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Postural control and Dynamics Presentation
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Transcript of Postural control and Dynamics Presentation
![Page 1: Postural control and Dynamics Presentation](https://reader034.fdocuments.in/reader034/viewer/2022042714/557aafd9d8b42a6f378b4f64/html5/thumbnails/1.jpg)
Developing and Evaluating New Methods for Assessing Postural Control and Dynamics
Industrial and Systems Engineering
Virginia Tech
Hongbo Zhang
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Background
• Falls are common and costly– Over 2.3 million older adults suffered nonfatal fall injuries and
662,000 hospitalized in 2010 (CDC, 2012) – The total direct medical costs associated with falls greater than
$19 Billion in 2000 (CDC, 2010)• Multiple factors contribute to falls
– Human physical and mental conditions, work complexity, and environmental factors
• Multi-factorial interventions for fall prevention – Physical strength training – Body flexibility, joint coordination training (e.g. Tai Chi) – Postural controller interventions (e.g. mechanical vibrations)
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Existing Methods
• Joint coordination assessment – Frequency-domain coherence analysis (Creath et al., 2005,
Zhang et al., 2007, Saffer et al. 2008)– Uncontrolled manifold (Krishnamoorthy et al., 2005, Hsu et al.,
2012)
• Postural control modeling – Continuous feedback controllers (Peterka, 2000, Mergner et al.,
2003, Peterka and Loughlin, 2004, Qu and Nussbaum, 2007, Kiemel et al., 2008)
• Ankle stiffness assessment – Passive and active ankle stiffness (Kearney et al., 1997, Loram
and Lakie, 2002a, Galiana et al., 2005,Casadio et al., 2005, Roy et al., 2011)
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Proposed Methods
• Study 1: Joint coordination assessment – Wavelet (time-frequency domain) coherence analysis
of two-joint coordination – Uncontrolled manifold analysis of whole body
coordination for exploring different control goals
• Study 2: Postural controller modeling – Intermittent sliding mode controller
• Study 3: Ankle stiffness assessment – A new method to calculate passive and active ankle
stiffness
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Data Source
• 32 participants (age and gender balanced)
• Localized muscle fatigue (LMF) conducted in muscles at one ankle
• Participants stood as still as possible on a force platform for 3 trials before LMF and 11 trials post-fatigue, each trial lasts 75s with rest interval 1 min
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Study 1
Effects of localized muscle fatigue and aging on two-joint and whole-body coordination
during upright stance
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Overview• Two-joint coordination
– Ankle-hip coordination, <1 Hz in-phase, >1 Hz anti-phase (Creath, 2005, Zhang et al., 2007)
– Head-trunk coordination, head angular acceleration depending on trunk positions (Keshner, 2003, St-Onge, 2011)
• Whole body coordination– Arm, trunk, knee, and ankle all involved in upright
stance pointing task (Tagliabue, 2009)– COM was treated as the hypothetical coordination
control goal (Hsu, 2012)
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• Study objectives– Evaluate two-joint and whole body coordination– Identify control variables involved in whole body coordination– Assess effects of LMF and aging on body coordination
• Study hypotheses– Ankle-knee, ankle-trunk, ankle-head, and whole body
coordination exist during quiet upright stance– Body coordination influenced by aging and ankle LMF– COM, head, and shoulder can all be possible whole body
coordination control goals
Objectives and Hypotheses
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Methods
3
4
5
2
7
6
1 Foot Angle
Ankle Angle
Knee Angle
Trunk Angle
Head Angle
Upper Arm Angle
Lower Arm Angle
3
4
5
2
7
6
1 Foot Angle
Ankle Angle
Knee Angle
Trunk Angle
Head Angle
Upper Arm Angle
Lower Arm Angle
Sagittal Plane Frontal Plane
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Methods
• Wavelet coherence– Step 1: Perform continuous wavelet transform of
ankle, knee, trunk, and head angle to obtain the wavelets coefficients (Wa, Wk, Wt, Wh) between 2.5 – 4Hz
– Step 2: Calculate cross wavelet transform (CW) of the wavelets (W)
– Step 3: Calculate cross wavelet power (CWP) – Step 4: Calculate wavelet coherence =
s(CWP)/s(WPJ1) s(WPJ2), s: smooth operator, J1, J2 =>{ ankle, knee, trunk, head)}
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Methods: Time Interval Ratio
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Methods: Phase Ratio
Phase Ratio = In-phase/Anti-phase
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Methods
• Uncontrolled manifold (UCM)– Step 1: Determine relevant task variables (COM,
shoulder, and head positions) and joints involved in whole body coordination
– Step 2: Calculate Jacobian matrix, which is the first order derivate of task variables over joint angles
– Step 3: Obtain the basis of null space of the Jacobian matrix
– Step 4: Obtain parallel component of uncontrolled manifold with the projection of joint angle variance on the null space
– Step 5: Obtain perpendicular component by subtracting parallel component from joint angle changes
– Step 6: Obtain uncontrolled manifold ratio equal to parallel component / perpendicular component
Joint Angle Variance
Basis of Null space of the Jacobian matrix
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Statistical Analysis• Dependent variables
– Wavelet coherence: phase ratio and time-interval ratio for ankle-knee (AK), ankle-trunk (AT), and ankle head (AH) angles in the sagittal and frontal planes
– UCM: head, shoulder, and COM uncontrolled manifold estimated separately in the AP and ML directions
• Two-way ANOVAs (age, gender) for each dependent variable
• Two-way ANCOVAs (age, gender) on change scores (post-fatigue – pre-fatigue) for each dependent variable, the pre-fatigue variable as a covariate
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Results
– AK time-interval ratio SP larger among older vs. young adults 1.05(0.15) and 0.96(0.10) sec
– AT time-interval ratio FP larger among older vs. young adults 1.32(0.14) and1.21(0.11) sec
– AT phase ratio FP larger among females vs. males 1.67(0.69) and 1.21(0.41)
– AH phase ratio FP larger among females vs. males 1.09(0.27) and 0.84(0.24)
• Wavelet coherence: pre-fatigue
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Results• UCM: pre-fatigue
– Shoulder UCM AP larger among young vs. older adults 1.15(0.09) and 1.08(0.09)
– Shoulder UCM ML larger among females vs. males 1.13(0.09) and 1.03(0.14)
– COM UCM ML smaller among females vs. males 0.634(0.001) and 0.635(0.0004)
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Results
Wavelet Coherence: Post-Fatigue
Age
Tim
e (
sec)
0.0
0.5
1.0
1.5
Young OldPre-LMF Post-LMF Pre-LMF Post-LMF
Young Older
Age Group
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Results
• UCM: post-fatigue– COM UCM ML increased, pre-fatigue:
0.633(0.0009), post-fatigue: 0.634(0.0008)– COM UCM AP decreased, pre-fatigue:
0.634(0.0009), post-fatigue: 0.633(0.0009)– Shoulder UCM ML increased, pre-fatigue:
1.07(0.15), post-fatigue: 1.10(0.10)
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Discussion
• Two-joint coordination appears Intermittent
• Older adults displayed a larger ankle-knee time-interval ratio in the sagittal plane and a larger ankle-trunk time-interval ratio in the frontal plane
• Females had a larger ankle-trunk phase ratio in the frontal plane and a larger ankle-head phase ratio in the frontal plane
• One joint coordination corresponds to 2 – 3 muscle bursts (Loram and Lakie 2002b)
• Older adults postural control compromised (Qu et al., 2009, Davidson et al., 2011, Nishihori et al., 2011)
• Females tended to display more erect (landing) postures (Decker et al., 2003)
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Discussion• Post-fatigue COM UCM increased in the ML direction and
decreased in the AP direction– Directional effects of fatigue
• Post-fatigue time-interval ratio decreased among older adults and increased for young adults – Older adults associated with increase in fatigue-resistant Type I muscles and the
alerted muscular metabolic anaerobic pathways (Chan et al., 2000, Kent-Braun et al., 2002)
• Shoulder and head UCM values >1 in both the AP and ML directions – COM UCM in disagreement with previous results (Hsu et al., 2007, Zhang et al.,
2007)
Increased time-interval ratio ->
reduced coordination
Increased UCM ->Improved coordination
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Study 2
Development of an Intermittent Control Model for Evaluating Aging and Muscle Fatigue Effects on Human Upright Stance
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Overview• Most of previous research involved using
continuous control modeling (Peterka, 2002, Kuo, 2005, Van Der Kooij & De Vlugt, 2007, Kiemel et al., 2008)
• Both open-loop and closed-loop control needed (Collins and Luca, 1993, Collins et al., 1996)– Only feedback control not sufficient to maintain
upright stance stability (Fitzpatrick et al., 1996, van der Kooij et al., 2001)
– Calf muscles intermittently adjusted 2 -3 times per unidirectional sway (Loram et al. 2005, 2009)
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• Study Objectives– Apply sliding mode control to model quiet
upright stance – Identify effects of aging and LMF on the
intermittent postural controller• Study Hypothesis
– Upright stance maintained intermittently
Objectives and Hypothesis
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Methods
T+ T-Ankle torque (T) determined by switching function (S) required to meet:Sliding Action
Chattering
Sliding surface
Chattering minimized by sgn function or others functions
Sliding surface S=0
Lyapunov stability condition
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• Sliding mode intermittent control– Determine body dynamics– Construct switching function
• Angle and angular velocity errors• Able to meet Lyapunov stability
condition
– Solve estimated ankle torque (EAT)
– Decompose EAT into passive and active ankle torque
Methods
x
y
Th
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Statistical Analysis• Dependent variables
– COM angle, angular velocity, and angular acceleration
– Total ankle torque tracking errors– Modeled and experimental ankle torque correlation– Passive and active ankle torques– Passive/active ankle torque ratio
• Two-way ANOVAs (age, gender) for each dependent variable
• Two-way ANCOVAs (age, gender) on change scores (post-fatigue – pre-fatigue) for each dependent variable, the pre-fatigue measure as a covariate
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Results: Representative Trial Sliding surface (top-left), first order derivative of sliding surface (top-right), and phase plot of the sliding surface (bottom)
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Results: Representative Trial
Modeled and experimental ankle torques
0 10 20 30 40 50 605
10
15
20
25
30
35
40
Ank
le T
orqu
e (N
.m)
Time (sec)
Experimental
Modeled
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Results: Representative Trial Passive ankle torque and COM angle
0 10 20 30 40 50 600
20
40
0 10 20 30 40 50 600
2
4
Pa
ssiv
e A
nkl
e T
orq
ue
(N.m
)
CO
M A
ng
le (
deg
ree
)
Passive Ankle Torque
COM Angle
Time (sec)
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Results: Representative Trial Active ankle torque and COM angular acceleration
0 10 20 30 40 50 60-5
0
5
0 10 20 30 40 50 60-5
0
5
Act
ive
Ank
le T
orqu
e (N
.m)
CO
M A
ngul
ar A
ccel
erat
ion
(deg
ree/
sec^
2)
Active Ankle Torque
COM Angular Acceleration
Time (sec)
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Statistical Results: Pre-Fatigue
• Passive ankle torque larger among young females, followed by (in order) older females, older males, and young males
• Active ankle torque larger in the older group and among males
• Passive/active ankle torque ratio larger in the young group and among females
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Statistical Results: Post-Fatigue
• Slightly decreased tracking performance for all measures
• Decreased passive ankle torque contribution to total ankle torque
• Increased active ankle torque contribution to total ankle torque
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Discussion
• Acceptable magnitude of tracking errors – COM angle [0.45, 0.7] degree and COM
angular velocity [0.33, 0.53] degree/s • Angle and angular velocity tracking errors about 13
- 25% and 5 – 10% of experimental values– Mean ankle torque tracking error in the range
of 1.45 - 4.48 Nm, overall of 26 - 42 Nm (5 – 10%)
– The tracking performance comparable and slightly smaller than Phasic – Bang Bang controller (Bottaro et al. 2008)
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Discussion
• Passive ankle torque accounts for 97% of the entire ankle torque – Active ankle torque accounts for 3% of the entire
ankle torque • These estimates similar but higher than previous
estimates – Passive vs. entire (91 ± 23%) (Loram and Lakie,
2002ª– Passive vs. entire (64 ± 7.8%) (Casadio et al., 2005)
• The estimated differences likely attributed to no mechanical or sensory perturbations involved in our experiment
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Discussion
• Older adults displayed greater active ankle torque compared to young adults– Possibly to compensate for the compromised stability
due to aging (Shumway-Cook and Woollacott, 2000, Speers et al., 2002, Qu et al., 2009)
• Males had larger active ankle torques than females– A possible indicator of gender related differences in
fall risks (Hunter, 2009)
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Discussion • Larger increase of post-fatigue active ankle torque
among young adults – Possibly due to aging related muscle fiber structure
and metabolic pathway differences (Chan et al., 2000, Ditor and Hicks, 2000, Baudry et al., 2007)
• Smaller post-fatigue active ankle torque changes identified among females – Possibly due to greater oxidative metabolism
capacity, less likelihood to experience central fatigue among females (Hunter, 2004, Paillard, 2012)
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Study 3
A New Method to Assess Passive and Active Ankle Stiffness during Quiet Upright Stance
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Overview• Passive and active ankle torque measurement
– Used very small mechanical perturbations for measuring passive and active ankle torques (Loram and Lakie, 2002ª, Casadio et al., 2005)
• Effects of aging and ankle LMF on ankle torque – Fatigue induced changes in force capacity (Enoka
and Stuart, 1992)– Aging associated increase in passive joint stiffness
(Silder et al., 2008)
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• Study objectives– Quantify passive and active ankle stiffness among
quiet upright stance– Assess effects of aging and LMF on passive and
active ankle stiffness
• Study hypotheses– Upright stance controlled intermittently – LMF and aging alters passive and (or) active ankle
stiffness
Objectives and Hypotheses
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Methods
Top-down approach to calculate modeled ankle torque
Experimental ankle torque
Ankle
Fy
Z
COPap
Te = Fz * COPap + Fy * Ha – Mfoot*g*CMfoot-ap
Fz
CMfoot-ap
HaMfoot
Human Body
Ankle
Hip
Neck
ankle
trunk
head
Tm
Top - Down Approach
(A) (B)
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Methods
• Determine passive and active ankle torques based on followings
Study 2 showed that active ankle torque is in-phase coherent with ankle angular acceleration
Upright stance controlled through intermittent muscle contractions of 2 – 3 times per second (Loram and Lakie, 2002ab, Loram et al., 2005b,Loram et al., 2011)
0 10 20 30 40 50 60-4
-2
0
2
4
0 10 20 30 40 50 60-4
-2
0
2
4
Ta
(N.m
)
Aa-
ac (
degr
ee/s
ec^2
)
Ta
Aa-ac
Time (sec)
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Methods
• Determine passive and active ankle torques– Step 1: Identify passive +
active (P+A) zones using local maxima of absolute values of Aa-ac time series
– Step 2: Calculate the size (duration) of each P+A zone
– Step 3: Locate P zones, which are simply the time windows adjacent to P+A zones
0 0.5 1 1.5 2 2.5-1
-0.5
0
0.5
1
1.5
a
Aa
-ac (d
eg
ree
/se
c^2
)
Time (sec)
P + A Zone
P Zone
Local Maximum of Absolute Value of Aa-ac
Step 1
Step 2 Step 3
200 ms
200 – 400 ms
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Methods
• Calculate passive and active ankle stiffness, damping – Perform linear regression between the passive ankle
torque and ankle angle and angular velocity – Perform linear regression between active ankle torque
and ankle angle, ankle angular velocity, ankle angular acceleration, and trunk angle
– The selection of independent variables in the linear regression models determined through an iterative explorative approach
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Statistical Analysis
• Dependent variables– Passive ankle torque, stiffness, and damping of the
ankle, – Active ankle torque, stiffness, damping, and moment
inertia of the leg• Two-way ANOVAs (age, gender) for each
dependent variable• Two-way ANCOVAs (age, gender) on change
scores (post-fatigue – pre-fatigue) for each dependent variable, the pre-fatigue variable as a covariate
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Results: Representative Trial
• Modeled and experimental ankle torques
0 10 20 30 40 50 60-25
-20
-15
-10
-5
0
5
Time (sec)
An
kle
Tor
que
(N.m
)
Experimental
Modeled
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Results: Representative Trial • Passive and passive + active zones on ankle angular
acceleration and ankle torque
0 5 10 15 20 25-4
-2
0
2
4
Time(Second)
An
kle
A-A
C(D
egr
ee/
s2)
0 5 10 15 20 25-30
-20
-10
0
10
Time(Second)
An
kle
Tor
que
(N.m
)
Time (sec)
Ank
le T
orqu
e (N
m)
Ank
le A
-AC
(d
egre
e/se
c^2)
Time (sec)Time Interval:
545ms
Passive + Active (P+A)
Passive (P)
Local Maxima An Assistant Curve to Mark the Identified Local Maximum
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Results: Representative Trial
• Relationships between ankle angle and passive ankle torque (left), and ankle angular acceleration and active ankle torque (right)
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Results: Representative Trial
• Experimental and predicted passive (left) and active (right) ankle torques
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Statistical Results: Pre-Fatigue• Passive ankle stiffness and damping both larger
among older adults and among males • Active ankle stiffness (ankle contribution) larger
among older adults. • Higher values of active ankle torque, stiffness
(both ankle and trunk contributions), damping, and leg inertia among males
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Statistical Results: Post-Fatigue
Young
Older
Male
Female
0.81(0.31)
Active Ankle Torque (Nm)
1.33(0.78)
1.34(0.66)
0.82(0.53)
Pre Fatigue Post Fatigue Post - Pre Post - Pre
1.03(0.56)
1.28(0.67)
1.46(0.61)
0.88(0.49)
0.23(0.36)
-0.052(0.18)
0.11(0.44)
0.06(0.11)
Male
Female
Male
Female
0.39 (0.44)
0.053 (0.12)
-0.17 (0.17)
0.068 (0.095)
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Discussion• No external mechanical or sensory perturbations
required for calculating passive and active ankle torques
• 540 - 550 ms identified as the active control time interval– 383±55 ms muscle contraction time interval
demonstrated by prior studies (Loram and Lakie, 2002b, Lakie et al., 2003, Loram et al., 2005a, Loram et al., 2011).
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Discussion• Passive ankle torque account for 97% of the entire ankle
torque comparable to prior studies (Loram et al. 2005) • An evident linear relationship between ankle angle and
passive ankle torque consistent with the results from Winter et al. (2001)
• An evident linear relationship between active ankle torque and ankle angular acceleration – new finding
• Trunk angle involved in regulating active ankle torque – Trunk movement involved in contributing to the regulation of
active ankle torque – Evidence of ankle-trunk interaction/coordination
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Discussion• Greater passive ankle stiffness and damping,
and greater active ankle torque and stiffness among older adults – Possible contributors to older adults increased fall
risks (Hortobágyi and DeVita, 1999,Gajdosik et al., 2004)
• Larger passive ankle stiffness and damping, active ankle torque, stiffness, damping, and leg inertia among males – Consistent with prior studies (Vandervoort et al.,
1992a, Granata et al., 2002, Gajdosik et al., 2006)
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Discussion• Overall post-fatigue passive ankle torque
decreased– Suggesting compromised performance related to
passive ankle viscoelastic tissues (Kuitunen et al., 2002)
• A smaller fatigue induced increase in active ankle torque evident among older adults– Different muscle fibers and altered anaerobic
metabolic pathways between two age groups (Chan et al., 2000, Ditor and Hicks, 2000, Baudry et al., 2007, Kent-Braun, 2009)
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• General conclusions – Two joint coordination exists and is executed
intermittently; head and shoulder also possible whole body coordination control goals
– Intermittent controller able to track upright stance kinematics and kinetics
– The new passive and active ankle stiffness and damping method able to give comparable results
Overall Research Summary
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Overall Research Summary
• Insights for fall prevention– Older adults suffer reduced joint coordination
and increased ankle stiffness– Females display smaller ankle stiffness and
ankle torque– Young male adults tend to suffer more
adverse effects from muscle fatigue
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Future Research
• Investigate muscle contraction patterns under different postures– Especially interested in discovering intermittent
muscular control patterns
• Build and validate more complete postural models
• Gain more insights on postural control and fall prevention
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Thank You All !!