Gait Analysis Flashcards
What can gait analysis be used for
- To provide a quantitative assessment of function or mobility (Frailty and fall risk in older adults
- Support treatment options (Surgical options for adults with OA, orthoses or surgery in cerebral palsy)
- Examine disease state or progression (Parkinson’s disease, Huntington’s disease. MS, OA)
What time points in the gait cycle is a step
heel strike to opposite foot heel strike
What time points denote a stride
heel strike to same foot heel strike
- made up of swing and stance phases
Stance Subphases
- Loading Response: initial contact to opposite toe off (double support)
- Mid-stance: Opposite toe off to heel raise (single support)
- Terminal Stance: Heel raise to opposite contact (single support)
- Pre-swing: Opposite initial contact to toe off (double support)
Swing Subphases
- Initial swing: Toe off to feet adjacent
- Mid-swing: Feet adjacent to tibia vertical
- Terminal Swing: Tibia vertical to initial contact
Common temporal parameters
- Step and stride time
- Stance time and swing time
- single support time
- double support time
Common spatial parameters
- Stride/step length
- base width
- foot angle
Ground reaction forces
Force exerted by the ground on the body
- small force away from movement in heel strike
- Large force away from movement in loading
- decrease in force and angled up in midstance due to off loading of center of mass (falling with style)
- large force in direction of movement during push off
- small force in direction of movement during toe off
Joint angle kinematics
- The movement patterns without considering forces
- Sensitive to changes with age, clinical conditions and injuries
- Studied using marker based-methods in the past but new technology make it easier to monitor without markers
Why can joint angle kinematics be complicated
- Occur in 3 dimensions
- Ankle, knee and hip all influence each other
- often focus is on fewer joints/plans
General gait findings with aging
- decreased gait speed
- decreased spatial parameters
- increased temporal parameters
- increased variability
- Healthy older adults may have little to no change
- Larger changes can occur with advanced age, addition of clinical conditions, reduced executive function
Where should we measure gait
In lab vs out of lab
- trade-off between more controlled and more realistic
- out of lab tends to have a wider spread and slow stride times
Normal vs perturbed
- Optimal gait vs stressed system
During functional tests
- time up and go, 6 min walk test, self-paced walk test
How do we measure gait with sensors
Temporal parameters
- requires timing of heel strike
- Finding these events in the data
Spatial parameters
- requires integration of acceleration to displacement
Joint angles
- Sensor on each segment or “rigid body”
- Requires integration of angular velocity to angular displacement
How do we get displacement
- Numerical integration from acceleration to velocity to displacement
- Have to set gravity as 0 point to get accurate data
Challenges with calculating displacement
- Any offset in data will be greatly amplified (low frequency)
- Error in signal will accumulate (high frequency)
- Unknown initial conditions (only able to determine changes from initial state)
Important considerations when integrating to find displacement
- Detrending (removing mean) or a high-pass filter is quick but limited
- Works ok with limited sensor rotation
- Better technique is required on lower limbs or placements with rotations
Process of integration to find displacement
ACCELERATION
- remove high-frequency noise
- remove offset/gravity
- numerical integration
VELOCITY
- remove offset (detrend or high-pass filter)
- Numerical integration
DISPLACEMENT
Sagittal Knee Joint Angle
- At heel strike, the knee is typically flexed (slightly), and continues to flex (absorbs load) as knee extensors work eccentrically
- Knee then extends (knee extensors working concentrically) as body moves forward over stance limb
- Knee flexes as toe off approaches and plantarflexion occurs/heel begins to lift
- Flexion continues to mid swing peak
- Knee begins to extend in preparation for heel strike again
What can cause change in knee flexion during gait
- Pain, muscle function, flexibility
- Aging, injuries, osteoarthritis
Common knee joint angle abnormalities
- Stiff knee gait
- Flexure contracture
Stiff knee gait
- Reduced knee flexion at heel strike, midstance, and/or swing
- Common in osteoarthritis - reduced range of motion, bending is painful, quadriceps avoidance strategy
- Knee arthroplasty to improve pain and function
Flexion Contracture
- Inability to fully straighten knee
- Can occur with osteoarthritis or other conditions, congenital deformities, rheumatoid arthritis, cerebral palsy
- Knee flexion angle maintained during swing phase but extension reduced causing straighter line to occur based on how severe the condition is
Cerebral Palsy
- Results from damage to one or more areas of the developing brain
- Can occur pre- or post-natally
- Numerous causes (e.g. premature birth, hypozia)
- Various difficulties with gait
3 main postural and gait differences for cerebral palsy and their causes
- Anterior pelvic tilt
- Equinus (restricted dorsiflexion)
- Reduced knee flexion
CAUSE
- Plantar flexor spasticity results in equinus
- which causes the reduced knee flexion at heel strike
- which leads to lead to excessive anterior pelvic tilt to progress forward
Treatment for altered gait with cerebral palsy
Ankle-foot orthosis
- Equinus is prevented/limited
- Secondary anterior pelvic tilt and extended knee are resolved
How do we measure joint angles with IMUs
- Need to get orientation estimates from IMUs (Angular velocity to angular displacement)
- Compare orientations from segments on either side of the joint (angle of shank vs. angle of thigh)
Calculating angular displacement from IMU data
- Bias instabilities (low frequency offset changes)
- Angular random walk (stochastic noise)
- Unknown initial conditions (only able to determine changes form initial state)
STEPS
1. remove high-frequency noise
2. remove offset
3. Numerical integration to displacement
Sensor Fusion
Combining data from different types of sensors to obtain estimates of displacement and orientation that have less uncertainty
- Elephant parable
Using zero velocity update
- Foot is fixed to the ground during the stance phase
- can use this to anchor output signal
- Brings it back to zero to minimize drift
Physical Activity Assessment
Estimates metabolic equivalents from accelerometer “counts”
- Working metabolic rate in comparison to your resting metabolic rate
- count is a measure of the number of peaks over a sufficient threshold in a signal
Determines activity level based on “counts per minute”
Activity Classification
Using inertial signals to classify time spent in various activities
Can range in complexity from:
- Stationary vs. Dynamic (simply thresholds of inertial data)
- Separating all different types of activities (utilizes artificial intelligence)
