AMC Sem 2 Flashcards
(211 cards)
1
Q
Describe the double pendulum chaos theory
A
The dbl pendulum has high sensitivity to initial conditions
Low speed start - get stable inphase or anti phase
High speed start - behaves chaotically in an unstable state
2
Q
What is a fractal
A
Infinitely complex pattern that is self similar across different scales
3
Q
Describe dimensions of a fractal
A
Dimension is not equal to the space it resides in.
Eg Koch snowflake - length measured depends on the size on the measuring stick
4
Q
Types of self similarity in fractals
A
Spatial self similarity- shape is repeated at arbitrarily smaller and smaller scales
Temporal self similarity- shape is repeated over time course eg graph has same pattern if over 3 min, over 30 min or over 300 min
5
Q
Describe physiological fractal example
A
Lungs
Follow simple rule of go certain distance then divide in 2
Causes surface area to be much bigger than if a traditional geometric structure was followed
More efficient gas exchange
6
Q
Impact of fatigue and age on self similarity
A
Likely to go from self similarity to brownian noise
7
Q
Types of noise + their predictability
A
White noise - completely unpredictable
1/f noise (pink noise) - some predictability
Brownian noise - more predictable only small variations can occur at any time point
8
Q
What is standard deviation
A
Measures how far individual data points are dispersed from the mean of that data set
Can measure magnitude of variation but takes no account of data order
Can’t identify self similar behaviour
9
Q
What is coefficient of variation
A
Ratio of the standard deviation to the mean
Higher coefficient of variation = higher variation
Can measure magnitude of variation but takes no account of data order
Can’t identify self similar behaviours
10
Q
What is entropy
A
Measure of level of uncertainty or disorder in a given data set
Higher entropy = more uncertainty
It increases as freedom of choice increases
Helps quantify signal regularity
11
Q
Entropy values
A
0 = completely predictable
2 = white noise
12
Q
What is detrended fluctuation analysis
A
Analyses statistical properties of time series data
Can detect self similarity
Separate data into boxes, make best fit of each box, calculate deviation of each box. Repeat with smaller and smaller boxes
13
Q
What is plotted on detrended fluctuation analysis graph
A
Log of root mean square error vs Log of corresponding box size
14
Q
Detrended fluctuation analysis alpha exponent values
A
0.5 = white noise
1 = pink noise
1.5 = brownian noise
15
Q
Heart rate complexity analysis results
A
Compared young and old
Both had resting HR 65 but ApEn young 1.09 old 0.48
Young - more unpredictable- good as it means it responds better to environment + stressors
16
Q
Why do we fluctuate
A
Interactions of lots of different signals
Motor unit recruitment
Motor unit firing
Muscle tendon interactions
17
Q
Entropy in older and younger females strength based task
A
Lower SampEn and ApEn in older - decreased complexity
Strength training made no difference
18
Q
Why get loss of complexity with aging
A
Denervation renervation process leads to larger, slower motor units
Older people have 20-40% fewer muscle fibres
19
Q
Define fatigue
A
Process that can lead to exhaustion
Neuromuscular fatigue = loss in the capacity for delivering force + or velocity of a muscle resulting from muscle activity under load. This is reversible by rest
20
Q
Define critical power
A
Maximum rate a muscle can keep up for a long period of time without fatigue
21
Q
What happens when exercising above critical power threshold
A
Fatigue occurs, fixed energy reserve is used which determines exercise duration
22
Q
What happens when exercising at or below critical power
A
Task is fatigueless
Energy reserves are not used up
23
Q
What happens during sub maximal exercise (fatigue)
A
Compensation for fatigue is possible allowing task to be continued but at the expense of maximal force/power generation
24
Q
Describe loss of complexity with age hypothesis
A
The down regulation of systems or less good integration reduces complexity of processes/outputs
25
Isometric force production variation
If told to hold a set force typically remain in right area with some slight fluctuations
26
Describe task failure experiment
Complete intermittent contractions until task failure
Perform MVC every 1 min
The fall in the MVC is a measure of fatigue
27
Describe central fatigue
Exercise induced processes reducing force proximal to NMJ - Brain/CNS/PNS effected
28
Describe peripheral fatigue
Exercise induced processes reducing force at or distal to NMJ
- muscle fatigue
29
Describe a superimposed twitch
Apply stimulus during contraction
If maximally activated the twitch shouldn’t increase output
30
Describe potentiated resting twitch
Stimulus is applied at rest - no input from CNS
Gives idea of muscle capacity
Peripheral fatigue results in reduced resting twitch
31
How to measure central fatigue
Voluntary activation = (1-a/b x 100)
a = superimposed twitch
b = resting twitch
32
How to assess central and peripheral fatigue
Use muscle stimulator
Can be per cutaneous or femoral nerve (better but less comfortable)
33
Effect of central fatigue on EMG
EMG is reduced
Submaximal EMG is increased to compensate for peripheral fatigue
34
Neuromuscular fatigue and critical torque
If above critical torque get progressive neuromuscular fatigue
35
Describe experiment re neuromuscular fatigue + critical torque
2 bouts exercise below torque + 2 bouts above torque
Below showed some progressive fatigue but able to continue for whole hour
Above - v significant fatigue, task failure within 15-20 min, had to use MVC to achieve desired force by the end
36
What is critical torque
Key fatigue threshold for peripheral fatigue
37
Does fatigue induced loss of complexity occur below the critical torque
No, metabolic rate cannot be stabilised above the CT therefore progressive reductions in torque complexity should only occur above CT
38
What is complexity driven by
Peripheral body eg muscles as no loss of complexity occurs below CT
39
Experiment to confirm complexity is driven by peripherals
1. Exercise to task failure
2. Group 1 allowed 3 min recovery, group 2 use cuff to occlude + prevent recovery
When no recovery occurs complexity remains low but complexity increases during recovery
40
Effect of caffeine on fatigue
Ingest either 6mg/kg caffeine or placebo
Caffeine prevented fall in neuromuscular complexity but no change in fatigue level
Suggests complexity plays a small but significant role in complexity
41
Define balance
Active control of physical shape of limbs to provide varying degrees of passive stability + muscular actions to provide compensatory active stability for passive insufficiencies
42
Define stability
Tendency for body to remain in or return to its initial position following application of force. Can be passive or dynamic
43
Why do we have postural sway
Impossible for body to remain completely still
- passive instability
- muscle errors
-sensory errors
-feedback delays
-control strategies
44
What happens in stable equilibrium
Likely to return to stable state following small perturbations
45
What happens in unstable equilibrium
Small perturbation cause centre of gravity to move more easily
46
4factors passive stability depends on
Weight - more mass = harder to accelerate/ be knocked
Area of base - more area = more stable
Horizontal distance of centre of gravity to pivot point
Height of centre of gravity above base - higher = less stable as the more of CoG moves for each 1 degree of movement
47
Why do humans have passive instability
Small base of support
High CoG above base
48
Describe dynamic stability in humans
Have passive instability so need active muscle contractions to maintain stability
Use muscles that cross joints to maintain or regain balance
CoG must remain in base of support
49
Describe muscle errors
Muscles cannot produce perfectly constant force due to variation/error or over/underwhelming force
Muscles act across multiple joints and in multiple planes/axis - need to use synergists or other muscles to control/stabilise other body parts
50
What proportion of sensory information does each part provide
Vision 10%
Vestibular apparatus 20%
Somatosensory proprioception (Golgi tendon organ/ muscle spindle etc) 70%
51
Why do we get sensory errors
Different inputs may cause sensory conflict (what makes you motion sick)
Require some movement to work
52
Describe sensory threshold
How much movement is needed for sensory system to say you have moved
Really slow movement can’t be detected
Really fast movement detected all the time
Proprioception has the lowest threshold
Vestibule highest threshold need to move quite quick, quite a lot to detect movement
53
Describe feedback delays
Input - delay- processing- delay output - delay - feedback
54
What is sensory delay
Time taken to detect movement
Varies based on movement- larger movement = smaller delay
55
Describe neurological delay
65-130ms
Afferent signal transmission - 50ms
Descion time - varies
Efferent signal transmission- 50ms
56
Describe electromechanical delay
13-55ms
Time taken from muscle activation til force is produced
57
List 5 control strategies
Ankle strategy
Hip strategy
Mixed strategy
Arm swing
Stepping
58
Describe ankle strategy
Sway about the ankle
Controls CoM via ankle torque
Most commonly used in quiet stance
Fixed hip angle
Bad on narrow surface, good with low friction
59
Describe hip strategy
Use when need to respond quickly
Uses more energy but requires less effort
Controls CoM by horizontal force
Hip angle is opposite to ankle angle
Good on narrow surface, bad with low friction
60
Describe mixed strategy
Uses hip and ankle together
Often done in practice as allows head to remain up so can still see
61
When are arm swing and stepping used
Arm swing - when can’t step eg in gymnastics
Stepping- to prevent falling
62
What is a control strategy tolerance reigon
Along where the CoG is in the same position in relation to the ground
63
Benefits of staying within control strategy tolerance reigon
Mechanically efficient
Easier to control
Uses less energy
64
Describe the control model
Expansion of information processing model from engineering
Involves model with assumptions- simplification of true system
Any variation = unwanted error
Add random error to try to simulate humans
65
Describe proportional (PID controller)
Present state of system (position)
Quick to correct but leads to overshoot
66
Describe integral (PID controller)
Past state of system (average over time)
Corrects for drift but is slow
67
Describe derivative (PID controller)
Future state of system (current velocity)
Prevents overshooting and is similar t dampening
68
Describe an example of PID controller
Peterka 2002 used numerous sensory perturbations to determine weights for sensory input - vision 10%, vestibular 20%, proprioception 70%
69
PID problems
Simulation output = too good - need to add error or would be perfectly still
Relies on excessive noise to reproduce typical postural sway
Struggles with latrge delays
Can use intermittent control models
70
Describe isolating 1 part of a non linear system
It changes the way the whole system evolves, and changes how components in the system are used
So may need to use an alternative method to assess the system in its entirety
71
Balance alternative approaches important bits
Variability is a fundamental part of the system not just unwanted noise
Movement is integral to perception
Sway magnitude is less important
Pattern of sway is more important
72
What is information entropy
Loss of information due to reduced order
Lower entropy = less loss of information ( easier to predict future)
73
Describe signals and information entropy
Periodic signal = low entropy
Complex signal = med - high entropy
Random signal = high entropy
74
What is the lyapunov exponent
Measure of local stability of a system
Low stability leads to exponential divergence in signal trajectories
75
Signals and lyapunov exponent
Periodic signals - high stability, zero divergence of trajectories
Complex signals - some instability, trajectories diverge as time progresses
76
What is used in non linear signal analysis
Entropy and Lyapunov exponent
77
Describe Harbourne + stergiou 2003 postural control in infants study
As child progresses from stage 1 (sitting with support) to stage 3 (independent sitting).
Lyapunov exponent decreases as become locally stable
Approximate entropy initially decreased and then increased slightly as baby began to explore
78
Describe Bardy et al 2002, 2007 experiment re control strategy and task frequency
Examined postural responses to tracking a moving target
Target frequency increased or decreased gradually
79
What is Newells constraints approach
Have task constraints, organism constraints and environmental constraints
Movement is the product of interaction between these constraints
80
What is motor learning in newells constraints approach
An ongoing dynamic process driven by constraints
It involves-
Search of perceptual motor landscape
Stabilisation and refinement of functional movement patterns
Optimisation of control by exploiting environmental and task information
81
Bardy et al 2002, 2007 results
Strategy used depended on task frequency
Hip strategy - anti phase coordination
Ankle strategy - in phase coordination
Different transaction points showed hysteresis in strategy selection
Are reigons of bistability where either strategy is acceptable
82
Pupil function
Dilated and constricts to let more or less light through
83
Cornea function
Protective barrier from foreign bodies and UV radiation
Initial refraction
84
Lens function
Uses refraction and accommodation to focus light on retina
85
Retina function
Cones - bright light , coloured central vision
Rods - dim light, peripheral vision
86
Optic nerve function
Transmits sensory info for vision to the brain in the form of electrical impulses
87
Describe binocular vision
Use both eyes together, the difference in the angle of light hitting each eye gives important proprioception information
88
Describe nasal + temporal
Nasal = nose side
Temporal = lateral side
Nasal fibres cross over at optic chiasm so info is on the same side
89
Name types of eye movement
Fixations
Saccades
90
Describe fixations
Central visual field (within 3 degrees)
100ms+ duration
Conscious processing
91
Describe saccades
Rapid eye movements
Between fixations
Information is suppressed.
Beneficial to work out where something will be + use 1 saccadic to move eyes there than to try + track it using multiple saccades
92
Describe focal vision
Aka ventral
Used for identification (what?)
Central visual field
Conscious- takes more time but gives more info
93
Describe ambient vision
Aka dorsal
Optical flow (Where something is)
Central and peripheral visual fields
Non-conscious - quicker
94
Describe pathways of vision
Optic nerve to occipital lobe
Dorsal = occipital lobe to parietal lobe to frontal lobe
Ventral = occipital lobe to temporal lobe to frontal lobe
Both frontal lobe (response planned) to pre-motor + motor cortex (sequenced and specific movement organised)
95
Describe optical flow
Closer objects appear bigger and take up more space on retina - size of something in visual field gives idea of how far away it is
96
Time to contact equation
Time to contact (Tau) = size of image/rate of expansion
97
How do we use vision in interceptive tasks
Use image direction on retina
Eg if both sides of a ball are on your left it will be on your left
If one side of ball is on either side, it will be hitting you.
The less the speed difference between the 2 sides = the wider it will pass
98
Calculation to intercept
Tau dot
Need to couple running speed with rate of change of tau
Stop just short - 0.5
99
Interception accuracy
Typically slower = more accurate
BUT
Timing tasks have a reversal of speed accuracy trade off.
Easier to intercept at higher speeds as is easier to time
100
Describe cricket batting cue experiment
Compared high skilled and low skilled players
Occluded sight of ball at various points
Pre-bounce occlusion results similar to no occlusion control results
Pre-release occlusion results dropped to virtually 0 for low skilled but only 50% for high skilled.
Suggests high skilled players use pre-release cues
101
Describe cricket ball tracking experiment
Elite players tracked ball first 100-200ms, saccade to bounce, then tracked onto bat - allowed longer viewing before and after bounce
Low skilled tracked ball first 100-200ms but we’re unable to accurately predict bounce so struggled tracking ball to bat
102
Describe differences when batting v bowler/machine
Vs bowler - things that occur earlier in movement are greater
Vs machine -things that occur later in movement eg wrist flick are greater as don’t get visual cues from machine
103
What is a control strategy
Activation patterns that minimise or maximise a task relevant cost function
104
Give 5 examples of cost functions
Minimise effort
Minimise muscle activations
Minimise jerk
Maximise performance outcome
Maximise likelihood of success
Can also be a combination with different weightings
105
What is jerk
Rate of change of acceleration
106
What is rate of change of acceleration proportional to
Rate of change of force
107
Define skill
Ability to bring about an end result with maximum certainty and minimum outlay of energy
108
Typical research method for cost functions
RSOS
Record performance (experimental)
Simulate performance (theoretical)
Optimise technique for various criteria
Select solution that best matches recorded one
109
What are simulation models based on
Newton’s equations of motion
Input-model-output
110
How are inverse dynamics used in simulation models
Give the model a movement (the output)
Work out what is needed to create that movement
111
Define constraints
Can be organisational, environmental or task that inhibit/ cause a certain movement
They are critically evaluated using a dynamical systems theory framework to recommend future direction and best practice
112
What is dynamical systems theory (Newell, 1986)
Task, environment and individual constraints lead to a persons perception of information and subsequent action. This contributes to physical performance
113
Example individual constraints
Stature
Mass
Segmental inertia properties
Range of motion of joints
114
Example task constraints
Velocity
Duration
Balance
Secondary objectives
Bilateral symmetry
115
Example environmental constraints
Gravity
Ground interaction
Interactions with equipment
116
What is local optimum
Finding the best solution within the same solution space, vary technique slightly within this area to find it.
Humans good at this
117
Global optimum
Explore other techniques that may be completely different to find the optimal way to complete a task
Humans bad at this
118
Walking optimum example
Ren 2007
Multiple solutions found for given constraints- stiff knee, inadequate knee extension, excess ankle plantar flexion, minimum energy outlay.
Minium energy outlay found to most closely resemble human gait
119
Why is minimum outlay of energy chosen when multiple solutions are possible
Possibly due to sensory information relating to amount of energy consumed
120
Describe gait transition
As speed increases we transition between methods eg walk - jog - run
As try to use gait with lowest O2 consumption for that speed + at some point a slow jog is more efficient that a fast walk.
121
What is the most efficient speed to walk at
Speed with lowest O2 consumption
122
Trigger for change in gait
Energy- where less energy is used for slow jog than fast walk.
Tends to correspond well with self selected speed
123
Cross country skiiing gait transition example
Herzog, 2015
Switch from a 1 skate technique to a 2 skate technique as speed increases based on energy efficiency
124
Under somersault on P bars technique
Hiling and Yendon 2012
Taught to do using open circle technique but elites often switch to stoop stadler technique
125
Under somersault on P bars simulation
Input - joint angle time history to vary the joint angles it moves through
Output = momentum
If optimise to minimise joint torque looks v similar to open circle technique (likely most efficient)
But if optimise to minimise horizontal velocity at release looks v similar to stoop stalder- more margin for error allowing for further skill development
Shows minimising effort is not always the most important cost function
126
Gymnastics upstart
Yamasaki 2004
Hard to simulate on model
Tried optimising for jerk, effort and torque change
But had to use via point
127
What is a via point
In a simulation model, putting in a midpoint that the model has to go through and then optimising the first half and the second half
128
How did Haley and Yendon simulate the upstart
1000 simulations adding noise based on recorded variability
Optimise to Maximise success
Had much lower root mean square error for shoulders and hips than optimising joint torque or torque change
So likely to move in that way at it copes with variability the best so maximises success
129
What can replicate muscle characteristics
Minimising jerk or torque change
130
What is a P-value
Probability of the observed outcome and all more extreme values if the null hypothesis is true
Eg null hypothesis = 0 which is true but you get 0.7 what is the probability of getting 0.7 or higher
131
What does a p value give the probability of
The data, not of the null hypothesis
132
What is Bayesian statistics
Making inferences based on uncertain data
133
What is Bayesian desicion theory
Aiming to select the optimal action based on inferences
134
Describe the process of Bayesian inference
Prior - have some prior knowledge to make a prediction based off
Data/Liklihood - get some evidence and update knowledge as data becomes available
Posterior - change prior predictions based on data, reducing uncertainty in our knowledge
135
Bayesian statistics paper
Wolpert, 2007
136
Bayesian desicion making process
Select action based on current beliefs to minimise loss
Calculate expected loss for a given action, which is the loss averaged across the possible states weighted by the degree of belief in a state
137
Define loss function
Quantifies the value of each possible outcome
138
Shooting at target Bayesian decision theory exampl
If scores are evenly distributed and your error is evenly distributed- aim for centre
If scores evenly distributed but your more likely to miss above - aim slightly lower than centre
139
Tennis Bayesian decision example
If no prior knowledge may guess ball would land in centre
Get data suggesting opponent likes to hit it to the far left
Aim to get to middle left to account for this
140
Where do you get noise
In command
Movement
Sensory info
141
What is signal dependent noise
The larger the force the larger the noise so bigger commands have more noise and therefore more error
142
How to get less noise in a movement
Do a movement with lower levels of activation over a longer period of time rather than a shorter movement but with large activation
143
Consequences of movements
How you move can dictate likelihood of an action
Eg trying to catch a ball if go up along the ball’s trajectory will still catch it even if mistime
But if go across ball’s trajectory’s will only catch if you time it right
144
Why did bipedalism arise
To allow foraging in the savannah and reaching food up high
To appear taller and intimidate predators
To fulfil locomotor needs of scavengers
Aquatic adaption due to prolonged flooding forcing ancestors out of forest
145
Adaptations associated with bipedalism
Lumbar curve in vertebral column
Opposing toe
Foramun magnum
146
Describe basic stepping pattern
Have stance phase and swing phase
Footstrike, opposite toe lifts, reversal of fore and after shear, opposite footstrike, toe lifts, tibia vertical, footstrike
147
Periods in basic stepping
Initial dbl limb support
Single limb stance
2nd dbl limb support
Initial swing
Mid swing
Terminal swing
148
Describe animal model prep for locomotor studies
Either transection of spinal cord or transection of brain stem
149
Describe rhythmic activity in cats
Rhythmic activity for walking is generated by networks of neurons in spinal cord
(Dorsal roots have been cut in transection)
150
Conclusions due to cat rhythmic activity findings
Supraspinal structures not necessary for producing basic motor patterns of stepping
Basic rhythmicity is produced by neuronal units contained entirely in spinal cord
Spinal circuits can be activated by tonic descending signals from the brain
Spinal pattern generating networks don’t require sensory input but are strongly regulated by input from limb propriocepters (eg if step on something sharp change gait)
151
What are flexor reflex Afferent
System of neurones in sc
152
Describe half centre hypothesis
Stimulation of flexor reflex Afferents produce short lasting bouts of alternating flexor/extensor activity
153
Stepwise process of half centre hypothesis
1.contralateral flexor reflex afferents fire
2. Activates extensor neurones which produce a positive impulse on extensor motor neurones causing it to fire
3. Also causes an excitatory synapse onto an inhibitory neurone causing inhibition of opposite side
4. Extensor motor neurone runs out of neurotransmitter and stops firing, therefore excitatory input stops and opposite side no longer inhibited
5. Flexor motor neurone activated and whole process repeats on opposite side
154
What does half centre hypothesis enable
Can switch between flexor and extensor firing without a break
155
How did half centre hypothesis evolve into central pattern generator hypothesis
Experiments recorded rhythm in in tact animal
Made animal decerebrate, by isolating sc
Isolated sc activity measured - showed same patterns as intact animal
156
Describe central pattern generator hypothesis
Brainstem inputs start the whole thing
Sensory inputs from each side work together to create flexor extensor pattern
157
Does central pattern generator exist in humans?
Big debate with some evidence on both sides
158
Yang 1998 central pattern generator experiment
Held 6 month old infant (unable to walk) over treadmill
Recorded stepping patterns - these seemed to be alternating
159
Describe Dimitrijevic 1998 central pattern generator experiment
Used SC patients with complete transection of sc
Was able to somewhat record alternating patterns in legs which would indicate a cpg as no brain input
But don’t know if transection is actually complete as was caused by accidents and even a tiny bit of descending input could account for this
160
Describe descending pathways
Necessary for initiation and adaptive control of walking
Come from the mesencephalic locomotor region and the medial reticular formation
161
What does the mesencephalic locomotor region do
Responsible for staring locomotion stopping locomotion and speeding things up
162
List supraspinal functions
Activate CPG - to initiate walking
Control speed
Refine motor pattern in response to Afferent feedback
Guide limb movement in response to visual stimuli
163
What is refining movement in response to Afferent feedback
Eg if step on something sharp you change gait, but how gait changes depends on where in gait cycle you are and where on foot sharp bit is
164
EEG - EMG. Walking coherence
Provides evidence for motor cortex control of tibialis anteroir
Walk on treadmill EEG and EMG recorded
High correlation between tibialais anterior activity and brain activity
Less so for other muscles
165
Describe Transcranial magnetic stimulation
Put electromagnetic coil over head (fasten in place and ensure doesn’t move whilst walking on treadmill)
Stimulate and activate motor cortex
Direct signal is sent through sc to tibialis anterior causing a motor evoked potential
166
What is short latency intercortical inhibition
Uses a low intensity conducting stimulus to suppress motor evoked potential
If see a change in this the brain must be involved
More inhibition was seen in walking than when stationary so brain is more involved in walking than stamding
167
What is short latency intercortical inhibition
Uses a low intensity conducting stimulus to suppress motor evoked potential
If see a change in this the brain must be involved
More inhibition was seen in walking than when stationary so brain is more involved in walking than standing
168
Why is tibialis anterior so important
It controls toe clearance in the swing phase which is critical for bipedal walking
Humans are subconsciously very good at toe clearance, clearing obstacles by less than 2cm
169
Gait key messages
Gait control is distributed across spinal, brainstem and cortical levels
Spinal CPGs generate a basic locomotor rhythm
Brain activates and modulates basic cpg pattern
Brainstem and cortex initiate and adapt gait to task demands
In humans cortical control probably more important than CPG
170
3 conclusions for complexity in isometric force production experiment
Complexity is lower the closer you are to max effort
Older adults are less complex at every effort level
Complexity is not restored through strength training
171
How is the scaling component (alpha) calculated
By computing the root mean square error for the detrended time series over various box sizes
172
What does scaling behaviour give info on
Presence or not of long term correlations
Can also give indication of power in the frequency spectrum but this is time scale specific
173
What are power law correlations
Values between 0.5 and1 in detrended fluctuation analysis
174
What is perceived fatigabilty
Factors you think determine how long you can exercise but are changeable
Eg homeostasis - blood glucose, core temp, hydration, oxygenation
Eg psychological state - arousal, executive function, mood, pain, motivation
175
What is performance fatiguabilty
Aka neuromuscular fatigue
Determined by
Contractile function - Ca kinetics, blood flow, metabolism
And Muscle activation - Afferent feedback, motor neurons, activation patterns, neuromuscular propagation
176
How to calcite peripheral fatigue
It how much the resting twitch drops following exercise
177
Describe experiment for complexity of torque fluctuations during maximal and submaximal fatiguing contractions
1. Max contractions for 5 min, duty cycle of 6s on 4s off. Regularly stimulate muscle
2. Submaximal contractions at 40% MVC til task failure, MVC and femoral nerve stimulation every min.
Complexity and noise quantified by ApEn, SampEn and DFA analysis with each 6s contraction
178
Results for complexity of torque fluctuations
1st min ApEn = 0.99
DFA = 1.10
Task failure - Ap En = 0.3
DFA = 1.43
179
What do fluctuations in torque correlate with
Motor unit output - makes sense as motor unit firing causes twitches which cause fluctuations
180
Describe experiment for mechanisms of torque complexity loss
Intermittent ramp contractions of the i
Tibialis anterior with blood flow occluded performed to failure using high density surface EMG
Dorsiflexion torque output measured at ankle
ApEn And DFA applied to both signals
181
What does a cumulative spike train do
Gives a measure of the ensemble activity pool, which can be correlated with force fluctuations
182
Problems with using dorsiflexors
MCt often 50% MVCor higher
If use more than 30% MVC on EMG lots of noise.
Had to cuff dorsiflexors in 1 condition to prevent blood flow to put it above CT
183
Contractions with open circulation results
No change in torque complexity
No change in cumulative spike train complexity
No task failure
184
Contractions with closed circulation results.
Torque complexity (ApEn) declined
Cumulative spike train declined
Task failure occurred in 5-6 min
185
Torque complexity loss conclusions
Loss of complexity is caused by changes in ensemble motor unit behaviour
186
Define variability and complexity
Variability - magnitude of fluctuations
Complexity- pattern of fluctuations
187
Effect of caffeine on fatigue
Prevent fall in complexity
Extend time to task failure
No change in peripheral fatigue
Prevented fall in voluntary activation- shows small but significant contribution of central fatigue to complexity
188
What is a motor evoked potential
Electrical signal recorded from muscles following stimulation of the motor cortex
Assesses integrity and function of motor pathways
Measured using transcranial magnetic stimulation
189
Describe uncontrolled manifold hypotheses
CNS Doesn’t eliminate redundant degrees of freedom but uses abundance to enhance performance
Variation of elements not crucial to performance allowed to increase (vUCM)
Variation in elements crucial to performance is reduced (vORTH)
190
Hsu 2007 UCM experiment
Analysed joint configuration variance on the stability of centre of mass
Examined contributions of each major joint on whole body com
Compared vision and no vision conditions
Modelled body with different degrees of freedom
191
Variations in HSU 2007 experiment
Single inverted pendulum - low variability UCM high variability ORTH
dbl inverted pendulum- less variation orth, more variability UCM
Multi joint coordination - most variation UCM least ORTH
Stiff joint- low variation in both
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HSU 2007 results
Most major joints coordinated to stabilise posture
Only small portion of joint variabilityafects whole body com or head variability
If control was pure ankle strategy this wouldn’t happen
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3 axis of modified perceptual framework
Targeted perceptual function
Stimulus correspondence
Response correspondence
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Describe targeted perceptual function
Whether a task is high order or low order
This depends on how much decision making is involved.
Little desicion making eg snellen chart test= low order
Having to make decisions based on visual info = high order
High order better
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Describe stimulus correspondence
How much does the stimulus corresponds to actual thing you want to improve
Bad to good
Generic (alpha-numeric)
Behavioural correspondence (behave in realistic manner but don’t look like what it should)
Visual and behavioural correspondence (looks and behaves like player eg video analysis)
Sport specific (doing training in performances environment)
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Describe response correspondence
Generic or sport-specific
If training one part of sport in isolation it’s not as good as doing the whole thing together
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Define advanced cue utilisation
Ability to make accurate predictions based on contextual information available early in the action sequence
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What is a temporal occlusion
Occlusion of vision timing varies
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What is spatial occlusion
Varying what in the visual field in occluded, eg prevent keeper looking at pen takers non-dominant leg or head
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Ecological validity of occlusions
Is it realistic in the environment
Or does missing contextual info impact
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Badminton occlusion results
Throughout all occlusion time points experts performed better
As occlusion gets later error decreases
Little difference between expert and novice at 1st occlusion.but big difference at 2nd occlusion therefore must be something experts pick up on between these time points that helps predict
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Penalties occlusion results
Experienced players had better predictions accuracy than inexperienced
Performance improves as more visual info available for both groups
Biggest difference between groups occurs at earliest occlusion(-120ms) and virtually no difference at occlusion at impact
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Penalties height vs direction
Before impact players get info re direction but error for height remains.
Only much later are players able to distinguish height
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Penalties visual fixations
Experts made much longer duration fixations but at less locations
Therefore suggesting they know most important places to look at focus on them
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Where do novices v experts fixate
Novice- progressively more on trunk arms and hips
Expert - early = head then kicking leg, non kicking leg and ball
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Define disguise
Hiding what your going to do
Keeps opponent in suspense and maintains outcome ambiguity
Maintains chance level 50/50
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Define deception
Performed to deliberately mislead opponents to trigger an incorrect motor response.
Reduce chance level if successful 0%
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Deception and expertise
Experts are better at predicting deceptive actions and are not as affected by deception
Less susceptible to deception
Better able to detect when have been deceived
Less biased towards perceiving actions as genuine
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Rugby deception response accuracy
Experts have better response accuracy
Accuracy in deceptive actions is lower for both skill levels
In deceptive actions both skilllevels accuracy decreases as occlusion gets later and then at certain point are able to realise and correct
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Rugby gaze results
Both groups looked at legs then torso as opponent approached
Lower-skilled more time viewing head
Higher skilled more time viewing hips
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Rugby tackle force plate simulation
Had to make decision early enough to make “tackle”
Experts able to detect and respond to change and deception earlier
