Gait patterns are studied in terms of a gait cycle, which enables comparison of gait patterns with different gait velocities and helps clinicians identify causes of individual gait abnormalities. A gait cycle is defined as the duration between two consecutive foot contact events of the same limb. In normal gait, foot contact occurs at heel strike. It includes the stance phase in which the foot contacts the ground and the swing phase in which the foot is in the air (Figure 1).18
To detect gait deviations from normal patterns, each laboratory must collect data on a group of normal subjects and establish normative values for the measurements. In the report of kinematics and kinetics,12,19 normative data are plotted as a norm band with mean value and standard deviations. Data collected in multiple trials are plotted to compare with the norm band to identify gait abnormalities. Comparisons can also be made within a patient between barefoot and braced conditions, between different types of orthoses and assistive devices, and between preoperative and postoperative data.
APPLICATION OF GAIT ANALYSIS IN PEDIATRIC PATIENTS
Gait analysis assists in identifying specific gait deviations and the causes of the abnormalities.3 Gait deviations may be due to impairments such as muscle weakness, abnormal muscle tone, static or dynamic muscle contracture, abnormal joint position, or reduced range of motion. Gait analysis helps differentiate the patients’ primary abnormalities, secondary abnormalities, and compensatory strategies.11 It is also used to monitor the progression of neuromuscular diseases, plan surgical procedures,20–23 evaluate postoperative outcomes,24–30 recommend nonsurgical intervention,31 and assess the effects of orthoses and prostheses.32 Baseline evaluation can be compared to subsequent assessment to follow the progression of gait problems. Preoperative evaluation of complex gait abnormalities helps physicians identify multiple problems, eliminate unnecessary surgery and make a treatment plan that may involve single event multi-level surgeries.33–35 Postoperative gait analysis provides opportunities to evaluate treatment outcomes and helps the physicians to accumulate experience about the predicted and unpredicted outcomes of each surgery. A database can be generated to include gait analysis data from various stages of clinical evaluation and treatment planning. This enables retrospective research studies that quantitatively evaluate surgical outcome, investigate gait patterns of patients with a specific diagnosis, or explore new assessment tools.
Computer assisted quantitative gait analysis does not replace observational gait analysis or dictate treatment plans.11 Instead, it is a tool to help the clinical team identify and understand gait problems more objectively and accurately and therefore facilitate better treatment planning.
It is the goal of any clinical measurement to provide data with minimal error. Most errors in gait analysis are clinically acceptable and related to marker placement.36 The motion analysis community continues to work to decrease variability and error with the implementation of standardized protocols37,38 and improvements in technology. It is important for motion analysis laboratories to provide extensive training to staff and implement quality assurance programs to improve clinical gait analysis.
PRINCIPLES OF PATIENT MANAGEMENT
A key principle of management of any condition is proper identification of the “problems” and their potential causes. In the analysis of a patient’s gait, a problem list is created by systematically reviewing the deviation of each joint, in each plane, and for each phase of gait. Though opinions on management may differ, correctly defining the problem is essential in evaluating gait abnormalities.11,12 The process begins with observational gait analysis (Table 4). In patients with abnormal gait, one must first observe and identify the important deviations from normal to direct care. Gait observation typically starts in the sagittal plane with the foot contact pattern, and then moves to the knees, hips, and finally the pelvis. The order may be reversed: pelvis to foot. The sequence is repeated for the coronal and transverse planes. Stance phase problems are identified first, followed by swing phase problems. Each deviation is noted and then collated to create a problem list. Many deviations that are the focus of attention are found in the sagittal plane. For example, toe walking is usually identified in the sagittal plane.
The next step of the process is to review the clinical examination, looking for anatomic abnormalities that may cause the problem identified. Using the toe-walking example, if the clinical examination demonstrates a contracture of the calf muscles (inability to passively dorsiflex the ankle past neutral), it is one component that needs to be treated to correct the problem. However, if the passive ankle motion is normal, another abnormality (such as knee flexion in the stance phase) rather than a fixed muscle or tendon contracture of the ankle is causing the toe gait. Each problem is analyzed in this manner with specific clinical examination measurements reviewed.
Patients with gait abnormalities that cannot be clearly defined by observational gait analysis39 and clinical examination may be referred for a 3D gait analysis. While the clinical examination provides important information, it provides mostly static measurements. Dynamic measures of joint motion (kinematics and kinetics) can only be achieved with 3D gait analysis. Muscle strength can be measured manually or with a mechanical device, but it may not correlate with actual muscle function during gait. The kinetic results of 3D gait analysis provide insight into areas of muscle weakness that are functionally based. While observational gait analysis can provide a rough estimation of kinematics (angular displacement, velocity, acceleration), it is subjective in nature and dependent on the observer’s skill and experience. In addition, observational analysis provides minimal information about kinetics (force, moment, and power). In contrast, the 3D gait analysis provides more detailed and quantitative information, correcting misperceptions as well as identifying deviations (primary, secondary, or compensatory) that are subtle and may have been overlooked.
For select patients, such as those with cerebral palsy (CP), it is helpful to review EMG data collected during gait analysis. It can provide insight into abnormalities of motor control that are driven by the central nervous system. EMG aids decision-making as certain muscle procedures may be chosen over others based on the timing of muscle activity. This information cannot be obtained through observation alone.
Combining all of this information helps formulate a plan by the clinician to treat the identified gait deviations. It is critically important to remember that joints do not function in isolation. Movements at each joint are influenced by the positions and motions of other joints. For example, transverse plane problems can affect other planar joint functions. Thus, external tibial torsion may reduce ankle push-off power, or external femoral rotation may influence foot contact pattern and foot pressure. Another vital consideration is weighing the effect of each deviation on overall function. Not all deviations can be normalized; instead, only interventions that could improve gait efficiency should be recommended. Other factors to consider include the best interest of the patient and issues such as psychosocial barriers, family’s resources to provide care, and the risk-to-benefit ratio of any treatment plan.
As the number of gait deviations and the complexity of interactions increase, the potential treatment recommendations also increase. Single joint or uniplanar problems usually have simple solutions (see case study #1). Patients with complex problems, such as CP, may require multiple surgical procedures to correct their gait deviations. This can be done through a series of single-level surgeries or a single-event multilevel surgery (see case study #2).
CASE STUDY 1: INTOEING [SDC]
A healthy 12-year-old girl, presented with bilateral in-toeing (Figure 2A; See Video 5, Supplemental Digital Content 5, http://links.lww.com/COP/A15 which demonstrates case #1’s preoperative and postoperative gait videos). She complained of frequent tripping, limited endurance, and hip pain with increased activity. Her primary goals were to lessen pain and reduce tripping. In-toeing can result from abnormal rotational alignment at the pelvis, femur, tibia, or foot (or a combination of these segments). Quantifying the contribution of each anatomic area to this gait abnormality is difficult to determine from observational gait analysis alone. Therefore, the patient was referred to have a computerized gait analysis to help identify the source of the deviation and to more accurately quantify the amount of deviation.
Key Findings from Gait Analysis
The patient was found to have normal strength at all joints with manual muscle testing. Range of motion measurements showed asymmetrical femoral rotation (more internal than external) and a significant deviation from the normal value of 45 degrees:
- Femoral external rotation was 5 degrees on the right and 10 degrees on the left
- Femoral internal rotation was 75 degrees bilaterally
Her transmalleolar axes and thigh-foot angles, which measure tibial torsion, were near norms.
Transverse plane kinematics showed bilateral femoral rotation internal to norms with internal foot progression angles throughout the gait cycle (Figure 2C). Bilaterally, tibial rotation was near the external end of the normal band.
Recommendations after Motion Lab Team Review
The gait analysis demonstrated that the patient’s in-toeing was caused by increased internal femoral rotation bilaterally. A surgical recommendation was made for bilateral femoral derotational osteotomies. Once the osteotomies had healed, physical therapy focused on resuming preoperative ambulation and continuing to work on strengthening and flexibility.
Conclusions from Postoperative Gait Analysis
One year after surgery, a postoperative gait analysis was performed (Figure 2B; See Video 5, Supplemental Digital Content 5, http://links.lww.com/COP/A15 which demonstrates case #1’s preoperative and postoperative gait videos). Her postoperative clinical examination showed femoral rotation close to norms bilaterally. Kinematics showed improved femoral rotation bilaterally (close to norms) with foot progression angles within norms (Figure 2D). Her velocity improved from 89% to 105% of age-matched norms. Standardized outcome measures helped quantify functional changes and measure the patient’s overall quality of life. Pediatrics Outcomes Data Collection Instrument40 (PODCI) scores showed improvements in the pain and comfort and happiness subtests; her satisfaction with symptoms increased from 1 to 5 (top score=5). The patient’s goals were met; she no longer has pain in her hips, and her reduced incidence of tripping makes it easier to keep up with peers when participating in physical activities.
CASE STUDY 2: CEREBRAL PALSY [SDC]
An 11-year-old girl who was born prematurely with a weight of 2.27 kg and a diagnosis of left hemiplegic CP was referred for a gait evaluation (Figure 3A; See Video 6, Supplemental Digital Content 6, http://links.lww.com/COP/A16 which demonstrates case #2’s preoperative and postoperative gait videos). She walked without orthoses or an assistive device and complained of pain in her left knee after activity. She reported that she walked slower than her peers, had decreased endurance, and stumbled or fell frequently. She and her father wanted to improve her stability and decrease pain. Gait deficits are common in CP because of a muscle imbalance associated with weakness, spasticity, or decreased flexibility. In patients with complex gait deviations, observational gait analysis from a fixed perspective may be deceptive.39 Thus, computerized gait analysis helps to separate the problems in the sagittal, coronal, and transverse planes. Furthermore, it helps to determine the primary cause of the problems identified and quantify the severity of the deviations, which helps differentiate treatment options.
Key Findings from Gait Analysis
See Tables 2 and 3 for measurement key and normal values. The patient was a level two on the Gross Motor Function Classification System (GMFCS) and a level five on all distances of the Functional Mobility Scale (FMS). Clinical examination revealed a decrease in strength, selective motor control, and range of motion on her left side compared to her right and compared to normal values. Deficits of strength and selective control were most notable in her left ankle. Muscle tone was mildly increased in her left adductors, with a score of 1+ on the Modified Ashworth Scale. Muscle tone was moderately increased in her left plantar flexors, quadriceps, and hamstrings; all were rated as scores of 2 on the Modified Ashworth Scale.
The following primary gait deviations were noted on the left side:
- Increased knee flexion with stiff-knee gait: Clinical examination showed a 10-degree knee flexion contracture with limitations in the popliteal angle and moderate tone suggesting hamstring tightness and spasticity. Prone knee flexion was also limited with moderate tone and a positive Duncan Ely test suggesting rectus femoris tightness and spasticity. Kinematics showed increased knee flexion in gait with reduced knee flexion and extension arc and delayed peak knee flexion in swing (Figure 3C).
- Toe-toe gait pattern: Clinical examination revealed limitations with dorsiflexion with moderate tone suggesting tightness and spasticity of the plantar flexors. Kinematics showed a flexion loading pattern and the ankle remaining in plantar flexion through the gait cycle. The foot pressure study demonstrated a toe-toe contact pattern with pressure increased medially in the forefoot (see Figure 3D).
Recommendations after Motion Lab Team Review
A recommendation was made for a left hamstring lengthening, rectus femoris transfer, and a tendo Achilles lengthening. Since the patient had retained hardware from a previous femoral osteotomy, it was suggested that these procedures be done with her hardware removal in one surgical event. After surgery, she was casted for four weeks and weight-bearing as tolerated. After the cast was removed, she transitioned to wearing an ankle-foot orthoses (AFO). Initial physical therapy focused on strengthening, regaining range of motion, gait training, and developing a home exercise program.
Conclusions from the Postoperative Gait Analysis
One year after her surgery, a postoperative gait analysis was performed (Figure 3B; See Video 6, Supplemental Digital Content 6, http://links.lww.com/COP/A16 which demonstrates case #2’s preoperative and postoperative gait videos). The surgical goals were to decrease knee flexion in gait, increase knee arc of motion, and achieve a plantigrade gait. All three surgical goals were met. Her range of motion measurements improved at her knee and ankle. Kinematics showed improved knee extension in stance with an improved total arc of motion and improved timing. At the ankle, postoperative kinematics (Figure 3C) showed a brief first rocker, full dorsiflexion in stance, and minimal dropfoot in swing. Improved knee extension and ankle dorsiflexion were also reflected in her foot pressure study. The preoperative study showed a toe-toe foot contact pattern (Figure 3D), while the postoperative study showed a heel-toe pattern (Figure 3E).
The patient’s goals were also met. She reported decreased knee pain, improved stability, and decreased frequency of stumbling and falling. The patient now wears an orthosis only at night to help maintain flexibility. Gait velocity improved from 78% to 106% of age-matched norms. Postoperative PODCI scores showed significant improvements compared to preoperative scores in the pain and comfort and global function and symptoms subtests. The postoperative study not only evaluates the outcomes of interventions but also provides new insight to problems that were not as apparent in previous studies. Mild external rotation of her left lower leg and foot identified during the preoperative assessment was more clearly defined in the postoperative analysis. The rotation was not significant enough to warrant intervention; therefore a recommendation was made for observation and future reassessment.
Motion analysis provides an accurate quantitative assessment of gait deviations. The findings from gait analysis can be combined with other diagnostic tools such as radiologic studies to formulate an individual treatment plan. As technology continues to evolve, so too will the clinical applications of gait analysis. One of the potential applications is the computer simulation of surgery with associated predicted outcomes for various procedures. The future of gait analysis depends on not only the advance of technology but also the willingness and ability of clinicians to utilize this tool to make clinical decisions. Gait analysis is useful not only in providing objective and quantitative assessment of gait abnormalities but also in evaluating treatment outcomes. Consequently, it can enhance, expand, and optimize treatment plans for patients. It is an excellent example of evidence-based care.
The authors wish to thank the following individuals from Shriners Hospitals for Children, Portland, Oregon for their assistance: Harlan Pine, Rosemary Pierce, Patrick Do, Robert Poljak, and Dr. Larry Jacobson. We would also like to thank the two patients and their families for allowing us to use their gait lab videos and data for example cases.
1. Wren TAL, Gorton GE, Ounpuu S, et al.. Efficacy of clinical gait analysis: A systematic review. Gait & Posture. 2011; 34:149–153.
2. Rasmussen HM, Pedersen NW, Overgaard S, et al.. The use of instrumented gait analysis for individually tailored interdisciplinary interventions in children with cerebral palsy: a randomized controlled trial protocol. BMC Pediatr. 2015; 15:202.
3. Ferrari A, Brunner R, Faccioli S, et al.. Gait analysis contribution to problems identification and surgical planning in CP patients: an agreement study. Eur J Phys Rehabil Med. 2015; 51:39–48.
4. DeLuca PA, Davis RB, Ounpuu S, et al.. Alterations in surgical decision making in patients with cerebral palsy based on three-dimensional gait analysis. J Pediatr Orthop. 1997; 17:608–614.
5. Wren TAL, Otsuka NY, Bowen RE, et al.. Influence of gait analysis on decision-making for lower extremity orthopaedic surgery: baseline data from a randomized controlled trial. Gait & Posture. 2011; 34:364–369.
6. Wren TAL, Elihu KJ, Mansour S, et al.. Differences in implementation of gait analysis recommendations based on affiliation with a gait laboratory. Gait & Posture. 2013; 37:206–209.
7. Wren TA, Otsuka NY, Bowen RE, et al.. Outcomes of lower extremity orthopedic surgery in ambulatory children with cerebral palsy with and without gait analysis: results of a randomized controlled trial. Gait & Posture. 2013; 38:236–241.
8. Baker R. Gait analysis methods in rehabilitation. J Neuroengineering Rehabilitation. 2006; 3:4. Published online Mar 2, 2006. DOI: 10.1186/1743-0003-3-4 Accessed January 26, 2016.
9. Sutherland DH, Hagy JL. Measurement of gait movements from motion picture film. J Bone Joint Surg Am. 1972; 54:787–797.
12. Rose SA, Ounpuu S, DeLuca PA. Strategies for the assessment of pediatric gait in the clinical setting. Phys Ther. 1991; 71:961–980.
13. Davids JR, Gorton GE III, Aiona M, et al.. A minimum standardized gait analysis protocol: development and implementation by the Shriners Motion Analysis Laboratory network (SMALnet). Pediatric gait: a new millennium in clinical care and motion analysis technology, edited by Gerald F. Harris, Peter A. Smith, 2000 by IEEE, pages 1–7.
14. Graham HK, Harvey A, Rodda J, et al.. The functional mobility scale (FMS). J Pediatr Orthop. 2004; 24:514–520.
15. Palisano R, Rosenbaum P, Walter S, et al.. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997; 39:214–223.
16. Hislop H, Montgomery J. Daniels and Worthingham’s Muscle Testing: Techniques of Manual Examination, 6th ed. Philadelphia, PA: W.B. Saunders Company; 1995.
17. Bohannon RW, Smith MB. Interrater reliability of a Modified Ashworth Scale of muscle spasticity. Physical Therapy. 1987; 67:206–207.
18. Gage JR, DeLuca PA, Renshaw TS. Gait analysis: principle and applications with emphasis on its use in cerebral palsy. Instr Course Lect. 1996; 45:491–507.
19. Ounpuu S, Gage JR, Davis RB. Three-dimensional lower extremity joint kinetics in normal pediatric gait. J Pediatr Orthop. 1991; 11:341–349.
20. Wren TA, Lening C, Rethlefsen SA, et al.. Impact of gait analysis on correction of excessive hip internal rotation in ambulatory children with cerebral palsy: a randomized controlled trial. Dev Med Child Neurol. 2013; 55:919–925.
21. Schwartz MH, Rozumalski A, Truong W, et al.. Predicting the outcome of intramuscular psoas lengthening in children with cerebral palsy using preoperative gait data and the random forest algorithm. Gait & Posture. 2013; 37:473–479.
22. Niklasch M, Döderlein L, Klotz MC, et al.. Asymmetric pelvic and hip rotation in children with bilateral cerebral palsy: uni- or bilateral femoral derotation osteotomy? Gait & Posture. 2015; 41:670–675.
23. Schwartz MH, Rozumalski A, Novacheck TF. Femoral derotational osteotomy: surgical indications and outcomes in children with cerebral palsy. Gait & Posture. 2014; 39:778–783.
24. Aiona M, Do KP, Feng J, et al.. Comparison of rectus femoris transfer surgery done concomitant with hamstring lengthening or delayed in patients with cerebral palsy. J Pediatr Orthop. 2015. July 17. Epub ahead of print.
25. De Mattos C, Do KP, Pierce R, et al.. Comparison of hamstring transfer with hamstring lengthening in ambulatory children with cerebral palsy: further follow-up. J Child Orthop. 2014; 8:513–520.
26. Haumont T, Church C, Hager S, et al.. Flexed-knee gait in children with cerebral palsy: a 10-year follow-up study. J Child Orthop. 2013; 7:435–443.
27. Dreher T, Wolf SI, Heitzmann D, et al.. Long-term outcome of femoral derotation osteotomy in children with spastic diplegia. Gait & Posture. 2012; 36:467–470.
28. Dreher T, Wolf SI, Maier M, et al.. Long-term results after distal rectus femoris transfer as a part of multilevel surgery for the correction of stiff-knee gait in spastic diplegic cerebral palsy. J Bone Joint Surg Am. 2012; 94:e142. (1-10).
29. Dreher T, Buccoliero T, Wolf SI, et al.. Long-term results after gastrocnemius-soleus intramuscular aponeurotic recession as a part of multilevel surgery in spastic diplegic cerebral palsy. J Bone Joint Surg Am. 2012; 94:627–637.
30. Firth GB, Passmore E, Sangeux M, et al.. Multilevel surgery for equinus gait in children with spastic diplegic cerebral palsy: medium term follow-up with gait analysis. J Bone Joint Surg Am. 2013; 95:931–938.
31. Narayanan UG. Management of children with ambulatory cerebral palsy: an evidence-based review. J Pediatr Orthop. 2012; 32(Suppl 2):S172–S181.
32. Ries AJ, Novacheck TF, Schwartz MH. The efficacy of ankle-foot orthoses on improving the gait of children with diplegic cerebral palsy: a multiple outcome analysis. PM&R. 2015; 7:922–929.
33. Khouri N, Desailly E. Rectus femoris transfer in multilevel surgery: technical details and gait outcome assessment in cerebral palsy patients. Orthop Traumatol Surg Res. 2013; 99:333–340.
34. Sung KH, Chung CY, Lee KM, et al.. Long term outcome of single event multilevel surgery in spastic diplegia with flexed knee gait. Gait & Posture. 2013; 37:536–541.
35. Thomason P, Selber P, Graham HK. Single event multilevel surgery in children with bilateral spastic cerebral palsy: a 5 year prospective cohort study. Gait & Posture. 2013; 37:23–28.
36. McGinley JL, Baker R, Wolfe R, et al.. The reliability of three-dimensional kinematic gait measurements: a systematic review. Gait & Posture. 2009; 29:360–369.
37. Gorton GE, Hebert DA, Gannotti ME. Assessment of the kinematic variability among 12 motion analysis laboratories. Gait & Posture. 2009; 29:398–402.
38. Davids JR, Gorton GE, Aiona M, et al.Harris GF, Smith PA. A minimum standardized gait analysis protocol: development and implementation by the Shriners Motion Analysis Laboratory network (SMALnet). Pediatric gait: a new millennium in clinical care and motion analysis technology. Piscataway, NJ: IEEE Press; 2000:1–7.
39. Kawamura CM, de Morais Filho MC, Barreto MM, et al.. Comparison between visual and three-dimensional gait analysis in patients with spastic diplegic cerebral palsy. Gait & Posture. 2007; 25:18–24.
kinematic; kinetics; movement disorders; pediatrics; outcome measures
Supplemental Digital Content
Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved