USING ELECTRICAL STIMULATION
TO RESTORE FUNCTION TO
PARALYZED MUSCLES
William Durfee
Department of Mechanical Engineering
University of Minnesota
Kurt Korkowski, Ben Dunn,
Karl Oberjohn, Brent Harrold
Department of Mechanical Engineering
University of Minnesota
Michael Goldfarb, Heather Beck
Karen Palmer, Jeff Chiou
Department of Mechanical Engineering
Massachusetts Institute of Technology
Gary Goldish, Rich Scarlotto
Physical Med. & Rehab. Service
VA Medical Center, Minneapolis, MN
Allen Wiegner, Nancy Walsh
Spinal Cord Injury Service
VA Medical Center, West Roxbury, MA
HUMAN/MACHINE DESIGN LAB
Department of Mechanical Engineering
University of Minnesota
(www.me.umn.edu/divisions/design/hmd/)
• Stimulated Muscles = Power
• Brace = Trajectory guidance
u
F
• Brake = Control, stability
T
x,v
Haptic interfaces for virtual
product prototyping
Active Element
u
IRC
Activation Dynamics
(2nd order)
X
CE Force-Length
V
CE Force-Velocity
X
Force
Fscale
•
Passive Element
X
PE Force-Length
V
PE Force-Velocity
•
Smart orthotics +
electrical stimulation
for gait restoration
Muscle mechanics
OUTLINE
 What
is Functional Electrical Stimulation
(FES)?
 How FES can be used to restore motion
 State-of-the-art
– Why it’s hard
– Commercial products
 FES
research at the U:
– FES + "smart" orthosis
– Modeling and control
FES APPLICATIONS
 Bladder
stimulation (incontinence)
 Cerebellar stimulation (movement disorders)
 Sensory substitution
 Visual prostheses (blindness)
 Auditory prostheses (deafness)
 Pain suppression (TNS)
 Pacemakers
 Limb control (paralysis)
HOW FES WORKS
Brain
Spinal Cord
Stimulator
Limb
SPINAL CORD INJURY





NUMBERS
150,000 in U.S.
8,000 new cases each
year
1/2 quadriplegic, 1/2
paraplegic
LEADING CAUSES
–
–
–
–
Automobiles
Guns
Sports (diving)
Falls
AGE GROUP
Range: 15-29
Mean: 23
SPINAL CORD INJURY





NUMBERS
150,000 in U.S.
8,000 new cases each
year
1/2 quadriplegic, 1/2
paraplegic
LEADING CAUSES
–
–
–
–
Automobiles
Guns
Sports (diving)
Falls
AGE GROUP
Range: 15-29
Mean: 23
FES BICYCLE ERGOMETER
FreeHand
FreeHand
FreeHand (NeuroControl)
Handmaster
(NESS)
Parastep (Sigmedics)
WalkAide (Neuromotion)
This is the story…...of the
multimillion-dollar functional
electrical stimulation (FES) project
that got them walking….. It's about
an ambitious but flawed technology
and of questionable medical ethics.
And it's about a tightknit research
community so convinced of its
promise that it would tolerate lessthan-acceptable standards of care
for its human subjects.
Inside Khawam's legs is a virtual
birdnest of corroding electrodes
….. He and his doctors see a clear
link between the infections and
the electrodes….."Mr. Khawam's
prognosis is decidedly
poor…..either above-or belowthe-knee amputation….."
New Mobility, June 1997
Wired For
Walking:
BY Sam Maddox
Fifteen years ago, Bassam "Sam" Khawam, a 22-year-old Lebanese
American living in the Cleveland suburbs, was paralyzed at T8-9
by a bullet. Khawam was big and physical, a black belt in karate.
He was given the usual spinal cord injury prognosis: Get used to
the chair, son, you're not going far without it. Khawam took the
news the way many young, strong guys who join the gimp world
do. He didn't buy it.
"You are 22 and it happens to you," says Khawam, now a rehab
engineer and father of two in Spokane, Wash. "You would want to
walk again too."
This is the story of Khawam and of a handful of other paralyzed
research subjects, of the multimillion-dollar functional electrical
stimulation (FES) project that got them walking, and of the scientist
who lined up the money and ran the lab. It's a story of good
intentions and good press on the side of science, and bad luck and
bad faith as seen by the project's participants. It's about an
ambitious but flawed technology and of questionable medical
ethics. And it's about a tightknit research community so convinced
of its promise that it would tolerate less-than-acceptable standards
of care for its human subjects.
Inside Khawam's legs is a virtual birdnest of corroding electrodes
that cannot be removed without destructive surgery. He has had
infections requiring antibiotics, plastic surgery and hospitalization.
He and his doctors see a clear link between the infections and the
electrodes, and one doctor suggested removing all of Khawam's
thigh and calf muscle as the only way to get the hardware out.
Another offers this bleak statement: "Mr. Khawam's prognosis is
decidedly poor, as the future course of medical treatment may
include either above-or below-the-knee amputation to rid him of a
constant source of infection."
LOWER LIMB FES
FEXT ERNAL
Inputs
CONT ROL
STIMULAT OR
Measurements
(The UNH Robot Lab, www.ece.unh.edu/robots/rbt_home.htm)
IS IT LIKE A BIPED ROBOT?
ROBOT CONTROL
Commands
CONTROLLER
MOTORS
SENSORS
Desired Task
SEGMENT
DYNAMICS/KINEMATICS
Disturbances
FES CONTROL
Cognitive feedback
?
CNS PROCESSOR
BRAIN
VISUAL
VESTIBULAR
Commands
?
SPINAL
NATURAL
SENSORS
UPPER LIMB SEGMENT
DYNAMICS/KINEMATICS
MUSCLES
Disturbances
Spinal Lesion
CONTROLLER
NATURAL
SENSORS
ARTIFICIAL
SENSORS
Desired Task
SPINAL CIRCUITS
MUSCLES
LOWER LIMB SEGMENT
DYNAMICS/KINEMATICS
Disturbances
SERVOMOTORS AS ACTUATORS
Torque
Torque
Current
Speed
Linear, time-invariant
MUSCLES AS ACTUATORS
Force = f(neural input, length, velocity, time, ...)
F
F
Activation
F
Velocity
Tim e
High power/weight,
but nonlinear, time-varying and uni-directional
WHAT MAKES FES DIFFERENT?





Not enough muscles
Not enough sensors
Muscle force too low
Muscle fatigue
Spasticity








Weight constraints
Size constraints
Cosmetic constraints
Ease-of-use constraints
Reliability
Implanted systems
No sensory feedback
User control?
WHY MODEL?
Inputs
CONTROL
STIMULATOR
Measurements

Complex system
– Multi-link inverted pendulum
– Nonlinear, time-varying actuators
(muscles)


Better models  Better control
Use model for:
– Designing "generic" controllers
– Prescribing/tuning custom
systems
MODEL VERIFICATION
Direct comparison with experimental data
 Predictive capability
 Parameterization to the subject

MODELING FOR CONTROL OF GAIT
•Rigid body links (10)
•Ideal joints
•Passive torques
•Active torques (muscles)
MODELING MUSCLE
u
F
x,v
u
T
Active (AE)
KSE
CE
KP
BP
“Muscle” = activity from
single stim channel
Joint-space model --> no
knowledge of anatomy
needed
Passive (PE)
3 inputs (u,x,v), 1 output,
modified Hill-type model
ISOMETRIC MUSCLE
Hammerstein model
force
stim
Static
nonlinearity
Linear
dynamic system
Identify LDS with impluse response
Identify SL by deconvolution
MODELING MUSCLE
Active Element
u
IRC
u
F
Activation Dynamics
(2nd order)
x,v
X
CE Force-Length
V
CE Force-Velocity
X
S
Fscale
Passive Element
X
PE Force-Length
S
V
PE Force-Velocity
Force
WHAT'S WRONG WITH THE
MUSCLE MODEL





Invariant F-A, F-L, F-V (no change with activation)
Invariant twitch dynamics (uniform fiber types)
Time-invariant (no fatigue)
Zero neural time-delay
Rigid SEC
XMT
XCE
XSE
CE
KSE
ISOLATED, ANIMAL MODEL MUSCLE
35
Model
30
Experiment
Force (N)
25
20
15
10
5
0
0
4
8
12
T ime (s)
(Durfee and Palmer, IEEE T rans. Biomed. Eng., 41(3):205-216, 1994)
16
INTACT, HUMAN MUSCLE
(Abushanab: Ph.D. Thesis, MIT, 1995)
EXPT VS. MODEL
Knee flexion (deg)
Hip flexion (deg)
40
30
20
0
2
4
Time (sec)
Experiment
Simulation
6
8
40
20
0
0
2
4
Time (sec)
6
8
WHERE WE ARE WITH MODELING
& IDENTIFICATION
 Goal
of modeling: simulation matches
experiment
 Subject-to-subject variation is large ==>
calibration is required
 How good is "good enough" will be
determined by control strategy
 Must extend to subjects with SCI
 Better experimental ID methods evolving
 More diverse verification tests evolving
PROBLEMS WITH FES-AIDED GAIT
(1)
Requires
precise, stable
control for
repeatable steps
Muscles are
nonlinear, timevarying
(2)
Need to walk
for reasonable
distances
Muscles fatigue
rapidly
PROPOSED SOLUTION:
Stimulation plus "smart" orthotics
BRACE (CBO) + FES
• Stimulated Muscles = Power
• Brace = Trajectory guidance
• Brake = Control, stability
CBO OVERVIEW, SPECIFICATIONS

JOINTS
–
–
–
–

2-dof hip, 1-dof knee, fixed ankle
hip adduction stop
magnetic particle brakes
Evoloid gear, 16:1 transmission
STRUCTURE
– aluminum, chromoly

WEIGHT, INERTIA
– 12.5 lbs, 10% of limb inertia

STIMULATION AND CONTROL
– 4-channel stimulation
– on/off stimulation control
– closed-loop brake control
Designed for RESEARCH use
(Goldfarb and Durfee, IEEE Tran Rehab Eng, 4(1):13-24, 1996)
CBO EVALUATION PROTOCOL
 4-channel
stimulation (quad + peroneal)
 Parallel bars, walker 5 - 10 m lengths
 Compare gait with and without CBO
 Speed/distance, quadriceps use,
repeatability
 Four subjects with paraplegia
FES
FES + CBO
INCREASED SPEED, DISTANCE
Gait Speed
Gait Distance
0.14
60
50
0.09
40
Distance (m)
0.1
0.08
Speed (m/s)
50
0.12
0.12
0.06
0.04
30
20
0.02
10
0
0
Without CBO
With CBO
25
Without CBO
With CBO
BETTER REPEATABILITY
With CBO
120
120
100
100
Knee angle (deg)
Knee angle (deg)
Without CBO
80
60
40
20
0
0
0.2
0.4
0.6
0.8
1
1.2
Time (sec)
1.4
1.6
1.8
2
80
60
40
20
0
0
0.2
0.4
0.6
0.8
1
1.2
Time (sec)
1.4
1.6
1.8
2
OPEN ISSUES


Substantial improvement in FES-aided gait.....but
preliminary, laboratory results only
Consumer-driven design (size, weight, ease of use)
Technical issues
Handling upper-limb inputs ???
Startle, stumble response ???
Fault tolerant equipment ???
Commercialization issues
Market size ???
User acceptance ???
Who pays !!??