Posts Tagged Gait Analysis

[WEB] Gait and Balance Academy: How Do We Use Gait Analysis to Measure Walking Consistency?

By Arnaud Gouelle, PhD, and Patrick Roscher, MS

How do we use gait analysis?

Have you ever asked yourself this simple question: why do we measure and analyze gait? Overall, the answers will revolve around the same ideas: to gauge the functional status of a person; to follow-up the natural history of a disease; to determine immediate or long-term treatment requirement and effects. Now, if the question is what main information are you taking from a gait analysis, answers will surely vary throughout different clinical expertise (see “Of Gait Analyses and Elephants,” page 9). An orthopedic surgeon will be interested in deviations in joint kinematics and kinetics; a physiotherapist will look at a more generic level of the motor performance, considering the whole speed or the step length asymmetry; a geriatrician will be interested in quantifying the fall risk or the impact of a cognitive load on the locomotion; a podiatrist will investigate gait at a foot level through the distribution of the weight during the roll-on. Similarly, a person’s academic or professional backgrounds guide the perception that a person will have about the use and the interpretation of a clinical gait analysis.

On one hand, this diversity illustrates the recognized value and wealth of gait analysis. While walking seems to be a simple movement, it is in fact a particularly complex function, combining the musculoskeletal and nervous systems with a multifaceted relationship between the automated and voluntary parts of control. From the brain to the effectors, most disturbances in the physical or cognitive status can have an effect which becomes noticeable in gait features. Even tiny details such as chewing or being in a bad mood change the way you walk, if you know where to look!

On the other hand, these multiple ways to examine gait also highlight a critical fact: whatever the promises, neither a unique system nor a single parameter can address the globality of the gait. With today’s technology, there is no way to get a full picture and using any analysis in isolation creates the risk of assessing a patient from a single, incomplete perspective. For example, for individuals diagnosed with hamstring triceps spasticity and/or bones misalignment, treatments can contribute to changes in the joint motion making it closer to healthy references. However, what is the consequence on the dynamic stability for a person whose locomotion was built on these so-called defects, especially in the first months after surgery? In another example, gait speed is one of the most commonly used parameters and is even suggested as a sixth vital sign of health. However, as the product of step length and cadence, it is possible to produce the same speed by multiple configurations ranging from quick, small steps to slow, long steps. Walking with higher speed than 1 m/s (value often used as a reference) does not mean that the configuration between step length and cadence is optimal. If walking at this pace causes the patient to produce multiple small steps at a fast rate, they could be at higher risk for falls.

The motor control, or how a movement is produced and regulated, is an essential component of gait interpretation; unfortunately, it is often ignored. While it is true that healthy gait is a hallmark, normative references are obviously needed. However, walking with outcomes closer to those seen in control populations does not necessarily imply a better performance. It must be kept in mind that what a patient does can be related to the disease as well as being the product of coping adaptations, all according to physiological possibilities and limitations.

It must be kept in mind that what a patient does can be related to the disease as well as being the product of coping adaptations, all according to physiological possibilities and limitations.

Who’s In Control?

Different Approaches of Motor Control Lead to Different Interpretations of Spatiotemporal Parameters and Variability. In a classical view, the central nervous system (CNS) controls all movements of the body. Coordinated movement patterns, such as walking, require motor planning and constant feedback from the surroundings to regulate the movement by a retroactive control. Consequently, any disorder could affect the production and the regulation of the movement planned by the CNS. Seen under this perspective, increased difference from “normal” walking parameters (for example, a slow walking speed) is seen as a linearly worsening clinical status. Therefore, the invariance of the movement is interpreted as the natural order of the biological system and the variability (for example, variation in the step-to-step values for step length, stride width or step time) only seen as a reflection of a physiological inability to produce the consistent movement as prescribed by the CNS. Clinically, gait variability is often only interpreted as a “noise” which must be removed, disregarding its potential for regulation.

Another approach considers further the possibility for a self-organization of the movement, to respond to the constraints as much as possible. Outside periods when a direct cognitive intervention is required to take control of the movement (eg, to choose which direction to turn at next street corner), it is postulated that the walking pattern emerges spontaneously from constraints related either to the task (eg, walking under time pressure), the organism (eg, pathological limitations), and/or the environment (eg, walking within a crowd). This implies that the way a person walks and the variability represent much more than the result of physical inabilities. Clinical assessment of gait is standardly administered in straight, unobstructed walking pathway, at self-pace. In this situation, there is no reason to see excessive variability in the gait parameters if there is not an underlying issue. However, if gait variability underlines the existence of an issue, it also demonstrates that the person can regulate the perturbations to walk. Another person walking without variability could be at higher risk for falls than the first patient when faced with a more complex situation, as the low variability could be hiding an inability to adapt.

Overall, an asymptomatic system must demonstrate control that allows it to be both robust (preserve the homeostasis) and flexible (ability to vary in order to adapt to the constraints).

A method to look at organization and variability

In a recent pilot study, Gouelle et al1 built on these concepts to introduce a scoring methodology based on the walking speed and the relationships between step length and cadence. One method, named the Organization Score, is proposed for looking at the mean gait characteristics and to quantify how much a patient’s gait pattern deviates from healthy references. This distance is not seen ultimately as a bad thing, instead it is thought to reflect the biomechanical adaptation and, indirectly, the residual capacity of adaptation which could be mobilizable for the management of internal or external perturbations. Therefore, a second component, the Variability Score, is needed to quantify the level of variability. By applying this method to a cohort of patients with Friedreich ataxia who walked independently, with one cane, or with a rollator, the authors demonstrated that equal levels of organization do not imply a same level of variability and vice-versa. Overall, the Organization Scores demonstrated a longitudinal deterioration in the gait characteristics from independent ambulators to those who ambulated with a rollator. Variability Scores mostly reflected dynamic instability, which became greater as the requirement of an ambulation aid or the switch from a cane to a rollator was imminent. In order to consider both components and the requirement to use an assistive device, the authors finally introduce the Global Ambulation Score (GAS) as a way to summarize the whole performance as a single number. The GAS might be a valuable outcome measure for longitudinal disease progression as it showed statistical correlation with the clinical status assessed by a standard notation scale for gait ability in Friedreich ataxia.

Due to gait’s complexity, it is essential that appropriate analysis tools, protocols, and outcome variables are used, as there is no global test or factor to answer all questions surrounding gait function.

Gait analysis can be performed using numerous methods that vary depending on purpose for the patient and the background of the clinician or researcher administering the analysis. Due to gait’s complexity, it is essential that appropriate analysis tools, protocols, and outcome variables are used, as there is no global test or factor to answer all questions surrounding gait function. The most important process is to define the clinical question that you want to address. Always keep in mind that gait analysis is highly contextual, don’t be too quick to extrapolate because the “same” results can have different interpretations in different individuals/under different circumstances. Under standardized conditions in a gait laboratory, the variability mainly reflects disturbances. But, in real-world assessments, with wearable sensors for example, if one is navigating in a crowd, an appropriate ability to regulate gait is necessary for safety.

Arnaud Gouelle, PhD, is Director of Research at ProtoKinetics. A Gait Disorder Specialist, he previously served as head of the Gait & Motion Analysis Unit at a pediatric hospital in France. His publications focus mainly on stability and motor variability in functional movements.

Patrick Roscher, MS, is Chief Technical Support Engineer for ProtoKinetics. His background includes graduate education in biomedical engineering with a concentration in human biomechanics and working in the clinical gait laboratory at the former Rehabilitation Institute of Chicago.


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[WEB PAGE] Gait by Numbers

Posted by Debbie Overman     

Gait by Numbers
PHOTO CAPTION: Observational gait analysis has had a long history with rehabilitation because it is accessible, affordable, and can be performed in nearly any type of space. As gait assessment technologies become smaller and more affordable, however, the possibility of bringing objective measures of gait in-house expands for many clinics.

Technologies for treating post-stroke patients are becoming smaller while the functions they perform are growing larger. This is especially true for advances that are making measurement and assessment systems more portable and affordable, and have equipped them with powerful electronics that provide a data-driven picture of patient performance.

Gait Analysis

Devices that measure gait are where some of the most significant developments in stroke rehab technologies have occurred. For a very long time, gait measurement has been performed by therapists who use their powers of observation to assess an individual’s gait characteristics. This “observational gait analysis” is accessible and affordable and requires only a therapist’s time and space in the therapy gym. No specialized equipment or training is needed. While the method is expedient and inexpensive, it carries a number of potential pitfalls associated with human error including distraction and therapist bias. Today’s technologies can reduce or remove the potential for those errors.

Among the current technologies that provide a clear and quantifiable assessment of an individual’s gait are mats and walkways that are placed over floors and a variety of other walking surfaces. Patients ambulate on those surfaces while the embedded sensors record data that capture the geometry and relative arrangement of each footfall as a function of time and space. These temporal-spatial measures of gait and pressure enable therapists to objectively measure the effectiveness of interventions and make comparisons against baselines to detect decline or improvement.

Some of the data that gait mats and electronic walkways provide include gait phase, gait cycle, step and stride, velocity, distance, center of pressure (COP), and coefficient of variation. Therapists can use these data for analysis of activities such as forward and backward gait, transitional movements, timed up and go (TUG), jumping and hopping, 4-square step-test, static and dynamic balance.

Systems vary in how they may be assembled, but some versions of this technology feature snap-together design that allows for layouts that are straight or have turns, shaped in ovals, or cover an entire floor. They also can be used with steps and curbs to measure gait parameters in real-world settings.

The clinical value of these systems is summed by Margaret Wood, MSPT, physical therapist at University of Maryland Shore Regional Health, in a 2017 online video released by the university.

Wood explains that one of the key components of care physical therapists provide is to help some patients walk more safely and efficiently, and return a person recovering from a gait impairment to normal daily life. By measuring gait, she says, therapists can break down components of how a patient walks and help them improve the ability to walk.

“[This technology] is used to objectively measure gait or walking in time and space. As the patient walks across the walkway, the system with the sensors on the side captures the geometry and the timing of each and every one of [the patient’s] footfalls.”

She notes that the gait mat system she works with provides specific data related to a patient’s speed, step length, and, “what an individual’s walking actually looks like.”

The data these systems create can also be used to develop interventions, establish baseline function, measure performance pre- and post-intervention, and provide objective data that can be used to support decisions about providing a patient with services or devices.

Gait Analysis On the Go

The trend toward making equipment smaller is complemented by a parallel trend in making equipment more portable. Previous generations of gait mats provided sophisticated data but could take up considerable amounts of floor space, and once put into place were unlikely to be moved. Some of the newest models of gait mats and electronic walkways are designed to simply roll out onto a floor or other walking surface—including outdoor terrain—and begin collecting data in a matter of minutes. Other useful features among these types of technologies include concealed electronics and sloped edges that are useful when collecting data for individuals who use assistive devices such as canes and walkers.

Manufacturers have shrunk the footprint of these technologies as well while maintaining accuracy and performance. The result is technology that takes up less space and costs less than what previously has been available. It’s a welcome trend that should help objective gait analysis become a reality for clinics and facilities that once thought them too expensive or too cumbersome.

As these technologies become more affordable and accessible, clinics that want to bring this power in-house will want to research the functions each system offers. A wealth of reports and information about these technologies is available online and at manufacturer websites to help clinic managers and owners inform their purchases. Likewise, part of the pre-purchase homework should include in-person testing and conversations with current users.

Welcome to Wearables

Another area where miniaturization and portability are leaving their marks is wearable technologies. These small devices offer big performance, and the comfort consumers seem to have with them appears to be growing as devices such as fitness trackers surge in popularity.

Though not a wearable in the sense of small watch-like devices worn on the wrist, a pressure mapping system that fits inside a shoe offers a good example of a wearable technology that is small, powerful, and can be worn comfortably by the patient. The device is wireless, Bluetooth-enabled, and aims to provide unrestricted movement to the patient who wears a sensor attached to each shoe. The system is built to provide timing parameters that include cadence, step time, stride time, stance time, and swing time.

Exercise and therapeutic fitness activities typically will be important for keeping post-stroke patients healthy after discharge and throughout their rehabilitation period. However, individuals who have experienced a stroke tend to have very low levels of physical activity and are sedentary for up to 80% of their normal day.1 Residual neurological deficits can also influence the amount of physical activity in which post-stroke patients engage and ultimately reduce the amount of exercise they perform.2 Keeping post-stroke patients active can be helpful in flattening the risk of cardiac complication in recurrent events so physical therapists may be keen to keep track of the activity levels among this vulnerable patient population. One way to accomplish that is to use accelerometers.

Jewelry-Sized Genius

As with gait analysis systems, accelerometry-sensing technologies historically were complex, expensive, and not particularly user-friendly. Physical therapists had few options for objectively assessing free-living physical activity patterns among stroke survivors. Recently, however, younger populations have embraced activity trackers that are user-friendly and affordable. This category of devices includes an ankle-worn consumer-level accelerometer that can accurately measure step counts—including treadmill walking. Likewise, it can calculate distance traveled, floors climbed, and calories burned. While the anatomical placement of these accelerometers can affect accuracy and reliability, they nonetheless can maintain a connection between the post-stroke patient and physical therapist, while providing data that keeps each one accountable to the other.

An example of how these small wearable devices serve stroke rehabilitation is summed by the authors of a 2018 report led by Jonathan Hui and published in Physiotherapy Canada. The peer-reviewed study investigated the effect of accelerometers on community-dwelling stroke survivors and left the authors to make the following conclusion:

“Using devices to monitor activity levels may be an integral component of promoting daily physical activity in this population. The participants in our study enjoyed using these activity-tracking devices, many experienced minimal to no complications, and several felt that the devices provided external motivation for activity change and would consider using them in the future.”

Good and Getting Better

Good gait analysis has never taken the path of least resistance, but medical and consumer device manufacturers have found ways to make these critical measures easier and more affordable. While the design trend has been toward smaller technologies at the same time wireless connectivity has also been integrated into these devices, making communication between patient and therapist easier than ever to maintain. As the rehab profession continues to move through the COVID-19 pandemic, this important feature will help blaze a trail toward outcomes that are more sustainable and accessible for all. RM

Frank Long, MS, is Editorial Director of Rehab Management. For more information, contact


  1. Hui J, Heyden R, Bao T, et al. Validity of the FitBit One for measuring activity in community-dwelling stroke survivors. PhysiotherCan. 2018;70(1):81-89.
  2. Gresham GE, Fitzpatrick TE, Wolf PA, et al. Residual disability in survivors of stroke—the Framingham study. N Engl J Med. 1975;293(19):954–6.

Related Content:
Search Here for Gait Analysis Data
AI-Powered Insole Turns Shoes Into a Portable Gait Analysis Lab
Keystroke Time, Rather Than Gait Analysis, Proposed as Diagnostic Test for Parkinson’s


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[WEB PAGE] Gait – Physiopedia


Gait pattern.jpg

Human gait depends on a complex interplay of major parts of the nervous, musculoskeletal and cardiorespiratory systems.

  • The individual gait pattern is influenced by age, personality, mood and sociocultural factors.
  • The preferred walking speed in older adults is a sensitive marker of general health and survival.
  • Safe walking requires intact cognition and executive control.
  • Gait disorders lead to a loss of personal freedom, falls and injuries and result in a marked reduction in the quality of life[1]


Gait – the manner or style of walking.

Gait Analysis –

An analysis of each component of the three phases of ambulation is an essential part of the diagnosis of various neurologic disorders and the assessment of patient progress during rehabilitation and recovery from the effects of a neurologic disease, a musculoskeletal injury or disease process, or amputation of a lower limb.

Gait speed

  • The time it takes to walk a specified distance, usually 6 m or less. Slower speeds correlate with an increased risk of mortality in geriatric patients.[2]
  • Normal walking speed primarily involves the lower extremities, with the arms and trunk providing stability and balance.
  • Faster speeds – body depends on the upper extremities and trunk for propulsion, balance and stability with the lower limb joints producing greater ranges of motion.[3]

The gait cycle is a repetitive pattern involving steps and strides[4]

A step is one single step

A stride is a whole gait cycle.

Step time – time between heel strike of one leg and heel strike of the contra-lateral leg[4].

Step width – the mediolateral space between the two feet[4].

The demarcation between walking and running occurs when

  • periods of double support during the stance phase of the gait cycle (both feet are simultaneously in contact with the ground) give way to two periods of double float at the beginning and the end of the swing phase of gait (neither foot is touching the ground)[5].

The Gait Cycle


The sequences for walking that occur may be summarised as follows:[6]

  1. Registration and activation of the gait command within the central nervous system.
  2. Transmission of the gait systems to the peripheral nervous system.
  3. Contraction of muscles.
  4. Generation of several forces.
  5. Regulation of joint forces and moments across synovial joints and skeletal segments.
  6. Generation of ground reaction forces.

The normal forward step consists of two phases: stance phase; swing phase,

  • Stance phase occupies 60% of the gait cycle, during which one leg and foot are bearing most or all of the body weight
  • Swing phase occupies only 40% of it[4], during which the foot is not touching the walking surface and the body weight is borne by the other leg and foot.
  • In a complete two-step cycle both feet are in contact with the floor at the same time for about 25 per cent of the time. This part of the cycle is called the double-support phase.Gait cycle phases: the stance phase and the swing phase and involves a combination of open and close chain activities.[3]

The 90 second video below gives the basics of this cycle

Phases of the Gait Cycle (8 phase model):[4][8]

  1. Initial Contact
  2. Loading Response
  3. Midstance
  4. Terminal Stance
  5. Pre swing
  6. Initial Swing
  7. Mid Swing
  8. Late Swing.[9]

Heel Strike (or initial contact) – Short period, begins the moment the foot touches the ground and is the first phase of double support.[3]


  • 30° flexion of the hip: full extension in the knee: ankle moves from dorsiflexion to a neutral (supinated 5°) position then into plantar flexion.[3][4]
  • After this, knee flexion (5°) begins and increases, just as the plantar flexion of the heel increased.[4]
  • Plantar flexion is allowed by eccentric contraction of the tibialis anterior
  • Extension of the knee is caused by a contraction of the quadriceps
  • Flexion is caused by a contraction of the hamstrings,
  • Flexion of the hip is caused by the contraction of the rectus femoris.[4]

Foot Flat (or loading response phase)

  • Body absorbs the impact of the foot by rolling in pronation.[3]
  • Hip moves slowly into extension, caused by a contraction of the adductor magnus and gluteus maximus muscles.
  • Knee flexes to 15° to 20° of flexion. [4]
  • Ankle plantarflexion increases to 10-15°.[3][4]


  • Hip moves from 10° of flexion to extension by contraction of the gluteus medius muscle.[4]
  • Knee reaches maximal flexion and then begins to extend.
  • Ankle becomes supinated[3] and dorsiflexed (5°), which is caused by some contraction of the triceps surae muscles.[3]
  • During this phase, the body is supported by one single leg.
  • At this moment the body begins to move from force absorption at impact to force propulsion forward.[3]

Heel Off

  • Begins when the heel leaves the floor.
  • Bodyweight is divided over the metatarsal heads.[3]
  • 10-13° of hip hyperextension, which then goes into flexion.
  • Knee becomes flexed (0-5°)[4]
  • Ankle supinates and plantar flexes.[4]

Toe Off/pre-swing

  • Hip becomes less extended.
  • Knee is flexed 35-40°
  • Plantar flexion of the ankle increases to 20°.[3][4]
  • The toes leave the ground.[4]

Early Swing

  • Hip extends to 10° and then flexes due to contraction of the iliopsoas muscle[4] 20° with lateral rotation.[3][4]
  • Knee flexes to 40-60°
  • Ankle goes from 20° of plantar flexion to dorsiflexion, to end in a neutral position.[3]

Mid Swing

  • Hip flexes to 30° (by contraction of the adductors) and the ankle becomes dorsiflexed due to a contraction of the tibialis anterior muscle.[4]
  • Knee flexes 60° but then extends approximately 30° due to the contraction of the sartorius muscle.[3][4](caused by the quadriceps muscles).[3][4]

Late Swing/declaration

  • Hip flexion of 25-30°
  • Locked extension of the knee
  • Neutral position of the ankle.[3]

Gait Cycle – Anatomical Considerations

  • Pelvic region – anterior-posterior displacement, which alternates from left to right. Facilitates anterior movement of the leg (each side anterior-posterior displacement of 4-5°).[3][4][8]
  • Frontal plane – varus movement in the: foot between heel-strike and foot-flat and between heel-off and toe-off; hip, in lateral movements (when the abductors are too weak, a Trendelenburg gait can be observed).[3][8] Valgus movement between foot-flat and heel off in the feet.
  • A disorder in any segment of the body can have consequences on the individual’s gait pattern.[10]

Gait Disorders

Gait disorders – altered gait pattern due to deformities, weakness or other impairments eg loss of motor control or pain[11].

Human falls.jpg
  • Prevelence increases with age and the number of people affected will substantially increase in the coming decades due to the expected demographic changes.
  • Lead to a loss of personal freedom and to reduced quality of life.
  • Precursors of falls and therefore of potentially severe injuries in elderly persons[1].

Causes of gait disorders include

  • Neurological, orthopedic, medical and psychiatric conditions and multifactorial etiology becomes more common with advancing age, making classification and management more complex.
  • Any gait disorder should be thoroughly investigated in order to improve patient mobility and independence, to prevent falls and to detect the underlying causes as early as possible.
  • Thorough clinical observation of gait, careful history taking focussed on gait and falls and physical, neurological and orthopedic examinations are basic steps in the categorization of gait disorders and serve as a guide for ancillary investigations and therapeutic interventions.

Gait Descriptions

Trendelenburg gait.jpg

This is not an exhaustive list.

  • Antalgic gait a limp adopted so as to avoid pain on weight-bearing structures, characterized by a very short stance phase.
  • Ataxic gait an unsteady, uncoordinated walk, with a wide base and the feet thrown out, coming down first on the heel and then on the toes with a double tap.This gait is associated with cerebellar disturbances and can be seen in patients with longstanding alcohol dependency. People with ‘Sensory’Disturbances may present with a sensory ataxic gait. Presentation is a wide base of support, high steps, and slapping of feet on the floor in order to gain some sensory feedback. They may also need to rely on observation of foot placement and will often look at the floor during mobility due to a lack of proprioception
  • Equine gait a walk accomplished mainly by flexing the hip joint; seen in crossed leg palsy.
  • Parkinsonian Gait (seen in parkinson’s disease and other neurologic conditions that affect the basal ganglia). Rigidity of joints results in reduced arm swing for balance. A stooped posture and flexed knees are a common presentation. Bradykinesia causes small steps that are shuffling in presentation. There may be occurrences of freezing or short rapid bursts of steps known as ‘festination’ and turning can be difficult.
  • Trendelenburg gait, the gait characteristic of paralysis of the gluteus medius muscle, marked by a listing of the trunk toward the affected side at each step.
  • Hemiplegic gait a gait involving flexion of the hip because of footdrop and circumduction of the leg.
  • Steppage gait the gait in footdrop in which the advancing leg is lifted high in order that the toes may clear the ground. It is due to paralysis of the anterior tibial and fibular muscles, and is seen in lesions of the lower motor neuron, such as multiple neuritis, lesions of the anterior motor horn cells, and lesions of the cauda equina.
  • Stuttering gait a walking disorder characterized by hesitancy that resembles stuttering; seen in some hysterical or schizophrenic patients as well as in patients with neurologic damage.
  • Tabetic gait an ataxic gait in which the feet slap the ground; in daylight the patient can avoid some unsteadiness by watching his feet.
  • Waddling gait exaggerated alternation of lateral trunk movements with an exaggerated elevation of the hip, suggesting the gait of a duck; characteristic of muscular dystrophy.
  • Diplegic Gait (Spastic gait). Spasticity is normally associated with both lower limbs. Contractures of the adductor muscles can create a ‘scissor’ type gait with a narrowed base of support. Spasticity in the lower half of the legs results in plantarflexed ankles presenting in ‘tiptoe’ walking and often toe dragging. Excessive hip and knee flexion is required to overcome this
  • Neuropathic Gaits. High stepping gait to gain floor clearance often due to foot drop[10][11][12][2]

Musculoskeletal Causes:

Pathological gait patterns resulting from musculoskeletal are often caused by soft tissue imbalance, joint alignment or bony abnormalities affect the gait pattern as a result[11].

Hip Pathology

  • Arthritis is a common cause of pathological gait. An arthritic hip has reduced range of movement during swing phase which causes an exaggeration of movement in the opposite limb ‘hip hiking[11].
  • Excessive Hip Flexion can significantly alter gait pattern most commonly due to; • Hip flexion contractures • IT band contractures, • Hip flexor spasticity, • Compensation for excessive knee flexion and ankle DF, • Hip pain • Compensation for excess ankle plantar flexion in mid swing. The deviation of stance phase will occur mainly on the affected side. The result is forward tilt of the trunk and increased demand on the hip extensors or increased lordosis of the spine with anterior pelvic tilt. A person with reduced spinal mobility will adopt a forward flexion position in order to alter their centre of gravity permanently during gait.
  • Hip Abductor Weakness. The abductor muscles stabilise the pelvis to allow the opposite leg to lift during the swing phase. Weak abductor muscles will cause the hip to drop towards the side of the leg swinging forward. This is also known as Trendelenburg gait[12]
  • Hip Adductor Contracture. During swing phase the leg crosses midline due to the weak adductor muscles, this is known as ‘scissor gait’[12]
  • Weak Hip Extensors will cause a person to take a smaller step to lessen the hip flexion required for initial contact, resulting in a lesser force of contraction required from the extensors. Overall gait will be slower to allow time for limb stabilisation. Compensation is increased posterior trunk positioning to maintain alignment of the pelvis in relation to the trunk[12]
  • Hip Flexor Weakness results in a smaller step length due to the weakness of the muscle to create the forward motion. Gait will likely be slower and may result in decreased floor clearance of the toes and create a drag
  • Knee Pathologies
  • Weak Quadriceps. The quadriceps role is to eccentrically control the knee during flexion through the stance phase. If these muscles are weak the hip extensors will compensate by bringing the limb back into a more extended position, reducing the amount of flexion at the knee during stance phase. Alternatively heel strike will occur earlier increasing the ankle of plantar flexion at the ankle, preventing the forward movement of the tibia, to help stabilise the knee joint[12].
  • Severe Quadriceps Weakness or instability at the knee joint will present in hyperextension during the initial contact to stance phase. The knee joint will ‘snap’ back into hyperextension as the bodyweight moves forwards over the limb[12] 
  • Knee Flexion Contraction will cause a limping type gait pattern. The knee is restricted in extension, meaning heel strike is limited and step length reduced. To compensate the person is likely to ‘toe walk’ during stance phase. Knee flexion contractures of more than 30 degrees will be obvious during normal paced gait. Contractures less then this will be more evident with increased speeds[11][12]

Ankle Pathologies

  • Ankle Dorsiflexion Weakness results in a lack of heel strike and decreased floor clearance. This leads to an increased step height and prolonged swing phase[12]
  • Calf Tightening or Contractures due to a period of immobilisation or trauma will cause reduced heel strike due to restricted dorsiflexion. The compensated gait result will be ‘toe walking’ on stance phase, reduced step length and excessive knee and hip flexion during swing phase to ensure floor clearance[11].

Foot Pathologies

  • Hallux Rigidus results in a lack of dorsiflexion of the great toe.  The MPJ uses the windlass effect to raise the arch and stiffen the foot during dorsiflexion of the hallux. This stiffness increases the efficiency of the propulsion portion of the gait cycle. To be efficient in creating stiffness, the hallux should be able to dorsiflex at least 65 degrees.

Leg Length Discrepancy

  • Leg length discrepancy can be as a result of an asymmetrical pelvic, tibia or femur length or for other reasons such as a scoliosis or contractures. The gait pattern will present as a pelvic dip to the shortened side during stance phase with possible ‘toe walking’ on that limb. The opposite leg is likely to increase its knee and hip flexion to reduce its length[11].

Antalgic Gait

  • Antalgic gait due to knee pain presents with decreased weight bearing on the affected side. The knee remains in flexion and possible toe weight-bearing occurs during stance phase[11]
  • Antalgic gait due to ankle pain may present with a reduced stride length and decreased weight bearing on the affected limb. If the problem is pain in the forefoot then toe-off will be avoided and heel weight-bearing used. If the pain is more in the heel, toe weight-bearing is more likely. General ankle pain may result in weight-bearing on the lateral border[11][12].
  • Antalgic gait due to hip pain results in reduced stance phase on that side. The trunk is propelled quickly forwards with the opposite shoulder lifted in an attempt to even the weight distribution over the limb and reduce weight-bearing. Swing phase is also reduced[11]

Below are links to videos demonstrating normal gait and various gait abnormalities:[13][14]

Age Related Gait Changes

Any threat to balance induces changes in the strategies for standing and walking – the stance and gait base is widened, bipedal floor contact is prolonged, step length becomes shorter, the feet are lifted less high during the swing phase, walking becomes slower and the posture becomes stooped.

  • The fear of falling and the actual risk of falling increase with age.
  • Older persons are therefore more likely to use these protective gait strategies.
  • As muscle power diminishes and proprioception and vision become impaired with age, body sway on standing, which is constantly present to a slight degree, increases.
  • In younger persons this sway can be compensated by activating the muscle groups around the upper ankle joints. Older persons shift this compensation to the proximal muscle groups around the hips due to loss of distal proprioception.
  • This requires an increased reliance on vestibular afferents, which undergo less change during the ageing process.
  • The preferred walking speed in apparently healthy elderly subjects declines by 1 % per year from a mean of 1.3 m/s in the seventh decade to a mean of 0.95 m/s in those aged over 80 years (caused by a decrease in step length rather than by a change in cadence).
  • Gait changes are to some degree a consequence of normal ageing however individual walking speed in elderly subjects is a strong indicator of general health and survival[1]

Gait Analysis

  • The analysis of the gait cycle is important in the biomechanical mobility examination to gain information about lower limb dysfunction in dynamic movement and loading.[15]
  • When analysing the gait cycle, it is best to examine one joint at a time.[3]
  • Objective and subjective methods can be used.[16][17] 


  • Different gait patterns – We might ask the individual to walk normally, on insides and outsides of feet, in a straight line, running (all the time looking to compare sides and understanding of “normal”).  
  • Ask/observe the type of footwear the patient uses (a systematic review suggests shoes affect velocity, step time, and step length in younger children’s gait[18]).


Gait Analysis CP.jpg

An objective approach is quantitative and parameters like time, distance, and muscle activity will be measured. Other objective methods to assess the gait cycle that use equipment include:[19][17]

Qualitative methods to assess and analyse gait include: [17]

Clinical Bottom Line

Gait assessment.png

Good knowledge of anatomy and biomechanics is important to understand the different phases of the gait cycle. When you know the normal pattern, you can see what’s going wrong!

Related articles

Gait in prosthetic rehabilitation – Physiopedia

Running Biomechanics – Physiopedia

Gait deviations in amputees – Physiopedia

Classification of Gait Patterns in Cerebral Palsy – Physiopedia

PII: S0966-6362(97)00038-6


  1. ↑ Jump up to:1.0 1.1 1.2 Pirker W, Katzenschlager R. Gait disorders in adults and the elderly. Wiener Klinische Wochenschrift. 2017 Feb 1;129(3-4):81-95.Available from: (last accessed 27.6.2020)
  2. ↑ Jump up to:2.0 2.1 Medical dictionary Gait speed Available from: (last accessed 28.6.2020)
  3. ↑ Jump up to:3.00 3.01 3.02 3.03 3.04 3.05 3.06 3.07 3.08 3.09 3.10 3.11 3.12 3.13 3.14 3.15 3.16 3.17 3.18 Shultz SJ et al. Examination of musculoskeletal injuries. 2nd ed, North Carolina: Human Kinetics, 2005. p55-60.
  4. ↑ Jump up to:4.00 4.01 4.02 4.03 4.04 4.05 4.06 4.07 4.08 4.09 4.10 4.11 4.12 4.13 4.14 4.15 4.16 4.17 4.18 4.19 4.20 Loudon J, et al. The clinical orthopedic assessment guide. 2nd ed. Kansas: Human Kinetics, 2008. p.395-408.
  5. Jump up↑ The biomechanics of running Tom F. Novacheck Motion Analysis Laboratory, Gillette Children’s Specialty Healthcare, Uni6ersity of Minnesota, 200 E. Uni6ersity A6e., St. Paul, MN 55101, USA Received 25 August 1997; accepted 22 September 1997 Available from:
  6. Jump up↑ Vaughan CL. Theories of bipedal walking: an odyssey. J Biomech 2001;36(2003):513-523.Available from
  7. Jump up↑ Nicole Comninellis The Gait Cycle Animation Available from
  8. ↑ Jump up to:8.0 8.1 8.2 Demos, Gait analysis, (, 2004.
  9. Jump up↑ Berger W, et al. Corrective reactions to stumbling in man: neuronal co-ordination of bilateral leg activity during gait. J Physiol 1984;357: 109-125.
  10. ↑ Jump up to:10.0 10.1 Shi D, et al. Effect of anterior cruciate ligament reconstruction on biomechanical features of knee level in walking: a meta analysis. Chin Med J 2010;123(21):3137-3142.
  11. ↑ Jump up to:11.0 11.1 11.2 11.3 11.4 11.5 11.6 11.7 11.8 11.9 Malanga G and Delisa J.A. Section One: Clinical Observation. Office of rehabilitation Research and Development No Date. (accessed 6 February 2010)
  12. ↑ Jump up to:12.0 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 University of Washington. Pathologic Gait: Musculoskeletal (accessed 5 February 2015)
  13. Jump up↑ onlinemedicalvideoAbnormal Gait Exam : Myopathic Gait Demonstration. Available from
  14. Jump up↑ scfpta gait deviation published final 001.wmvAvailable from
  15. Jump up↑ Langer PS, et al. A practical manual of clinical electrodynography. 2nd ed. Deer Park: The Langer Foundation for Biomechanics and Sports Medicine Research, 1989.
  16. ↑ Jump up to:16.0 16.1 Terrier P, Schutz Y. How useful is satellite positioning system (GPS) to track gait parameters? A review. J Neuro Eng Rehab 2005;2:28.
  17. ↑ Jump up to:17.0 17.1 17.2 Deckers JHM, et al. Ganganalyse en looptraining voor de paramedicus, Houten, Bohnfleu van Lonhum, 1996.
  18. Jump up↑ Cranage S, Perraton L, Bowles KA, Williams C. The impact of shoe flexibility on gait, pressure and muscle activity of young children. A systematic review. Journal of Foot and Ankle Research. 2019 Dec 1;12(1):55.
  19. Jump up↑ Frigo C, et al. Functionally oriented and clinically feasible quantitative gait analysis method. Med Biol Eng Comput 1998;36:179-185.
  20. Jump up↑ Shumway-Cook A, Woollacott MH. Motor control: translating research into clinical practice. Lippincott Williams and Wilkins, 2007. p.408.
  21. Jump up↑ Van Peppen RPS, KNGF-richtlijn Beroerte, 2004, Nederlands Tijdschrift voor Fysiotherapie.
  22. Jump up↑ Baer RH, Wolf SL. Modified emory functional ambulation profile: an outcome measure for the rehabilitation of post stroke gait dysfunction. Stroke 2001;32(4):973-979.
  23. Jump up↑ Potsiadlo D, Richardson S. The timed “Up and Go”: a test of functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39(2):142-148.
  24. Jump up↑ Shephard RJ, Taunton JE. Foot and ankle in sport and exercise, Toronto:Karger, 1987. p30-38.
  25. Jump up↑ Bautmans I, et al. The feasibility of whole body vibration in institutionalised elderly persons and its influence on muscle performance, balance and mobility: a randomised controlled trial. BMC Geriatr 2005;5:17.


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[ARTICLE] Effect of Exercise on Gait Kinematics and Kinetics in Patients with Chronic Ischaemic Stroke – Full Text


Introduction In 2014, American Heart Association and American Stroke Association (AHA/ASA) issued exercise guidelines for stroke patients.
Aim of the Study: To study the effects of an exercise programme based on AHA/ ASA guidelines, on gait kinematics and kinetics in patients with chronic ischemic stroke.
Materials and Methods: Twelve stroke patients, 67.33 ± 9.14 years old, followed an 8-week exercise programme, with 3 hourly sessions per week, consisting of strength, endurance and flexibility training, as well as neuromuscular activities. Patients’ gait kinematics and kinetics were evaluated before and after the intervention using a 3-dimensional gait analysis system.
Results: In most cases, patients in the intervention group showed significant increase or no change in gait kinematics, significant increase in joint moments at the anterior-posterior plane during support phase, and non-signi- ficant change in the frontal and transverse planes kinetics.
Conclusions: Exercise prevented further deterioration and/or led to improved walking pattern.

1. Introduction

It is estimated that one in 5 women and one in 6 men will sustain a stroke up to the age of 75 years [1] . The main purpose of rehabilitation in such patients is to achieve the maximum possible personal performance, physical and psychological, with the ultimate goal of regaining a level of functional independence that will allow them to be re-integrated into social life as much as possible [2] . However, stroke patients often adopt a sedentary lifestyle [3] [4] [5] [6] . This may be attributed to 1) factors associated with patients themselves, such as depression, lack of interest or motivation, decreased perception, decreased confidence, ignorance that exercise is possible and desirability and fear of falls, of a new stroke or other undesirable effects; 2) practical factors, such as lack of support from family or other social actors, inability to access exercise sites, inadequate public transport, health professionals’ ignorance of the availability of physical activity services; 3) financial cost [7] [8] [9] [10] [11] . Conversely, exercise in groups may improve patient motivation [12] .

In 2014, the council of the American Heart Association and the American Stroke association (AHA/ASA) revised the exercise recommendations for stroke patients at all stages of their recovery [13] . Therefore, the aim of this study was to assess the effect of an exercise programme based on these recommendations on gait kinematics and kinetics of ischaemic stroke patients in the chronic phase of recovery.[…]


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[Abstract] A Method for Self-Service Rehabilitation Training of Human Lower Limbs – IEEE Conference Publication


Recently, rehabilitation robot technologies have been paid more attention by the researchers in the fields of rehabilitation medicine engineering and robotics. To assist active rehabilitation of patients with unilateral lower extremity injury, we propose a new self-service rehabilitation training method in which the injured lower limbs are controlled by using the contralateral healthy upper ones. First, the movement data of upper and lower limbs of a healthy person in normal walk are acquired by gait measurement experiments. Second, the eigenvectors of upper and lower limb movements in a cycle are extracted in turn. Third, the linear relationship between the movement of upper and lower limbs is identified using the least squares method. Finally, the results of simulation experiments show that the established linear mapping can achieve good accuracy and adaptability, and the self-service rehabilitation training method is effective.

via A Method for Self-Service Rehabilitation Training of Human Lower Limbs – IEEE Conference Publication

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[ARTICLE] Effect of Exercise on Gait Mechanics in a Patient with Severe Gait Disorder Due to Chronic Ischaemic Stroke: A Case Study – Full Text


We describe the effects of an exercise programme based on the American Heart Association and American Stroke Association guidelines for stroke patients on gait mechanics in a patient with severe gait disorder due to chronic ischaemic stroke. A 74-year-old female patient, with right hemiparesis as a result of a stroke attack before 18 months followed an 8-week exercise programme, consisting of three hourly sessions per week. Patient’s gait mechanics were evaluated before and after the intervention using a three-dimensional gait analysis system, with six infrared cameras, two force plates, and an electronic timing system. Exercise led to increase of spatial and decrease of temporal gait parameters, increase of joint range of motion and lower limb muscle powers during the entire gait cycle and increase of the moments in the support phase. In conclusion, exercise had a positive effect on this patient’s gait pattern and improved her functionality.

1. Introduction

Stroke is the most common cause of serious long-term disability [1] . Although the rate of neurological recovery is rapid in the first 4 weeks after the stroke [2] , functionality improvement seems to extend beyond this period, possibly through the development of compensatory strategies against neurological deficits [3] . However, patients often adopt a sedentary lifestyle that leads to dependence on other people, but also to increased risk of falls and recurrence of stroke [4] , or other cardiovascular events [5] [6] . In particular, patients after stroke are significantly less physically active in comparison with the elderly who suffer from chronic musculoskeletal diseases or other cardiovascular diseases [7] [8] [9] [10] . A sedentary lifestyle exacerbates further their cardiovascular function and the already impaired functional capacity [11] [12] . Furthermore, it leads to increased fatigue, muscle atrophy and weakness, osteoporosis and impaired circulation in the lower limbs. Finally, the greater dependence of patients with stroke on others for daily activities and their impaired ability for usual social activities can have serious negative psychological effects [13] .

In 2014, the American Heart Association and American Stroke Association (AHA/ASΑ) published the revised recommendations on exercise in patients with stroke [14] . Nevertheless, to the best of our knowledge, there is no data concerning the effect of the above exercise programme on patients’ gait pattern. Importantly, gait pattern affects muscle and joint loads during movement and thus on the long-term function of the skeletal system [15] [16] [17] . We herein describe the effect of an exercise programme based on these recommendations on gait mechanics in a patient with severe gait disorder resulting from an ischaemic stroke in the chronic phase of rehabilitation.


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[ARTICLE] Gait analysis with the Kinect v2: normative study with healthy individuals and comprehensive study of its sensitivity, validity, and reliability in individuals with stroke – Full Text



Gait is usually assessed by clinical tests, which may have poor accuracy and be biased, or instrumented systems, which potentially solve these limitations at the cost of being time-consuming and expensive. The different versions of the Microsoft Kinect have enabled human motion tracking without using wearable sensors at a low-cost and with acceptable reliability. This study aims: First, to determine the sensitivity of an open-access Kinect v2-based gait analysis system to motor disability and aging; Second, to determine its concurrent validity with standardized clinical tests in individuals with stroke; Third, to quantify its inter and intra-rater reliability, standard error of measurement, minimal detectable change; And, finally, to investigate its ability to identify fall risk after stroke.


The most widely used spatiotemporal and kinematic gait parameters of 82 individuals post-stroke and 355 healthy subjects were estimated with the Kinect v2-based system. In addition, participants with stroke were assessed with the Dynamic Gait Index, the 1-min Walking Test, and the 10-m Walking Test.


The system successfully characterized the performance of both groups. Significant concurrent validity with correlations of variable strength was detected between all clinical tests and gait measures. Excellent inter and intra-rater reliability was evidenced for almost all measures. Minimal detectable change was variable, with poorer results for kinematic parameters. Almost all gait parameters proved to identify fall risk.


Results suggest that although its limited sensitivity to kinematic parameters, the Kinect v2-based gait analysis could be used as a low-cost alternative to laboratory-grade systems to complement gait assessment in clinical settings.


The physiological basis of cerebrovascular accidents make gait deficits a common sequelae after stroke [1]. More than 60% of stroke survivors are unable to walk independently after the injury [2] and, even after rehabilitation, more than half of the cases still present gait-related deficits [3]. Most prevailing deficits after stroke include reduced speed [4] and increased gait inter-limb asymmetry [5]. These gait impairments can be aggravated in the elderly, due to the natural musculoskeletal and cognitive decline with age [67], where the incidence of stroke is higher [8]. Importance of these deficits relies on their great impact on independence [9], quality of life [10], and fall risk [11]. Consequently, their adequate assessment is necessary for a proper diagnosis and to plan, if required, customized interventions to each individual’s condition and evaluate the effectiveness of these interventions.

Assessment of gait is commonly performed in the clinical setting using standardized scales and tests that evaluate different aspects of human locomotion and, in some cases, compare the results of the person being tested with those obtained by a matched healthy sample [12]. Although these tools are easy to administer and, in general, not time-consuming, they can present lack of specificity and, more importantly, may have poor accuracy and be biased by subjective evaluations [13]. Over the years, different technological solutions have been proposed to overcome these limitations. Accurate estimation of spatiotemporal parameters has been enabled by instrumented walkways [14] and force plates [15], generally, from ground reaction forces during walking. Estimation of kinematic parameters, however, require the position of several joints to be tracked during the test, which has been indirectly facilitated by different technological solutions that estimate the position of some sensors that are attached to specific body parts [16,17,18]. Among them, optical motion tracking has become the most common alternative for accurate investigation of kinematic gait parameters [19]. Although instrumented systems allow for accurate spatiotemporal and kinematic analysis, their high cost and large size have restricted their use to research laboratories and large clinical centers with high economic resources [20].

In the last years, the Microsoft Kinect (Microsoft, Redmond, WA), a portable off-the-shelf infrared camera originally intended for entertainment, has enabled human motion tracking without using wearable sensors at a very low-cost. Reliability studies have shown comparable performance of the Kinect to laboratory-grade gait analysis systems, for both the first [2122] and the second version of the device [23], known as the Kinect v2, which features improved depth accuracy and number of joints tracked [24]. Characteristics of the Kinect v2 have motivated their use for assessing spatiotemporal [25,26,27] and kinematic parameters of gait [2628] with promising results in healthy individuals, even on treadmills [2829]. Its reliability in stroke population, however, remains almost unexplored. Little evidence suggests that data retrieved from the Kinect v2 can be used to differentiate healthy subjects from individuals with stroke [30] and to complement clinical assessment [31]. Despite of the existing data supporting the reliability of the Kinect v2 to assess spatiotemporal and kinematic gait parameters, the unavailability of the software, the limited investigation in individuals with stroke, and the unknown psychometric properties of Kinect-based tests in this population could compromise the clinical relevance of these results.

The objective of this study was fourfold. First, to compare a cohort of individuals with stroke with respect to a group of healthy controls to determine the sensitivity of an open-access Kinect v2-based gait analysis system to motor disability and aging. Second, to determine the concurrent validity of the system with standardized clinical tests in individuals with stroke. Third, to quantify its reliability as defined by the inter and intra-rater reliability, the standard error of measurement, and the minimal detectable change. And, finally, to investigate the ability of the system to identify risk of falls after stroke.



Continue —>  Gait analysis with the Kinect v2: normative study with healthy individuals and comprehensive study of its sensitivity, validity, and reliability in individuals with stroke | Journal of NeuroEngineering and Rehabilitation | Full Text

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[ARTICLE] The validity of spatiotemporal gait analysis using dual laser range sensors: a cross-sectional study – Full Text



The spatiotemporal parameters were used for sophisticated gait analysis in widespread clinical use. Recently, a laser range sensor has been proposed as a new device for the spatiotemporal gait measurement. However, measurement using a single laser range sensor can only be used for short-range gait measurements because the device irradiates participants with lasers in a radial manner. For long-range gait measurement, the present study uses a modified method using dual laser range sensors installed at opposite ends of the walking path. The aim of present study was to investigate the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a computer-based instrumented walkway system.


Ten healthy participants were enrolled in this study. Ten-meter walking tests at 100, 75, and 50% of the comfortable speed were conducted to determine the concurrent validity of the proposed method compared to instrumented walkway measurements. Frequency distributions of errors for foot-contact (FC) and foot-off (FO) estimated times between the two systems were also calculated to determine the adequacy of estimation of FC and FO from three perspectives: accuracy (smallness of mean error), precision (smallness of variability), and unambiguity (monomodality of histogram). Intra-class correlation coefficient (2,1) was used to determine the concurrent validity of spatiotemporal parameters between the two systems.


The results indicate that the detection times for FC and FO estimated by the proposed method did not differ from those measured by the instrumented walkway reference system. In addition, histogram for FC and FO showed monomodality. Intra-class correlation coefficients of the spatiotemporal parameters (stance time: 0.74; double support time: 0.56; stride time: 0.89; stride length: 0.83; step length: 0.71; swing time: 0.23) were not high enough. The mean errors of all spatiotemporal parameters were small.


These results suggest that the proposed lacks sufficient concurrent validity for spatiotemporal gait measurement. Further improvement of this proposed system seems necessary.


In gait disorder rehabilitation, gait analysis plays an important role in optimizing treatment for each patient [1234]. Conventionally, visual observation of gait analysis is easy and low cost and is commonly used in rehabilitation facilities. However, previous studies report that visual observation gait analysis has low inter-rater and test-retest reliability as well as low criterion concurrent validity in contrast to kinematic analyses using various instruments [45]. For highly accurate measurements with good inter-rater and test-retest reliability, a three-dimensional motion analysis system has been used. Although this system is able to measure whole-body joint motions, it has high costs and is time- and labor-intensive to set up [6].

Spatiotemporal gait measurement is another valuable method to identify gait deviations, make diagnoses, determine appropriate therapy, and monitor patient progress [23]. Frequently, parameters such stance time, swing time, double support time, stride time, stride length, and step length are evaluated [78910]. To calculate these spatiotemporal parameters, accurate detection of two events for switching between the stance and swing phases is essential: foot contact (FC) and foot off (FO). FC is defined as when any point of the foot first contacts and is the starting point of the stance phase. FO is when the sole is raised completely from the floor and is the onset of the swing phase. A measurement system for detection of FC and FO is a computer-based instrumented walkway system with pressure sensors and produces high inter-rater and test-retest reliability [278910]. Although this system has a relatively reasonable price as compared with a three-dimensional motion analysis system, it is still considerably expensive to become widely used. In addition, it occupies a large amount of floor space and greatly limits effective use of the exercise room. While this system is placed on the floor, the place is not able to be used for other purposes even though the exercise room has limited floor space.

Recently, spatiotemporal gait measurement using a laser range scanner has been proposed as easy to install and remove [11121314]. With a laser range scanner, both lower legs are measured using two best-fitting circles whose contours are defined by laser points. Although this method is useful for easy measurement of gait parameters in a clinical setting, the raw contour of the leg is incomplete because the sensor provides only one-sided information [11]. In addition, the number of laser points comprising the spheres decreases with long-range gait measurements because the lasers irradiate participants in a radial manner. Since the radial range decreases with increasing distance from the laser, this causes larger measurement errors.

For eliminating problems in long-range gait measurement, we proposed a method of spatiotemporal gait analysis using dual laser range sensors installed at opposite ends of the walking path. Because the measurement using laser range sensor is quick and easy method, this proposed method has a high degree of usability for clinical practice. However, it is not clear whether the proposed method has concurrent validity, which is defined as evaluation of an instrument against an already validated measure [15], for spatiotemporal gait measurement by comparison to a computer based instrumented walkway system (reference system) that was widely used for criterion-related validity. The aim of present study was to investigate the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a reference system.



Ten healthy participants (7 males and 3 females, 20–24 years of age, 154-184 cm in height, 49-70 kg in weight) were enrolled in the present study. All participants have no history of orthopedic, neurophysiologic, and cardiovascular diseases. Informed consent was obtained from each participant before the experiments. The present study was approved by the ethics committee and was conducted according to the Declaration of Helsinki for human experiments.

Experimental procedures

This study used a cross-sectional design to assess the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a reference system.

Participants wearing short pants were asked to get on a walking path and walk barefoot along a 12 m straight line including 3.5 m in front of the measured walking path and 3.5 m beyond the end of walking path. Each participant performed one trial at each speed: 100, 75, and 50% of the comfortable speed in a subjective manner. Before measurement, the order of the speed conditions was randomized for each participant. During the gait test, spatiotemporal measurements were carried out simultaneously using both the proposed method and the reference system. The inter-trial interval was set to 2 minutes to prevent fatigue.

Proposed method using laser range sensors

A two-dimensional radial scanning laser range sensor (UTM-30LX, Hokuyo Automatic Co., Ltd., Osaka, Japan) was used (Fig. 1a). The device has a scanning range from − 135° to 135° in steps of 0.25° (total of 1080 data points measuring the distance from the sensor to the target), and one scan is completed in 0.025 s (i.e., the sampling frequency is 40 Hz). In addition, the device exhibits very small test-retest variability and the relative error of a distance (0.1 to 10 m, σ < 0.01 m and ± 0.01 m, white Kent paper, respectively) in the repeated measurements using same laser range sensor unit (i.e. unit testing). Two devices were installed at opposite ends of a five-meter walking path at the level of the average shin height (0.25 m above the floor) [16] (Fig. 1b).


Continue —>  The validity of spatiotemporal gait analysis using dual laser range sensors: a cross-sectional study | Archives of Physiotherapy | Full Text

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[Abstract] Effect of postural insoles on gait pattern in individuals with hemiparesis: A randomized controlled clinical trial.



Recovering the ability to walk is an important goal of physical therapy for patients who have survived cerebrovascular accident (stroke). Orthotics can provide a reduction in plantar flexion of the ankle, leading to greater stability in the stance phase of the gait cycle. Postural insoles can be used to reorganize the tone of muscle chains, which exerts an influence on postural control through correction reflexes. The aim of the present study was to perform kinematic and spatiotemporal analyses of gait in stroke survivors with hemiparesis during postural insole usage.

Material and Methods

Twenty stroke victims were randomly divided into two groups: 12 in the experimental group, who used insoles with corrective elements specifically designed for equinovarus foot, and eight in the control group, who used placebo insoles with no corrective elements. Both groups were also submitted to conventional physical therapy. The subjects were analyzed immediately following insole placement and after three months of insole usage. The SMART-D 140® system (BTS Engineering) with eight cameras sensitive to infrared light and the 32-channel SMART-D INTEGRATED WORKSTATION® were used for the three-dimensional gait evaluation.


Significant improvements were found in kinematic range of movement in the ankle and knee as well as gains in ankle dorsiflexion and knee flexion in the experimental group in comparison to the control group after three months of using the insoles.


Postural insoles offer significant benefits to stroke survivors regarding the kinematics of gait, as evidenced by gains in ankle dorsiflexion and knee flexion after three months of usage in combination with conventional physical therapy.


via Effect of postural insoles on gait pattern in individuals with hemiparesis: A randomized controlled clinical trial – Journal of Bodywork and Movement Therapies

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[Abstract] Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot


Background: Lower limb exoskeleton rehabilitation robot is a bionic robot, which is the product of the combination of medical technology and robot technology, simulating human walking movement. It can be mainly used for rehabilitation training of patients with lower limb dysfunction.

Objective: To provide an overview of recent lower limb exoskeleton rehabilitation robot and introduce their respective characteristics and development.

Method: A recent lower limb exoskeleton rehabilitation robot is divided into passive drive, pneumatic drive, hydraulic drive and motor drive. This paper reviews various representative patents related to lower limb exoskeleton rehabilitation robot. The structural characteristics and applications of the typical lower limb exoskeleton rehabilitation robots are introduced.

Results: The differences between different types of lower limb exoskeleton rehabilitation robots are compared and analyzed, and the structural characteristics are concluded. The main problems in its development are analyzed, the development trend is foreseen, and the current and future research of the patents on lower limb exoskeleton rehabilitation robot is discussed.

Conclusion: There are a lot of patents and articles about the exoskeleton rehabilitation robots, however, if these problems can be solved, such as small size, light weight and high power output are solved at the same time, the consistency with human body will be advanced, with the combination of traditional rehabilitation medicine. It will be possible to maximize the rehabilitation of the lower limbs.

Source: Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot: Ingenta Connect

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