neural/EMGTelemetry System for Flying Insects

Stewart J. Thomas∗, Reid R. Harrison†, Anthony Leonardo‡, Matthew S. Reynolds∗∗Department of Electrical and Computer Engineering, Duke University, Durham, NC

†Intan Technologies LLC, Los Angeles, CA‡Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA

Abstract—Most recently reported multi-channel wireless neu-ral telemetry systems are not suitable for studying insects in flightbecause of mass and battery limitations. We present preliminaryresults toward the development of a digital neural/EMG teleme-try system with a measured flight package mass of only 38 mg.This system includes a single-chip telemetry system employing RFpower harvesting for battery-free operation, with communicationvia modulated backscatter in the UHF (902–928 MHz) band. Anon-chip 11-bit ADC digitizes 10 neural channels with a samplingrate of 26.1 kSps and 4 EMG channels at 1.63 kSps. We alsopresent a companion base station transceiver including an RFtransmitter of +36 dBm (4 W) output power to wirelessly powerthe IC, and a digital receiver with a threshold sensitivity of-70 dBm for 10−5 BER at 5.0 Mbps to receive the data stream.The chip was fabricated in a commercial 0.35 µm 4M1P (4 metal,1 poly) CMOS process. The die measures 2.36 x 1.88 mm, andis 250 µm thick. Measurements to date indicate that the chip isfully functional as designed.

I. INTRODUCTION

The study of neural activity during behavior is a topicof intense interest in neuroscience, but progress is oftenslowed by difficulty in measuring the activity of multipleneurons in a moving animal. For example, dragonflies arepredatory insects that catch prey on the wing, interceptingtheir targets over flights 0.5–1.0 m in distance. Dragonfliesof the species Libellula lydia, which initiate foraging flightsfrom a perch, weigh about 400 mg, and can maintain theirinterception behavior with payloads of up to 33% of theirbody weight, or about 130 mg. This small payload capacitypresents severe challenges for designing instrumentation thatcan measure the electrical activity of one or more neuronsin the dragonfly nervous system during flight. While muchsuccessful work has occurred using tethers [1], these devicescan hinder movement. Most existing wireless multi-channelneural telemetry systems have masses in the 30–60 g rangeand require a large battery pack for extended operation [2]–[4]. This work represents a continuation of earlier efforts [5] todevelop wireless instrumentation that allows less kinematicallyinvasive measurements for very small animals.

Power requirements present the greatest obstacle to achiev-ing successful data capture from a flying insect. Even state-of-the-art ultra-lightweight battery powered systems are fairlyheavy (170 mg) with the bulk of this weight (130 mg) beingassociated with a 1.5 V silver oxide battery [5]. We haveaddressed this challenge by developing an on-chip UHF (902–928 MHz) power harvesting subsystem that extracts the chip’soperating power (1.23 mW) from incident RF energy supplied

Fig. 1: Layout diagram of the 14 channel digital telemetry IC.The die is 2.36 mm x 1.88 mm x 250 µm thick.

Fig. 2: Assembled chip-on-flex flight package. Package massis 38 mg including all necessary external components.

by a transmitter and antenna mounted beneath the dragonfly’sperch. By eliminating the battery and almost all externalcomponents, the complete telemetry system, shown in Figure2, has a mass of only 38 mg.

In contrast to commonly used inductive power, UHF powerharvesting can operate with small dragonfly-sized dipole an-tennas at distances of several meters, depending on telemetrysystem power consumption and available transmitter power.Related work in biotelemetry powered by UHF energy har-vesting includes [6], [7].

While payload mass provides one significant constrainton the design of any flight telemetry system, a secondequally important requirement is the telemetered bandwidth

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16-to-1 analog MUX

11-bit ADC

11

10 neural amplifiers

neural amp reference

4 EMG amplifiers

2 DC amplifiers

data serializer; Hamming encoder; frame sequencer;

Manchester encoder

digital control logic

crystal oscillator

off-chip 20 MHz crystal

clock

control

MUX select

4

impedance modulator

Cmod

Encoded serial data stream

antenna

RF rectifier; voltage

multiplier

1.23V LDO

regulator

off-chip smoothing capacitors

chip Vdd

= bond pad

Fig. 3: Block diagram of the 14 channel digital telemetry IC

and number of channels. Many of the most pressing questionsin systems neuroscience relate to understanding the role ofspecific neurons within a circuit so signals must be measuredin a manner that preserves their identity. Telemetering eventtimes based on a threshold is insufficient because the identityof the neurons is lost. Extracellular electrodes, such as thoseused in awake behavior experiments, measure the summedactivity of multiple neurons. These signals must then be sortedback into the activity of individual cells. There are welldeveloped tools that facilitate such spike sorting [8], but theyuse computational methods difficult to embed on-chip [9],and generally require the full analog waveforms seen on theelectrode to perform well. It is preferable to record sampledtime series data for each electrode for maximum flexibility inspike sorting and analysis.

In the dragonfly, there are ≈ 16 target-selective descendingneurons (TSDNs) that appear to control interception basedsteering [10]. At flight temperatures of 35◦C, TSDNs haveaction potential spikes of ≈ 250 µs in duration. These actionpotentials must be sampled at 25–40 kHz in order to havesufficient resolution to allow accurate neuron identification.Extracellular action potential spikes, such as those seen in thedragonfly, can be 4 mV in amplitude, on background noiselevels of 10 µV RMS or smaller. The entire telemetry payloadshould be no more than 25 mm2 (e.g. 5 mm x 5 mm, whichwill fit under the thorax) and weigh substantially less than130 mg.

II. THE DIGITAL TELEMETRY IC

The telemetry IC is highly integrated, with a layout shownin Fig. 1 and block diagram shown in Fig. 3. The flightpackage shown in Fig. 2 includes the optional impedancematching network, a miniature 20 MHz quartz crystal, andtwo 0402 SMD bypass capacitors for the unregulated andregulated power supplies. The crystal provides precise clocksfor analog to digital converter (ADC) sampling and data clocksynchronization.

TABLE I: Telemetry IC power breakdown (meas. vs. sim.)

Neural amplifiers 10 x 16 µA 160 µAEMG amplifiers 4 x 0.25 µA 1 µADC amplifiers 2 x 45 µA 90 µAAnalog mux 139 µAAmplifier / mux bias generators 80 µA11-bit ADC and digital control logic 320 µALDO voltage regulator 60 µACrystal oscillator 70 µABackscatter modulator 15 µASimulated Total IC supply current 935 µAMeasured Total IC supply current 940 µA

Minimum unregulated supply voltage 1.31 VSimulated Total IC power consumption 1.22 mWMeasured Total IC power consumption 1.23 mW

to LDO voltage regulator

external smoothing capacitor (0.1 µF typ.)

Antenna

bond pad

bond pad C

C

C

CCC

C = 10 pF MIM capacitors

Fig. 4: Simplified schematic of the on-chip RF power harvester

The IC digitizes 10 neural inputs at 26.1 kSps, along with 4additional EMG inputs at 1.63 kSps. An ADC with 11 bits ofresolution is used to preserve the waveform shape. Includingerror detection and correction overhead, a data rate of 5Mbps is required. A modulated backscatter communicationlink enables data rates over 14x higher than recently reportedlow-power transmitter approaches [5], while using similarpower levels. A breakdown of the power consumption of thechip appears in Table I.

Each 11-bit ADC sample is encoded as a 16-bit wordusing an extended (11,16) Hamming code, which providesSECDED (Single Error Correction; Double Error Detection)capability, providing robust data transmission with high BER.Fixed frame marker words are added to the Hamming encodedamplifier data, and the 5 Mbps serial data is then BPSKencoded. A capacitive modulator that is digitally configurableto values between 63 fF and 940 fF produces PSK backscatter.

The neural and EMG amplifiers have fully differentialarchitectures. The use of differential signaling throughout addsimmunity to common-mode noise and power supply noise. Ahigh-speed analog multiplexer connects one selected amplifierto an 11-bit successive approximation ADC with a differentialinput and bandgap voltage reference.

The neural amplifiers each have a simulated bandwidth of250 Hz to 10 kHz with a gain of 500 V/V and a maximuminput range of ±2.4 mV. The simulated input-referred noiseof each neural amplifier is 4 µVrms. The ADC LSB step sizeis 2.3 µV, referred to the input. Simulation indicates that eachneural amp consumes 20 µW of power.

The EMG amplifiers each have a simulated bandwidth of5 Hz to 700 Hz with a gain of 50 V/V and a full-scale inputrange of ±24 mV. The simulated input-referred noise of each

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902-928 MHz Synthesizer! Low Pass

Filter!Fc = 1.2GHz!

Microcontroller!Level!Conversion!

Modulation!

Vapc!

Pulse Shaping Filter!

SPI!Control!Bus!

LO to Receiver!

Transmit Antenna

RF Power Amplifier!+30dBm to +36dBm!

Fig. 5: Block diagram of the base station transmitter (BSTx)

EMG amplifier is 22 µVrms. The ADC LSB step size is 23 µV,referred to the input. Simulation indicates that each EMG ampconsumes 0.3 µW of power.

The DC amplifiers have a 0 to 4.9 V input range (using anon-chip voltage divider). The ADC LSB step size is 2.4 mV,referred to the input. One of the DC amplifiers is permanentlyconnected to the output of the RF power recovery circuit, andthus monitors the unregulated voltage supply of the chip. Theother DC amplifier is available for use with optional off-chipsensors.

III. WIRELESS POWER FOR THE TELEMETRY SYSTEM

An on-chip RF power recovery circuit uses a 4X voltagerectifier/multiplier circuit (Fig. 4) to harvest power from anoff-chip dipole antenna. The unregulated dc voltage from thiscircuit feeds a bandgap-reference 1.23 V low dropout (LDO)voltage regulator. The dropout voltage is 80 mV, so only1.31 V from the RF power recovery circuit is required to powerthe chip.

At 915 MHz (in the center of the 902-928 MHz ISM band),simulation indicates an RF power harvester efficiency of 36%including mismatch losses. Because Libellula tend to captureprey within 1–2 m of their perch, a perch-mounted RHCPpatch antenna has been selected for this application. Thepreliminary link budget analysis presented in Table II indicatesa maximum operating distance of 5 m from the transmittingantenna. The dragonfly flight arena in which experiments willbe conducted approximates free space due to its large size(5 m x 5 m x 5 m) and freedom from obstructions. The flightarena can be fitted with RF absorber (EccosorbTM) as neededto reduce reflections.

TABLE II: Wireless Power Link Budget

Transmitter output power Pt 36 dBmTransmitter antenna gain Gt 9 dBiReceiver (insect) antenna gain Gr 0 dBiOperating wavelength λ 33 cmReceived power at IC input terminals Pr 4 dBmIC power harvester + mismatch efficiency η 49 %DC power consumed by IC Pth 1.23 mWPower-up threshold distance r|Pr = 4 dBm

† 5 m†Experimentally confirmed by dipole substitution

IV. BASE STATION TRANSMITTER (BSTX)

Because of the relatively high power consumption of thewireless neural telemetry system (1.23 mW) compared to

Fig. 6: Photograph of the BSTx circuitry

Fig. 7: Measured BSTx local oscillator phase noise

typical UHF RFID tags (≈ 10 µW) a much higher EIRPis required to achieve similar operating distances. The basestation transmitter (BSTx) is able to deliver an RF outputpower of up to +36 dBm and is typically used with antennagain of 8–10 dBi, yielding an EIRP of up to +46 dBm.These power levels exceed the FCC Part 15.247 EIRP limitof +36 dBm EIRP, but are permitted under the FCC’s Part 18rules for industrial, scientific, and medical (ISM) systems.

A block diagram of the BSTx is shown in Fig. 5, and aphoto is shown in Fig. 6. A Texas Instruments MSP430F2011microcontroller is used to control the transmitter. The micro-controller programs the frequency synthesizer to generate a902–928 MHz carrier, which is amplified by a power amplifiermodule specified for continuous duty at +36 dBm output.All conducted harmonic and out-of-band spurious outputs aresuppressed in excess of 70 dB. The BSTx microcontrollercan also amplitude modulate the power amplifier to sendaddressing commands from the BSTx to future generationsof the neural telemetry system.

Due to the full-duplex on-channel nature of modulatedbackscatter communication, receiver performance is typicallylimited by strong-signal handling (linearity) as well as localoscillator phase noise. Measured LO phase noise (Fig. 7) isbetter than -129 dBc/Hz in the critical 1 MHz – 10 MHz carrieroffset regime where the BPSK encoded backscatter is present.Transmitter-receiver isolation is maximized with a bistatic Tx-Rx antenna pair.

V. BASE STATION RECEIVER (BSRX)

A block diagram of the BSRx is shown in Fig. 8 and aphotograph of the receiver circuitry is shown in Fig. 9. Thebase station receiver (BSRx) is a homodyne receiver witha digitized baseband section. Unlike typical non-backscattercommunication systems, the transmitted carrier is alwayspresent during reception. The receiver’s analog front end

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Receive Antenna

!"#$%&'()%"*'+",'

I/Q de- mod

I

Q

LO Path

VGAs

I ADC

Q ADC

FIR Bandpass

Phase Rotation To I Axis

Correlators !1 and "2

Data Clock Recovery

PLL Hamming Decoder / Framing

Clock_In

Data_In

-.&.*#$'/#012#",'

USB 2.0

Fig. 8: Block diagram of the base station receiver (BSRx)

(AFE) is thus optimized for large signal performance at theexpense of noise figure. The receiver’s AFE has a measured1 dB compression point of +14 dBm with a noise figureto analog baseband of 13 dB. Given the high input-referrednoise of the baseband ADCs (1 LSB / 43 µVrms) the systemnoise figure is approximately 19 dB. The relatively highnoise figure does not limit receiver performance at telemetrysystem operating distances of up to 5 m. Within the 5 MHzbaseband signal bandwidth the input-referred noise power isapproximately -88 dBm, yielding a sensitivity of better than-70 dBm at a BER of 10−5. In practice, sensitivity is somewhatreduced by partial phase noise correlation in the transmitter-receiver system. At the telemetry IC’s terminal power-upthreshold (+4 dBm RF at the IC terminals) and assuming abackscatter ratio of -15 dB, the expected signal power at theBSRx is -47 dBm yielding a receive-system implementationmargin of ≈ 23 dB.

Baseband signals filtered by a matched pair of bandpassfilters to reject out of band noise, decimated, then rotatedto the in-phase axis to bit-slice the BPSK-encoded signal.A digital phase locked loop and symbol correlators extractclock and data prior to Hamming decoding with a LUT-basedapproach. A USB 2.0 port interfaces the received data to a PCfor subsequent processing. Several time-synchronous digitalinputs are also carried along with the received data to achievesynchronization between the telemetry data stream and a videomotion capture system.

VI. SUMMARY

We present preliminary results toward the development ofa digital neural/EMG telemetry system with a measured flightpackage mass of only 38 mg. A single-chip telemetry ICemploying RF power harvesting for battery-free operation,with communication via modulated backscatter in the UHF(902–928 MHz) band is described along with a companionbase station transceiver including an RF transmitter and adigital receiver. The IC has been fabricated in a commercial0.35 µm 4M1P process.

Fig. 9: BSRx analog front end and digital baseband sections

VII. ACKNOWLEDGMENTS

This work was supported in part by the Howard HughesMedical Institute.

REFERENCES

[1] M. Fee and A. Leonardo, “Miniature motorized microdrive and com-mutator system for chronic neural recordings in small animals,” J.Neuroscience Methods, no. 112, pp. 83–94, 2001.

[2] T. A. Szuts, V. Fadeyev, S. Kachiguine, A. Sher, M. V. Grivich,M. Agrochao, P. Hottowy, W. Dabrowski, E. V. Lubenov, A. G. Siapas,N. Uchida, A. M. Litke, and M. Meister, “A wireless multi-channelneural amplifier for freely moving animals,” Nature Neuroscience,vol. 14, no. 2, pp. 263–U363, Feb. 2011.

[3] R. E. Hampson, V. Collins, and S. A. Deadwyler, “A wireless recordingsystem that utilizes Bluetooth technology to transmit neural activity infreely moving animals,” J Neurosci Methods, vol. 182, no. 2, pp. 195–204, Sep 2009.

[4] E. Greenwald, M. Mollazadeh, C. Hu, W. Tang, E. Culurciello, andN. V. Thakor, “A VLSI neural monitoring system with ultra-widebandtelemetry for awake behaving subjects,” IEEE Transactions On Biomed-ical Circuits and Systems, vol. 5, no. 2, pp. 112–119, Apr. 2011.

[5] R. Harrison, H. Fotowat, R. Chan, R. J. Kier, R. Olberg, A. Leonardo,and F. Gabbiani, “Wireless neural/EMG telemetry systems for smallfreely moving animals,” IEEE Transactions on Biomedical Circuits andSystems, vol. 5, no. 2, pp. 103–111, April 2011.

[6] D. Yeager, F. Zhang, A. Zarrasvand, N. George, R. Daniel, and B. Otis,“A 9µA, addressable Gen2 sensor tag for biosignal acquisition,” IEEEJournal of Solid-State Circuits, vol. 45, no. 10, pp. 2198–2209, Oct.2010.

[7] Z. Xiao, C. Tang, C. Dougherty, and R. Bashirullah, “A 20µW neuralrecording tag with supply-current modulated AFE in 0.13µm CMOS,”in Proc. IEEE International Solid-State Circuits Conference, 2010, pp.122–123.

[8] M. Lewicki, “A review of methods for spike sorting: the detection andclassification of neural action potentials,” Network computation in neuralsystems, vol. 9, no. 4, pp. 53–78, 1998.

[9] Z. S. Zumsteg, R. E. Ahmed, G. Santhanam, K. V. Shenoy, and T. H.Meng, “Power feasibility of implantable digital spike-sorting circuits forneural prosthetic systems,” Proc IEEE Eng Med Biol Soc, vol. 6, pp.4237–40, 2004.

[10] R. Olberg, “Identified target-selective visual interneurons descendingfrom the dragonfly brain,” J. Comp. Physiol A, vol. 159, pp. 827–840,1986.