USING ELECTRICAL STIMULATION TO RESTORE FUNCTION TO PARALYZED MUSCLES

William DurfeeDepartment 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 ScarlottoPhysical Med. & Rehab. ServiceVA Medical Center, Minneapolis, MN

Allen Wiegner, Nancy WalshSpinal Cord Injury ServiceVA Medical Center, West Roxbury, MA

• Stimulated Muscles = Power • Brace = Trajectory guidance • Brake = Control, stability

HUMAN/MACHINE DESIGN LABDepartment of Mechanical EngineeringUniversity of Minnesota(www.me.umn.edu/divisions/design/hmd/)

Fu

x,vT

X

PE Force-Velocity

CE Force-Velocity

Fscale

IRC

CE Force-Length

Activation Dynamics (2nd order)

PE Force-Length

u

V

X

V

X

Force

Passive Element

Active Element

Muscle mechanicsSmart orthotics +

electrical stimulation for gait restoration

Haptic interfaces for virtual product prototyping

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

Limb

Stimulator

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 GROUPRange: 15-29Mean: 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 GROUPRange: 15-29Mean: 23

FES BICYCLE ERGOMETER

FreeHand

FreeHand

FreeHand (NeuroControl)

Handmaster (NESS)

Parastep (Sigmedics)

WalkAide (Neuromotion)

New Mobility, June 1997

Wired ForWalking: 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."

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 less-than-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 below-the-knee amputation….."

LOWER LIMB FES

FEXTERNAL

CONTROL STIMULATORInputs

Measurements

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)IS IT LIKE A BIPED ROBOT?

ROBOT CONTROL

SEGMENTDYNAMICS/KINEMATICS

MOTORS

SENSORS

CONTROLLER

DisturbancesDesired Task

Commands

FES CONTROLCNS PROCESSOR

BRAIN

SPINAL

VISUALVESTIBULAR

NATURALSENSORS UPPER LIMB SEGMENT

DYNAMICS/KINEMATICS

MUSCLES

NATURALSENSORS

LOWER LIMB SEGMENTDYNAMICS/KINEMATICS

MUSCLES

ARTIFICIALSENSORS

SPINAL CIRCUITS

CONTROLLER

DisturbancesDesired Task

?

?

Disturbances

Spinal Lesion

Commands

Cognitive feedback

SERVOMOTORS AS ACTUATORS

Linear, time-invariant

Torque

Current

Torque

Speed

MUSCLES AS ACTUATORS

High power/weight, but nonlinear, time-varying and uni-directional

Time

FFF

Activation Velocity

Force = f(neural input, length, velocity, time, ...)

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?

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

CONTROLInputs

Measurements

STIMULATOR

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

T

CEKSE

BP

KP

Active (AE)

Passive (PE)

u

Fu

x,v

3 inputs (u,x,v), 1 output, modified Hill-type model

“Muscle” = activity from single stim channelJoint-space model --> no knowledge of anatomy needed

ISOMETRIC MUSCLE

Staticnonlinearity

Lineardynamic system

Hammerstein model

stim force

Identify LDS with impluse response

Identify SL by deconvolution

MODELING MUSCLE

Force

Fu

x,vX

PE Force-Velocity

CE Force-Velocity

Fscale

IRC

CE Force-Length

Activation Dynamics (2nd order)

PE Force-Length

u

V

X

V

X

Passive Element

Active Element

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

CEKSE

XCEXSE

XMT

ISOLATED, ANIMAL MODEL MUSCLE

0

5

10

15

20

25

30

35

0 4 8 12 16

Fo

rce

(N

)

Time (s)

(Durfee and Palmer, IEEE Trans. Biomed. Eng., 41(3):205-216, 1994)

Experiment

Model

INTACT, HUMAN MUSCLE

(Abushanab: Ph.D. Thesis, MIT, 1995)

EXPT VS. MODEL

ExperimentSimulation

Hip

flexio

n (

deg)

Knee fl

exio

n (

deg)

Time (sec) Time (sec)

0 2 4 6 8 0 2 4 6 820

30

40

0

20

40

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

PROPOSED SOLUTION:

Stimulation plus "smart" orthotics

Requires precise, stable control for repeatable steps

Muscles are nonlinear, time-varying

(1)

Need to walk for reasonable distances

Muscles fatigue rapidly

(2)

BRACE (CBO) + FES

• Stimulated Muscles = Power • Brace = Trajectory guidance • Brake = Control, stability

CBO OVERVIEW, SPECIFICATIONS

Designed for RESEARCH use

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

(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

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Without CBO With CBO

Gait Speed

0.09

0.12

Sp

eed

(m

/s)

0

10

20

30

40

50

60

Without CBO With CBO

Gait Distance

25

50

Dis

tan

ce (

m)

BETTER REPEATABILITY

0

20

40

60

80

100

120

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

20

40

60

80

100

120

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Time (sec)

With CBO

Time (sec)

Without CBO

Kn

ee a

ng

le (

deg

)

Kn

ee a

ng

le (

deg

)

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 !!??