1 Feedback gain scaling quantifies postural abnormality of Patients with Parkinson’s disease...

Feedback gain scaling quantifies pos-tural abnormality of Patients with

Parkinson’s disease

Seyoung Kim, Fay B. Horak, Patricia Carlson-Kuhta and Sukyung Park, “Postural Feed-back Scaling Deficits in Parkinson’s disease”, Journal of Neurophysiology, Vol.102: 2910-2920, 2009

Human Balance Research

Quantification of postural balance

Seyoung Kim, PhD

[email protected]

Model based balance & gait analysis

• 1/3 of the elderly has a fall every year [www.mw.go.kr, 2008].

• The medical expenses for the aged people have been steadily increased [www.nhic.or.kr,

2005].

Research background

[ http://www.kerals.com ]

• Scientific research into postural balance is re-quired to provide solutions for fall prevention.

CoP

[ Termoz et al., Gait & posture (2008) ]

RMS amplitude ofSide by side / 45°• Elderly: 0.48 / 0.41*• PD: 0.45 / 0.34CoP does not explain the abnormality of elderly or

patients.

Outcome measure is not enough to represent pos-tural balance.

e.g. Parkinson patients

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Systematic analysis with feedback con-trol model

[ Park et al. 2004 ]

Can this model be a good measurement for postural balance ?

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• Objective : – We examined whether the “feedback gain and its scal-

ing” may explain the deteriorated control adjustability of Parkinson patients.

• Hypothesis :– The deteriorated control adjustability of PD patients

might be reflected in feedback gain scaling.

Research objective

@ Neurological Sciences Institute

Perturbation

Feedback

gain

K

Ankle Hip strategy

NormalPD

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Experimental procedure

@ Neurological Sciences Institute

• Subjects– Seven healthy elderly

(63±7y)– Seven age-matched pa-

tients with PD (UPDRS: 23.8±10.2)

• Protocols– Backward perturbation

• (3-15cm in 275ms) X 5set

Subject

AgeGende

r

Height

(cm)

Weight

(kg)

Duration

of PD(yrs)

UPDRSTotal

Dyskinesia Score

Side most

affected

H&Y Score

ABC*

Sub01 53 M 178 71 9 13 0 R 2 93

Sub02 66 M 188 90 3 33 0 R 2 91

Sub03 65 F 163 81 5 24.5 0 R 2 96

Sub04 81 M 180 90 11 39 0 R 3 95

Sub05 67 M 185 89 1 19.5 0 R 2 96

Sub06 56 M 180 89 8 11 1 L 1.5 99

Sub07 65 M 185 77 N/A 26.5 0 R 2 83* Activities-specific Balance Confidence scale

• Measurement– Joint angle captured by Motion capture system (Santa

Rosa, California) 200 Hz sampling rate 5th Butterworth low-pass filter with cutoff frequency

of 10 Hz– Moment & Ground reaction forces measured by a cus-

tom force plate 400 Hz sampling rate 5th Butterworth low-pass filter with cutoff frequency

of 30 Hz

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• 2segment inverted pendulum model in sagittal plane

Linearized

• Joint torques were calculated by inverse dynamics [ Kuo,1998 ].

• Full-state feedback control model that represent CNS control

• Gain parameters calculated by optimization

Biomechanical model for human pos-tural control

xa)(PT),(V)(G)(M

uuxQxKJ TT )(

0)}(Re{ BKAeig

),( refxxKT Thipankhipankx ][

8

K

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Calculation of feedback gains by model simulation

[ Exp. data and Simulation ]

2exp

2simexp2

x

)xx(1R

Elderly : avg. 0.84±0.038PD : avg. 0.80±0.036

9

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• Postural response to support translation• Postural feedback gain and its scaling

Results and Discussion

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Postural response to support transla-tion

Nor-mal

Patient

@ Neurological Sciences Institute [ S. Kim et al., Journal of Neurophysiology (2009) ]

CoP does not explain the abnormality of elderly or patients.

Can feedback gain diagnose the abnormality of pos-tural balance ?

[email protected]


Postural feedback gain scaling of el-derly and PD

[ S. Kim et al., Journal of Neurophysiology (2009) ]

[email protected]


• Postural adjustments in responses to increased perturbation magnitudes were quantified by the scaling of the feedback control gain.

• The PD patients showed significantly different gain and gain scaling behavior from the healthy elderly. – The PD subjects showed much smaller ankle gain with

low ankle gain scaling and a larger hip gain with slightly greater hip gain scaling.

– Subjects with PD have significantly larger hip feedback gains than age-matched control subjects, leading to stiffer hip joints so that overall postural sway resembles an inverted pendulum with significantly smaller hip joint motion.

Conclusion

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Model limitations

• Current model does not exclude the possibility of the nervous system’s selection of preprogrammed re-sponses.

• The violation of constraint followed by the initiation of step response was not explicitly modeled with current model.– Subjects were instructed to recover their upright posture with-

out violating the flat-feet constraints. However, subjects would rather step when they encounter unexpected perturbation in real situation.

• The current model misses various nonlinear, temporal aspects of postural physiology. – Dynamics of muscle mechanics– Short-latency responses from reflexes– Long-latencies from long-loop feedback

16

Different postural response to support translation

between the young and the elderly

Seyoung Kim, Fay B. Horak, Patricia Carlson-Kuhta and Sukyung Park, “Postural Feed-back Scaling Deficits in Parkinson’s disease”, Journal of Neurophysiology, Vol.102: 2910-2920, 2009

Human Balance Research

Quantification of postural balance

Seyoung Kim, PhD

[email protected]


Peak joint kinematics and kinetics


[email protected]


Feedback gain scaling of young and el-derly


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Parameter study : Peak joint angle as a function of body inertia and feed-back gain

Avg. upper body massYoung : 39.84±7.70 kgElderly : 63.42±15.84 kg

20[ S. Kim et al., Journal of Neurophysiology (2009) ]

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• The differences in the measurements of joint mo-tion and torques between the young and elderly groups may be attributed to altered system pa-rameters such as feedback gains and body mass distributions and do not necessarily indicate changes in postural strategy.

• Smaller maximum allowable ankle joint torque in the elderly may be due to the tendency of initial forward leaning at their preferred upright posture.

Conclusion

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• Funds– Postural control study was supported by a Basic Research Fund

of the Korea Institute of Machinery and Materials, the second stage of the Brain Korea 21 Project, and a National Institute on Aging.

– Walking research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Tech-nology (#2010-0013306) and the Unmanned Technology Re-search Center (UTRC) at the Korea Advanced Institute of Sci-ence and Technology (KAIST), originally funded by DAPA, ADD.

• Collaborators– Fay B. Horak (Oregon Health & Science University)– Patricia Carlson-Kuhta (Oregon Health & Science University)– Chris G. Atkeson (Carnegie Mellon University)

Acknowledgement

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Special thanks to…

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1 Feedback gain scaling quantifies postural abnormality of Patients with Parkinson’s disease...

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