Power and data

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Power and data
Microsytèmes dédiés aux applications
médicales intracorticales: réalisation et
expérimentation
Mohamad Sawan, Fellow, IEEE
Chaire de recherche de recherche du Canada sur les dispositifs
médicaux intelligents
Laboratoire de neurotechnologies Polystim
Département de génie électrique
ÉCOLE
POLYTECHNIQUE
M O N T R É A L
FETCH’2007
Villard de lans, France
10 janvier 2007
Main technological breakthrough
-- FES based SMDs - 1947,
 1952,
 1960,
 1961,
 1980,
 1984,
transistor allows designs suitable for implants;
1st external pacemaker : size of a table radio;
totally implanted pacemaker (Buffalo);
peroneal nerve stimulator for foot drop;
first chip was used to design small pacemakers;
FDA approved the first cochlear implant.
 Pacemaker: More than 500,000 pacemakers annually;
 Defibrillator: Around 50,000 implants annually;
 Cochlear implant: > 100,000 people worldwide;
 FES: Recuperate hands & legs movements of patients;
 Deep Brain Stimulation for Parkinson, scleroses, etc;
 Vagus nerve in the neck to treat depression & epilepsy.
Page 2
Research Program of Polystim Lab.
-- Mixed-signal circuits, RF, HVMOS, MEMS: Design, test and assembly --
 Wireless intracortical microsystems
 Monitoring and recording of neural activities
 Microstimulation in the visual region
 Bladder dysfunctions
 Dual stimulation and volume & pressure measurement
 Respiration
 Diagnostic catheters
 Apnea: monitoring and stimulation
 Sensors and sensing networks
 Artificial leg movement by recording & processing ENGs
 Non-invasive measurements (ultrasonic & optical devices)
 Laboratory-on-chip for advanced diagnostic tools.
Page 3
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
Research Program (continued)
-- Smart medical devices -Sensitive Nerve (afferent)
Sensitive
Tissues
Brain
Spinal
cord
Electronic
device
Controller
Muscle
Motor (efferent)
Page 5
Sensors
Smart medical devices
-- Typical topology --
External
controller
Receiver
Test
stimuli
Stimuli
generator
Modulator
AC/DC
Supply
Demodulator
Main
Controller
Power
Back
telemetry
Data
processing
Skin
Page 6
Measure
&
digitize
Current
sources
MUX
DeMUX
Electrodes
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
Wireless inductive link
-- Power transfer efficiency -Inductive link
Rectifier
Vrec
R2
C1
M
Vs
*
R1
~
L1
*
L2
C3
C2
1
η
total
η
Page 8
2
=
total
R1C1 Pload +
1
2
Voltage
regulator
Linear
regulator
k 2V 2 C 2
DC
k 2C 2 (V rec + 2V diode ) V
= ηrflink η rectifier η regulator ~
DC
12 %
VDC
LOAD
Wireless dedicated links
-- External and internal interfaces -Rectifier
- Inductive
link
- Resonance
- Data
processing.
Off chip inductor
- Power
amplifier
calibration
External coil
- Power
supply
Shunt
regulator
Load
Shift
Key
(LSK)
ASK/PSK
Demodulator
Start-up
Page 9
Switched
Capacitor
DC/DC
Encoder
ADC
LDO Reg 1
VDD1
LDO Reg 2
VDD2
LDO Reg n
VDDn
M
U
X
Analog
FrontEnds
(1..n)
Controller/
Stimulator
Protection
Clock Generator
Tissues contacts
Control unit
RF LINK to Transfer Data
-- BPSK demodulation -Gilbert multiplier
Arm
LP Filter
I branch
m(t) cos(θ1−θ2)
2 sin(ω1t+θ2)
Data In
m(t) sin(ω1t+θ1)
m(t) = 1 or –1
VCO
Low Pass
Filter
Gilbert
Phase
Shifter 90
m(t) sin 2(θ1−θ2)
multiplier
2
2 cos (ω1t+θ2)
Arm
LP Filter
Gilbert multiplier
m(t) sin(θ1−θ2)
Q branch
• Hard-limited Costas loop circuit
• Coherent : recover carrier / data in the same loop
Page 10
Data
Out
RF LINK to Transfer Data
-- BPSK demodulation implementation -I branch
Arm Filter
Dout
Data in
Clk
Quadrature
signal
generator
Receiver
coil
VCO
Loop
Filter
Chopper
multiplier
Arm Filter
Q branch
Digital domain
Analog domain
Requirements: 1) Fully integrated, 2) Low power consumption, 3) Fully differential
Page 11
RF LINK CMOS circuits
-- Comparator with hysteresis -VDD
M16 M14 M10 M7
Von
M15 M13 M9
CP
M5
M8 M12 M20
M21
M6 M11 M19
M1
M17
Vop
1
0
Received carrier
Vinp
Vinn
M18
PSK input
M22
M2
CN
M3
BN
M4
M23
M24
Hard-limited carrier
VSS
Fully differential
comparator
Page 12
Simulation result of the
comparator
1
RF LINK CMOS circuits (cont’d)
-- The voltage controlled oscillator -VDD
M11
M12
BP
CP
M13
M14
MP11
M3
M4
Voutp
MP12
R1
Vinp
M9
Ic
M10
M1
Page 13
Vtune
C1
M15
M17
MN14
M5
M6
M16
M18
MN13
M7
M8
Gm Cell
Voutn
ictrl
Vinn
CN
M2
VSS
Relaxation Oscillator
RF LINK to Transfer Power & Data
-- The BPSK demodulator chip -Simulation &
Experimental results
Monolithic
implementation
Parameters
Transmitter
Coil (PCB)
Receiver
Coil (PCB)
Coefficient
Tech CMOS
ASK
demodulators
[LIU2000]
[AKI1998]
Page
14
M. Sawan
Data rate
(kbps)
< 250
< 125
Power
consumption
N/A
2 mW
Simulated
1.25 µ H
1.25 µ H
Measured
5 turns,
D = 3.5 cm
5 turns,
D = 2.7 cm
0.07
0.18 µm
Distance 1.5
0.18 µm
Circuit area
Carrier Freq.
Supply Volt.
NA
13.56 MHz
1.8 V
0.19 mm2
10 MHz
1.8V/3.3V
VCO gain
Data rate
Power Cons.
14.7 M
1.51 Mbps
652 µ W
13.5 M rad/s
1.12Mbps
610 µ W
NA
1.00E-04
BER
RF LINK to Transfer Data
-- QPSK demodulation implementation -LPF
Incoming
OQPSK
Signal
sin("1t + !2)
VCO
Vs (t)
Data Out A
Vd(t) $
LPF
+
90°#
Phase Shifter
Data Out B
cos("1t +!2)
LPF
QPSK
CMOS
0.18µm
13.56
MHz
4Mbps*
8Mbps**
0.76 mW
at 4Mbps
*Postlayout
**Matlab
Page 15
Power transfer
-- Efficiency & safety -External Controller
C1
Data
Modulator
Skin
Rectifier
PA
Vdd
Battery
Implant
Switching
Regulator
ASK Demodulator /
DAC/Decoder
L2
L1
Shunt
regulator
C2
Load
Shift
Key
(LSK)
To/From
Other
parts
Encoder
ASK/PSK Demodulator
0.4
0.35
0.3
0.25
Power Efficiency
Versus Load Power
W/O Feedback
0.2
0.15
0.1
W Feedback
0.05
0.002
Page 16
0.004
0.006
0.008
0.01
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
The visual cortical stimulator
-- Evolution / Approaches - Researchers develop solutions

1960s, investigation of creating points of
lights
 Several approaches explored
Artificial retina
 Optic nerves
 Surface stimulation of the visual cortex
 Intracortical stimulation of the visual
cortex

 Intracortical stimulation
It does not depend on the health of the
eye or optic nerve
 Allows high precision with little power
 First prototype built few years ago

Page 18
The visual cortical stimulator
-- Image/data processing -External components
Image
Acquisition
Program
GUI
Image
Enhancement
Experimentation data
Visuotopic
map
Config
Visual Field
Emulator
Artificial
Vicuotopic
Map gen
Image
fitting
SSA to
PVC
mapping
Direct
Mapping
Low level
Pulse
sequence
Low Level
Data Managment
Encoding
& timing
Transmision
Page 19
PVC to
SSA
Maping
Ordering
Implantable
components
Interface
Module
Display
Module #1
Module #2
Module #N
Matrices of
electrodes
Inputs
Visuotopic
Map
VDB source
Fovea
Inverse
Stim. Site to
PVC Mapping
The visual cortical stimulator
-- Implant architecture -PWR
Stim.
Mod.
Stim.
Mod.
Serial
in
Interface
Module
Data
Ref
Clk
Stim
Mod.
DAC
#1
DAC
#3
Bandgap
Bias
Vout
Stim
Mod.
DAC
#2
Electrode
Switch
Matrix
Controller
Coil
DAC
#0
R2R

Multichannel
stimulation
ETC monitoring
 Sampling Prog.
Time

Page 20
Measure voltage &
current.
Hi-Z
Imonit.
REF
REF
To/From
Controller

Enable
Clk
Conv
ADC
Out
+
-
Hi-Z
Vmonit.
Analog
Monit. Bus
Current
Monit.
Controller
 Stimulate/Monit. Module
Normal
Stim.
Vdd
Vss
R2R
REF
The visual cortical stimulator
-- Implementation results - Stimulation Module (4x4)
 CMOS 0.18 µm, ~60 000 Gates
Downlink
 Downlink
 > 1 Mbps @ 13.56 MHz, Δ = 67%
 Uplink : 200 kb/s
 Power: <1mW/SM @ 1MHz
 > 100 mW load; P (err) < 10-6
TEST
structures
CTRL
Page 21
DACs
BIA
S
MONITORING
R2R AMP
ELECTRODES
CONN / CTRL
Monitoring
Image acquisition/processing
-- Power pre-regulation -
With large electrode arrays, stimulation current represents
a major part of power consumption


Predetermined image scanning results in large current variations
Adaptive scanning method regulates current demand
 Equalize the required power and reduce the peak demands
Fixed
Scan average
Min. Current
Max. Current
Adaptive
Scan average
Stimulation current
for 1 sample frame
Page 22
t
Total stimulation
current
The visual cortical stimulator
-- Second prototype -
Complete 4x4
channels
2x2x2 mm3;
 Monitoring;
 Microstimulation;
 Flexibility, versatility,…


Tests in vivo
Presently in rats in
collaboration with the
department of Psychology
McGill
 In monkeys to begin
shortely.

Page 23
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
Multichannel neural recording
-- Requirements and challenges - Subject to severe form factor – small integration area
 Low power dissipation
 Restricted to 80 mW/cm2 (~130uW per channel)
 Neural signal characteristics
 Amplitude < 100 µV << Noise Level
 Frequency 100 Hz - 20 KHz
 Bandwidth limitations
 Present wireless data rate < 2 Mbps
 100 channels sensor = 24 Mbps!
 In situ signal conditioning and digital signal processing
 Data reduction, compression, pre-processing
 In situ Analysis.
Page 25
Analog signal conditioning
-- Low-noise low-power integrated bioamplifier -v in
vf
OTA1
+
v out
CL
Ma
CI
Mb
OTA2
+
 Close loop transfer function :
Input-referred noise
Power consumption
Integration area
Phase margin
Page 26
5.4 μVrms
8.5 μW
< 0.064 mm2
> 60°
v ref
H ( s) =
− sτ A
oa 1
sτ + A
oa 1
fhp-3dB = Aoa1 / (2πτ)
Integrated Bioamplifier
-- Frequency and phase responses -55
Gain (dB)
50
100
50
45
0
40
-50
Gain
Phase
35
-100
-150
30
10
2
10
3
Frequency (Hz)
Page 27
10
4
10
5
Phase Angle (degree)
150
Multichannel neural sensor design
-- Conditioning and digitization -Analog inputs
Digital outputs Supply
I/O pads
1 channel




1 low-noise
bioamplifier
1 SAR-ADC
2 output
registers
A = 0.25 mm x
0.39 mm.
The chip includes:
 16 recording
channels
 Digital readout
 Test circuits
 8 digital outputs
 3 test I/O
Multiplexers
Test circuits
Bias circuits
Clock generator
Supply
Page 28
Analog inputs
Digital inputs
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
The bladder controller
-- Selective and permanent stimulations -
Selective stimulation to improve voiding:



HF stimuli for somatic fibres which innervate the sphincter.
LF stimuli for parasympathetic fibres which innervate the detrusor
Permanent LF stimulation using low amplitude train waveform to:
 Prevent the bladder hyperreflexia
 Maintain the bladder shape.
Skin
User
interface
Bipolar cuff
electrode
Power
Data
RF emitter
Page 30
1/Freq
Amp
Dualstimulator
Bladder
PW
The bladder controller
-- Dual stimulation implant -RF_PWR
Switch
#1
Power
recovery
Antenna
ASK
demodulator
Controller
#1
(FPGA)
Bus
controller
Other
control
signals
MANCH_IN
Manchester
decoder
DATA_IN
CLOCK
READY
Controller
#2
(RISC µP)
Switch
#2
Battery
Switch
#2
PIC_PWR
SWT_PWR
SYS_ON
Serial
DAC
Current
source
Nerve
d
c
Current (mA)
b
e
f
a
Page 31
Current
switches
g
Time (Sec.)
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
Laboratory-on-Chip
-- Integration of Microfluidic Structures into
Microelectronic devices -Epoxy encapsulation
Microtube
Microflow
Microchannel
Microchamber
Sensing electrode
Microelectronics chip
Electronics board
Page 33
Experimental Results
-- Capacitive sensor - Circuit implemented in the same CMOS chip.
M7
M2 Ck1 M1
Vb1
Vout
CR
M13
M14
Ck2
Gnd
CS
Is-IR
Gnd
Interdigitated electrode
(One of capacitances)
Cin
Interdigitated electrode
M10
CBCM
Cin
Page 34
Laboratory-on-Chip
-- Direct-Write CMOS Based LOC - Direct write CMOS-based
Capacitive electrode
A new approach for the
fabrication of microfluidics

Robotic deposition of
fugitive ink
 Coating of epoxy on
substrate and curing it
 Extraction of ink and
shaping a microfluidic
device


Page 35
Experimental results.
Dielectrophoresis
electrode
Lab-on-chip
Capacitive electrode
Electrode
Flowing
droplet
«Microsytèmes dédiés aux applications médicales
intracorticales: réalisation et expérimentation»
OUTLINE
 Introduction
 Wireless
link (Power and data)
 Intracortical
stimulation & monitoring (Vision)
 Intracortical
recording (multichannel data
acquisition)
 Peripheral
nerves connected devices
(micturation and apnea control)
 Laboratory-on-chip
 Collaborations,
 Summary
for particle detection
and infrastructure
Regrouper pour innover
Alliance for innovation
http://www.resmiq.org
Université de
Montréal
Microsystems Strategic Alliance
Université of Québec
McGill Mohamad Sawan, directeur depuis 1999.
Université du
Québec Contenu
à Montréal  Domaines de recherche
École Polytechnique  Personnels, résultats et contributions
de Montréal
 Projets et infrastructures
École de technologie  Promotion de travaux (Newcas).
supérieure
Université Concordia
Domaines de recherche
--- Applications --Dispositifs
médicaux
Technologies
micro et nanoélectroniques
émergentes
Circuits &
systèmes
(analogique,
numérique, RF)
Sécurité,
Multimédia
Contrôle
industriel
Nanoélectronique
Page 38
Télécom.
Optiques
& sans fil
Modélisation,
synthèse &
co-design
Test,
vérification &
caractérisation
Assemblage µsystèmes
Contributions et réalisation
--- Exemples ---
Transferts technologiques
1
2
3
4
5
:
:
:
:
:
Cinéma maison 3D (Sensio)
Radio programmable (Canadian Marconi)
Annulation des interférences 3G (Axiocom)
Implants électroniques (Victhom)
Composants haute précision (LTRIM)
Travaux d’envergure actuelles
1
2
3
4
5
6
7
8
Page 39
:
:
:
:
:
:
:
:
Micro et nano-robots
Microsystèmes intégrés (Lab sur puce)
Fluoromètres miniatures
RFID pour localisation 3D
Synthèse et vérification SoC
CODEC voix et image
Dispositifs médicaux
Autres (> 100 projets).
Collaborations
--- Nationale et internationale ---
8 universités
Au Québec
CMC
µsystems
Paris, Bordeaux,
Montpellier, Metz,
Lyon, ..
Tunisie, Maroc,
Liban, etc..
Page 40
Autres universités
au Canada
EU, Chine,
Inde, …
Industries
au Québec
Industries
Ailleurs au Canada
http://www.polystim.org
-- Collaborations with medical institutions -Royal Victoria
Bladder control
Mtl. Neurologic Inst.
Vision
Respiration
Ste-Justine
Notre-Dame
Electrodes
Epilepsy
Sacré-Cœur
Catheters
Page 41
Hôtel-Dieu
CHUS
Imaging
IRCM
Monitoring
http://www.lasem.org
Assembly
Infrastructure
CFI Room A345
Page 42
 ReSMiQ founded an annual international conference IEEE-
NEWCAS
2003 : Montréal, 70 participants
 2004 : Montréal, 90 participants
 2005 : Québec, 110 participants
 2006 : Gatineau - Ottawa, 125 participants

http://www.newcas.org
Conclusion
 Brève description de quelques projets de l’équipe Polystim
- Multidisciplinaires
- Plusieurs intervenants
 L’enregistrement multicanaux nous permettra de
comprendre le mécanisme de la vision et autres fonctions
du SNC.
 Les progrès technologiques nous facilitent de plus en plus la
tâche pour réaliser de nombreux implants et améliorer la
qualité de vie de patients
 Dispositifs médicaux pour surveiller et stimuler dans la
région visuelle du cortex seront bientôt disponibles pour
permettre une vraie vision pour les non-voyants.
 Aperçu sur le regroupement stratégique en microsystèmes
du Québec (ReSMiQ).
Page 44
Main references
BUFFONI, L.X., SAWAN, M., COULOMBE, J., “Image Processing Strategies Dedicated to Visual Cortical
Stimulators: A Survey”, Artificial Organs J., Vol 29, no 8, 2005, pp. 658-664.
CRAMPON, M.A., SAWAN, M., BRAILOVSKI, V., TROCHU, F., “New easy to install nerve cuff electrode
based on a shape memory alloy armature: fabrication, modelling and experimental results”, Int. J. of
Bio. Materials and Eng., 2002, V. 23, N. 5, pp. 392-395.
COULOMBE, J., CARNIGUIAN, S., SAWAN, M., “A Power Efficient Electronic Implant For A Visual Cortical
Stimulator”, Artificial Organs J., Vol. 29, no. 3, 2005, pp. 233-238.
DJEMOUAI, A., SAWAN, M., SLAMANI, M., "New Frequency-Locked Loop Based on CMOS Frequency-toVoltage Converter: Design and Implementation", IEEE Trans. CAS-II, Vol. 48, No. 5, 2001, p. 441-449.
HU, Y., SAWAN, M., “A Fully-Integrated Low-Power BPSK Demodulator for Implantable Medical Devices”,
IEEE Transactions on CAS-I, Vol. 52, no. 12, 2005, pp. 2552-2562.
HU, Y., SAWAN, M., EL-GAMAL, M.“An Integrated Power Recovery Module Dedicated to Implantable
Devices”, Springer Analog ICs & Signal Processing J., Vol. 42, no. 3, 2005, pp. 171-181.
HU, Y., SAWAN, M., "CMOS Front-end Amplifier Dedicated to Monitor Very Low Amplitude Signal from
Implantable Sensors", Kluwer Analog ICs & Signal Processing J., 2002, Vol.33, pp. 29-41.
LU, Z., HU, Y., SAWAN, M., “A 900 mV 66 µW Sigma-Delta Modulator Dedicated to Implantable Sensors”,
IEICE Transactions on Information and Systems, Vol. E88-D, no. 7, July 2005, pp. 1610-1617.
NORMANDIN, F., SAWAN, M., FAUBERT, J., “A New Integrated Front-End for a Non-Invasive Brain Imaging
System Based on Near-Infrared Spectroreflectometry”, IEEE Trans. CAS-I, Vol. 52, no. 12, 2005, pp.
2663-2671.
SAWAN, M., TREPANIER, A., TREPANIER, J.L., AUDET, Y., “A New CMOS Multimode Digital Pixel Sensor
Dedicated to an Implantable Visual Cortical Stimulator”, To appear in Springer Analog ICs & Signal
Processing J., 2006.
SAWAN, M., HU, Y., COULOMBE, J., “Wireless Smart Implants Dedicated to Multichannel Monitoring and
Microstimulation”, Invited paper in IEEE Circuits and Systems Magazine, Vol. 5, 2005, pp. 21-39.
Page 45