Influence of Audio Biofeedback on Structural

Properties of Postural Sway

L. Chiari1, M. Dozza1,2, A. Cappello1, F.B. Horak2

OHSU1Dipartimento di Elettronica, Informatica e Sistemistica

Alma Mater Studiorum - Università di Bologna, Italia2Neurological Sciences Institute

OHSU, Beaverton (OR), USA

What is Audio Biofeedback (ABF)?

(van der Kooij, 2000)

BALANCE

SENSES

MUSCLESBRAIN

Sensory Integration

InternalMap

• Balance is the consequence of appropriate muscle activations processed by the brain fusion of sensory information

BALANCE

MUSCLESBRAIN

Sensory Integration

InternalMap

• Visual, Vestibular and Somatosensory information are the major cues used by the brain to perform balance

VISION

VESTIBULAR

SOMATOS.

AUDITORY

• ABF may be used to involve more largely in the “game” the AUDITORY channel

Diapason: a recent solution for ABF

(Chiari et al., IEEE Trans Biomed Eng, submitted)

Sensor characteristics

• The sensor used is able to provide the complete linear & angular kinematics of the trunk (3 accelerometers, 3 gyroscopes)

• ABF in its present release uses only 2-D acceleration (AP and ML directions)

(Giansanti et al., Proc. ISPG, Maastricht, 2001)

Accelerometricsensors

Amplifier andlow-pass filter

SENSOR BOX

TRANSMISSIONBOX

Release 1 - 2002

Diapason: the sonification procedure

Safety Region (SR)

• represents the limit of stability

• is the region in which the COM projection is inside the subject’s support base

• the support base is processed on anthropometric parameters (feet length and width)

Reference Region (RR)

• represents the region for natural sway (±1 degree)

• is processed using the subject’s height

ML acceleration ML acceleration

Volume Balance

Volume Frequency

AP accelerationAP acceleration

A B

C D

SRRR

SRRR

Example of ABF signals

• ABF can provide similar information as one otolith:– If the trunk/head moves slowly, primarily

gravitational information is provided– If the trunk/head moves quickly, primarily

acceleration information is provided

• Continuous ABF sound also provides trunk VELOCITY information (most critical)

Remarks

• Subjects learn how to use Diapason in 1 minute

• Subjective balance score (Schieppati et al., JNNP 1999) is lower also when ABF seems NOT actually helpful

• It is small, light and comfortable to wear

Release 2 - 2003

Results: quiet standing

• Improve balance (Sway Area decreases)• Increase control (Mean Velocity increases)

ABF can restore standing stability in patients

NO ABF WITH ABF

This subject can NOT stand on the foam with eyes closed.

This subject can stand on the foam with eyes closed using ABF.

0 50 [mm]

CO

NTR

OL

VEST

IBU

LAR

Eyes Closed Eyes Open and foam Eyes Closed and foam

AB

F ON

AB

F OFF

AB

F OFF

AB

F ON

NO ABF

ABF

NO ABF

ABF

Which is the origin of the changes observed in body sway

trajectories?

Cognitive

Sensory

Tuning-fork

??Open-Loop

Feedback

Feed-forward

Some insights on the structural properties of body sway can be

provided by Stabilogram Diffusion

Analysis (Collins & De Luca, 1993)

Stochastic analysis: fractional Brownian motion (fBm) modeling through the

Variance Analysis Method

We model the output of the human postural control system as a system of (1-D and 2-D) bounded, correlated random walks.

This is done by investigating the memory of the system through an analysis of the increments in displacement (x, y, r)

Vx(t) = <x2> - <x>2 t2Hx

Vy(t) = <y2> - <y>2 t2Hy

Vr(t) = <r2> - <r>2 t2Hr

C = 2 (22Hj-1 - 1)

For fBm the following correlation function holds (Feder, 1988):

Computed from the experimental data

Estimated by LS techniques

0.05 0.310

-1

100

101

HjS > 0.5j = x, y, r

C > 0 (persistence)

0.5 110

0

101

102

HjL < 0.5j = x, y, r

C < 0 (anti-persistence)

Hence, COP fluctuations have a structure that is dependent upon the timescale of observation and not simply random (fractality).

Moreover, AT LEAST TWO scaling laws are needed to accurately model the phenomenon in the range of interest (0.01- 10 s).

- Scaling functions that describe how the values change with the resolution tells more about the data than the value of the measurement at any one resolution (in particular at the higher resolution as it is commonly done by the summary statistic scores, working with the original sampled time series).

- Two modes of postural control take place over different timescales, associated with persistent and anti-persistent motion of the COP

Collins & De Luca, 1993

HOW MANY SCALING REGIMES ?This mechanism of transition from persistent to anti-persistent behavior is a common property of many biological systems. How to model this ?

We choose the easiest answer: correlation is assumed to change continuously

10-3

10-2

10-1

100

101

102

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

H

c

tKtV

tttH

2)(

)]/1(2log[2log)(

Chiari et al., Hum Mov Sci, 2000

H

t

-Parameter K is the variance of the displacements for t=1 s, which is also proportional to the variance of the displacements for large time-lags (V(t→4K as t→∞). Since V(tc)=K tc, K can be thought of as an estimate of the actual diffusion coefficient of the random process which is encountered by sampling the time series r at a sampling frequency 1/tc.

-In fact, parameter tc is the midpoint of the sigmoid and represents the time-lag in which H = 0.5, corresponding to a purely random behavior. In this sense it is an estimate of the time-lag at which the real process switches from a persistent (positively correlated) to an antipersistent (negatively correlated) behavior.

K & tc do correlate with several pathological conditions Central pathologies - Parkinson (Rocchi et al., 2000) - Multiple sclerosis (Chiari et al., in preparation)Peripheral pathologies - Peripheral Neuropathy (Lenzi et al., 1999) - Vestibular Loss (Kluzik et al., 2001)

K & tc allow to identify different postural strategies in control subjects - Post-adaptation to an incline (Chiari et al., 2001;) - Postural blindness (Chiari et al., 2000)

Do structural properties of the postural sway change with ABF?

If so, in which way this may help in the understanding of the

mechanisms underlying ABF efficacy and improving the design

of a rehabilitation strategy for balance disorders?

100.0

266.7

433.3

600.0

1 2

ABF_on_off

K

* **

0.1

0.2

0.3

0.5

1 2

ABF_on_off

delta

_Tc

*p<0.05**p<0.01

ResultsWe present the results obtained from 9 healthy subjects in the condition with the least sensory cues (i.e. eyes closed on foam) that benefited the most from ABF

Both K and tc show a systematic reduction due to ABF

Structural properties do change during biofeedback trials

Conclusions• ABF is comfortable and well accepted by the subjects• Subjects increase postural control using ABF (area

decreases, mean velocity increases)• ABF may help people manage more easily inadequate

surface somatosensory and visual information for postural control

• ABF determines structural changes in the COP that may reflect a larger role for feedback (conscious?) control over feed-forward control of posture.

• Future studies are needed to determine whether, with more practicing, subjects can use ABF without conscious control and hence how much this result is consistent over time.

Thank you for your attention

Luigi Galvani, Guglielmo Marconi and Augusto Righi, Bononiensi

Work in Progress

• Development of a portable wireless prosthesis for balance improvement

• Use in clinical rehabilitation for subjects with balance deficits

• Validation of ABF during dynamic tasks

Open question: Can use of ABF become more automatic with

practice?

• We have shown that practicing with ABF increases subject’s balance performance

• Vestibular loss subjects have difficulties using ABF when they are already controlling balance using a voluntary strategy i.e. concentrating specifically on the other senses (Divided Attention problem). Can use of ABF become more automatic (less voluntary)?