Journal of Annals of Bioengineering

Case Study

Clinical Gait Analysis for Assessing Bilateral Lower Extremity Function: A Case Study

Nathan Edwards, Alex Stokes, Clark Dickin and Henry Wang*

Biomechanics Laboratory, School of Kinesiology, Ball State University, Muncie, IN 47306, USA

Received: 30 April 2019

Accepted: 30 May 2019

Version of Record Online: 20 June 2019


Edwards N, Stokes A, Dickin C, Wang H (2019) Clinical Gait Analysis for Assessing Bilateral Lower Extremity Function: A Case Study. J Ann Bioeng 2019(1): 01-10.

Correspondence should be addressed to
Henry Wang

DOI: 10.33513/BIOE/1901-05


Copyright © 2019 Henry Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and work is properly cited.


Clinical gait analyses allow researchers, clinicians, and patients to better understand the underlying causes of visually observed movement irregularities. This case involved a 48-year old woman with presumed femoral neuropathy to the right leg. Damage to the femoral nerve can limit quadriceps activation levels during movement. The purpose of this study was to identify bilateral lower extremity differences for the client during gait and the sit-to-stand movement and to support the use of clinical gait analysis for clinicians. A clinical gait analysis was performed using motion capture cameras and imbedded force plates to measure kinematic and kinetic variables. Hip, knee, and ankle range of motion testing and knee flexion and extension strength tests were also conducted. The client had lower right leg quadriceps and hamstring strength. The right leg also had less range of motion for all joints but most notably for knee flexion and hip external rotation. During gait, the client presented bilateral differences for ankle power production and hip and knee internal joint moments. The sit-to-stand movement appeared symmetrical, and there was no joint angle difference between limbs; however, more joint power was required by the left leg to compensate for the right leg. The client in this case suffers from right leg weakness, but she adjusts her movement patterns to maintain a “normal” appearance during movement. This clinical gait analysis provides a great example of how clinicians can benefit from the added information gained through more in-depth analysis procedures. Precisely assessing abnormalities during movement that cannot be seen requires further techniques, and clinical gait analysis can benefit the clinician, the researcher, and the patient.


Clinical Gait Analysis; Femoral Nerve; Gait; Kinematics; Kinetics; Neuropathy


Clinical gait analysis is the study of assessing gait disorders or abnormalities [1]. Gait abnormalities can occur for a variety of reasons including injuries, stroke, and neurological disorders and often compound into other musculoskeletal etiologies such as damage to bones, joints, and soft tissues resulting in pain. Over time, gait analysis has become part of many fields including medical, therapeutic, sport science, and robotics. Gait analysis in the clinical sense is used to diagnose, assess and treat disorders [2]. For example, individuals with cerebral palsy who followed recommendations from Three-Dimensional (3D) gait analysis experienced improved gait parameters [3]. Several other populations utilizing gait analysis to improve walking ability include: multiple sclerosis, Parkinson’s disease, and cerebellar ataxia [4,5].

Gait analysis provides an accurate and detailed picture of the lower body during walking. Through clinical gait analysis the effects of musculoskeletal injuries and strength and range of motion deficiencies on movement patterns can be highlighted. In order to understand gait characteristics, it is important to collect and analyze kinematic and kinetic information. The addition of lower-extremity Range of Motion (ROM) analyses along with other secondary assessments aid in the overall understanding of the factors affecting gait patterns.

Using 3D motion capture to perform kinematic and gait parameter analyses allows clinicians to obtain precise measurements of clearly seen movement irregularities in addition to irregularities that do not present visually [6]. The components of a clinical gait analysis vary based on the testing facility, but typically some form of motion capture is performed. Common measurements include temporal-spatial variables (step length, step width, cadence, stride and step behaviors, stance and swing phase timing, etc.) and kinematic variables (joint angles, joint angular velocity, segment linear velocity, etc.). Kinetic variables can be included with the use of force plates [6]. The force plates collect the Ground Reaction Force (GRF) data as the subject moves across the plates, which can be used to calculate joint power production, joint power absorption, and joint moments.

Additionally, electromyography techniques can be used to measure muscle activity occurring during movement. Apart from 3D motion capture, assessments of muscular strength and joint ROMs are often performed, providing clinicians with an understanding of the patient’s physical characteristics. Imbalances or weaknesses noted during these additional assessments are often associated with movement irregularities noted during gait analysis.

Qualitative investigations provide preliminary information about a patient’s condition; however, quantitative techniques can provide clinicians with more precision. The combination of motion capture and force plates allow researchers to analyze internal and external movement patterns that cannot be visualized. Kinetic information regarding different joints and muscles during movement increases the applicability of a gait analysis for patients. Using quantitative methods for data collection increase the repeatability and reliability of assessments, improving comparability between time points and between patients.

The present study focuses on a client with femoral neuropathy. Symptoms of femoral neuropathy include numbness or tingling in the leg, muscle weakness, shrinking of thigh muscles, and reduced sensation to touch on the affected limb. The rectus femoris, vastus medialis, vastus lateralis, and vastus intermedius are innervated by the femoral nerve, and weakness in the knee extensors and hip flexors may occur from nerve damage. Due to the importance of the quadriceps during walking, individuals who are experiencing femoral neuropathy must develop compensatory adaptations. These adaptations include full extension of the knee which compensates for weak quadriceps by not allowing an eccentric loading response in the stance phase [7,8]. Knee extension is achieved by minimizing posterior GRF in early stance phase or even keeping the GRF in front of the knee joint, controlling the foot as it lowers to the ground after foot contact, and using the hip extensors to control the femur [7,8]. Performing gait analysis on individuals with femoral neuropathy could help diagnose the effect of the condition on movement patterns and aid in rehabilitation. Therefore, the purpose of this clinical gait analysis was to measure bilateral kinematic and kinetic differences during gait and sit-to-stand movements, to assess bilateral lower extremity muscle strength and ROM differences, and to express the usefulness of clinical gait analyses for patients, clinicians, and physicians.

Materials and Methods

One female client (age: 48 years, height: 1.65 m, body mass: 63.6 kg) came to the Ball State Biomechanics Laboratory for a clinical gait analysis with additional functional movement analyses. The client experienced weakness and numbness in her right leg and had difficulty performing daily activities (e.g. walking and standing from a seated position). Previous physician assessments suggested that damage to the femoral nerve may be responsible for limitations in hip flexion and knee extension strength.

Upon the client’s arrival, all clinical gait analysis procedures were explained to the client before she changed into provided compressive clothing. Passive hip extension, hip flexion, hip internal and external rotation, ankle plantarflexion and dorsiflexion, and active knee flexion ROMs were measured for both lower extremities. Hip extension ROM was assessed with a modified-Thomas test with a digital inclinometer (The Saunders Group, INC., Chaska, MN, USA) placed on the anterior portion of the leg at the midpoint between the lateral epicondyle and the greater trochanter [9]. Hip flexion was tested using a sit-and-reach box (AssessPro Flex-Solo Tester, Gopher, Owatonna, MN, USA) securely placed against a stable wall. The client removed her shoes and sat on the ground with her feet placed against the box. With one hand on top of the other and her knees erect, the client leaned forward in a controlled manner until feeling moderate discomfort. The furthest point of hands over the top of the box was recorded for three separate trials. The sit-and-reach test is an alternative to other techniques used to measure hamstring and lumbar extensibility [10].

When measuring internal and external hip rotation, the client laid prone on the assessment table with both knees passively flexed to 90°. With the contralateral leg fully extended, the shank was moved laterally and medially until passive motion was resisted and internal and external rotations were recorded, respectively. The inclinometer was positioned between the medial malleolus and the medial tibial condyle on the medial shaft of the tibia. For all ROM assessments, measurements were recorded three times and averaged for each limb.

Ankle plantarflexion and dorsiflexion were performed with the client laying supine and the lower leg resting off the testing table. The inclinometer was placed on the midline of the heel and aligned with the third metatarsal as the ankle was moved into plantarflexion and dorsiflexion [11]. Three trials were performed for each movement, and resisted ankle motion marked the end of the ROM. To assess knee ROM, the client laid supine on an assessment table and flexed her hip to 90° before moving the knee through a full ROM [12,13]. The digital inclinometer was set on the lateral aspect of the shank, and the full ROM was recorded from full knee extension to full knee flexion.

Following the range of motion tests, a modified plug-in-gait model [14] was followed and retroreflective markers (14 mm) were placed bilaterally on the following anatomical landmarks: acromion process, anterior super iliac spine, iliac crest, posterior super iliac spine, lateral femoral condyle, medial femoral condyle, lateral malleolus, medial malleolus, second metatarsal head, fifth metatarsal head, and posterior calcaneus. Single markers were also placed on the suprasternal notch, xiphoid process, thoracic vertebrae ten, and right scapula, and four-marker clusters were attached to the lateral aspect of the right and left thighs and lateral aspect of the right and left shanks. Nine motion capture cameras collecting at 100 Hz (5 Vantage and 4 Vero, VICON Inc., Denver, CO, USA) were used to collect kinematic data during walking and sit-to-stand trials. These movement trials were performed on a 10 m long platform, and three imbedded force plates (Model ORG-7-2000, Advanced Mechanical Technologies Inc., Watertown, MA, USA) recorded GRF data during the movement tasks (Figure 1). For the walking trials, the client walked at a self-selected preferred pace. For the sit-to-stand trials, the client began in a seated position on a chair with a height corresponding to 90 degrees of knee flexion and was instructed to stand up without using her arms to assist the movement. Each of the client’s feet were placed on separate force plates during the sit-to-stand trails.


Figure 1: The testing facility used to conduct the clinical gait analysis. Pictured is the 10 m walking platform, three imbedded force plates, and the nine-camera motion capture system.

Bilateral isometric knee extension and knee flexion strength were tested with a Cybex dynamometer (Computer Sports Medicine Inc., Stoughton, MA, USA). Three Maximum Voluntary isometric Contractions (MVC) were held for three seconds and each trial was separated by one minute of rest. Collected data were processed using VICON Nexus (Version 2.6.1, VICON Inc., Denver, CO, USA) and Visual 3D (Version 6, C-Motion, Germantown, MD, USA).


Anthropometric measurements revealed that the client’s left leg was 2.5 cm longer than her right leg. Strength assessments indicated bilateral strength differences for knee extension (left: 127 N*m-1; right: 91 N*m-1) and knee flexion (left: 61 N*m-1; right: 45 N*m-1), as well as bilateral ROM differences during ROM assessments (Table 1). Specifically, the left limb had greater hip extension ROM, hip internal and external ROMs, and knee flexion ROM than those of the right limb.

  Left Right
Hip Extension 30° 25°
Hip Internal Rotation 50° 45°
Hip External Rotation 60° 38°*
Hip Flexion 74° 75°
Knee ROM 121° 113°*
Ankle Plantarflexion 29° 23°
Ankle Dorsiflexion 28° 24°
*Denotes a difference > 7 degrees between left and right sides; ROM = Range of Motion.

Table 1: Client’s joint Range of Motion (ROM) measures for the lower extremity.

During gait, the client walked at a preferred speed of 0.83 m/s. Her left and right step lengths were 0.60 ± 0.06 m and 0.66 ± 0.05 m, respectively. The single limb stance time was longer for the left leg than the right leg (0.96 s and 0.90 s, respectively). Bilateral comparisons of average joint angles during gait revealed that the client reached peak knee flexion earlier in the right leg than the left leg. Additionally, the right lower extremity had more ankle dorsiflexion and maintained dorsiflexion through the end of the stance phase upon toe-off (Figure 2). Figure 2 shows the client’s joint kinematics during a sample gait cycle. In the figure 2, normative kinematic data for the ankle, knee, hip and pelvis were also provided for comparison purpose [15]. Differences between the left and right limbs in gait mechanics were further revealed through kinetic analysis of joint moment and power. It was discovered that the largest differences in joint moments between the left and right limbs occurred in the sagittal plane (Table 2). Specifically, the left limb produced greater knee extension moment and ankle plantarflexion moment than those of the right limb. It was also discovered that the left limb contributed more hip and knee power absorption during the stance (Figure 3) and greater ankle power production during the late stance (Figure 4) than those of the right limb.


Sagittal Plane




Internal Joint Moments






Hip Extension

0.26 ± 0.12

0.38 ± 0.07

0.62 ± 0.03

0.71 ± 0.05

Hip Flexion

-0.64 ± 0.03

-0.77 ± 0.22

-0.37 ± 0.06

-0.34 ± 0.06

Knee Extension

0.19 ± 0.04

0.14 ± 0.01

0.93 ± 0.02

0.86 ± 0.03

Knee Flexion

-0.46 ± 0.05

-0.32 ± 0.10

-0.14 ± 0.02

-0.09 ± 0.06

Ankle Plantarflexion

1.33 ± 0.09

1.13 ± 0.33

0.30 ± 0.03

0.34 ± 0.02

Ankle Dorsiflexion

-0.20 ± 0.04

-0.12 ± 0.02

-0.21 ± 0.01

-0.12 ± 0.02


Frontal Plane




Internal Joint Moments






Hip Abduction

0.93 ± 0.15

0.98 ± 0.03

0.26 ± 0.08

0.34 ± 0.06

Hip Adduction

-0.03 ± 0.07

-0.02 ± 0.01

-0.12 ± 0.03

-0.01 ± 0.01

Knee Abduction

0.36 ± 0.13

0.37 ± 0.02

0.04 ± 0.03

0.06 ± 0.02

Knee Adduction

-0.08 ± 0.09

-0.04 ± 0.02

-0.20 ± 0.02

-0.14 ± 0.02

Ankle Eversion

0.02 ± 0.02

0.02 ± 0.01

0.05 ± 0.00

0.02 ± 0.01

Ankle Inversion

-0.46 ± 0.15

-0.50 ± 0.02

-0.12 ± 0.01

-0.14 ± 0.02

Table 2: Peak hip, knee, and ankle joint moments (Mean ± SD) during gait and sit-to-stand.

Note: Highlighted boxes indicates >10 N*M*kg-1 difference between left and right side for internal joint moments.


Figure 2: Joint angles of the pelvis, hip, knee, and ankle normalized to the gait cycle. The first column represents sagittal plane motion, the second column represents frontal plane motion, and the third column represents transverse plane motion. For sagittal plane motion, flexion is positive, and extension is negative. For frontal plane motion, adduction is positive, and abduction is negative. For transverse plane motion, internal rotation is positive, and external rotation is negative.


Figure 3: Peak joint power of absorption during gait.


Figure 4: Peak joint power production during gait.

During the sit-to-stand movement, differences in peak joint angles appeared to be minimal (Mean ± SD; left hip: 105° ± 1°, right hip: 105° ± 1°; left knee: 91° ± 0°, right knee: 92° ± 1°; left ankle: 23° ± 1°, right ankle: 22° ± 1°). However, differences in joint moment and power were exhibited between the two limbs. Specifically, the left limb produced greater knee extension moment than the right limb, while the right limb produced greater hip extension and adduction moments than those of the left limb (Table 2). In addition, the left limb contributed more knee power production than that of the right limb (Figure 5). Finally, the right hip produced more power production than the left hip (Figure 5).


Figure 5: Peak joint power during sit-to-stand.


The purpose of this clinical gait analysis was to measure bilateral lower extremity kinematic and kinetic differences during gait and the sit-to-stand movement. Muscular strength and joint ROMs were also assessed for the lower extremities. The client presented consistent decreases in ROM for the right lower extremity, most notably for hip rotation and knee flexion. Furthermore, the client’s right knee extension strength was 28% weaker than the left knee. This discrepancy suggests a weakness in the quadriceps muscles of the right leg. A similar relationship was found between right and left knee flexion strength (right leg was 26% weaker), which implies a weaker right hamstring strength. These imbalances may be results from less use of the right leg during the client’s regular ambulation and general movement.

The quality of the movement performed in the form of walking can be assessed by examining the kinematics of the movement and kinetics of the lower-extremity joints. Kinematically, fast walking speed and symmetrical gait patterns are considered good qualities of gait. Kinetically, greater lower-extremity joint moments and powers produce the better presentation of the gait kinematics such as fast walking speed. An internal joint moment represents the torque occurring within the joint that is resisting an external torque. An internal joint moment can be associated with the degree of muscle activation occurring in the same joint that results in the corresponding joint movement [2]. Knowing the internal joint moments allows clinicians to understand how force and limb positioning interact within the joint. Furthermore, joint power often correlates with the strength of the muscle groups that produce that power (i.e., weak plantarflexors may correspond with low ankle power) [2]. Joint power is often expressed as power production and power absorption. These terms are differentiated by the type of muscle action occurring as the joint moves. Power production corresponds with concentric muscle actions, while power absorption corresponds with eccentric muscle actions.

In this clinical gait analysis, the client’s walking speed was 60% slower than a typical preferred walking speed (1.39 m/s) for women in their 40 s [16]. Step length for one leg often indicates the level of balance and confidence one has for the opposite leg. In this case, right leg step length was longer than left leg step length insinuating that the client was more confident and more balanced when standing on her left leg. This asymmetry in step length could be largely attributed to the strength differences between the two limbs. The right limb possessed a weaker knee extensor and flexor than the left limb, thus, during normal walking, the right knee yielded a smaller knee extension moment (26% less) as well as knee power absorption (41% less) than those of the left knee. In this study, we did not measure the strength of the ankle and hip joints, however, we noticed that the right ankle elicited less plantarflexion moment (15% less) and power production (39% less) than those of the left ankle. This implied that the right ankle might also have been affected by the neural condition and possessed a lower strength than the left side. The reduced contribution of the right knee and ankle to the walking movement due to a deficit in joint strength could explain the partial compensation from the right hip, which increased its extension moment by 46% more than that of the left hip.

The client also presented more right ankle dorsiflexion throughout the gait cycle and less right ankle plantarflexion near toe-off (Figure 2). This imbalance between the right and left ankles is likely because of right ankle muscle weakness as well as 6° less passive plantarflexion ROM (Table 1). The ankle ROM differences might have affected the plantarflexion moment during gait and limited ankle power production. The client’s compensatory gait pattern has distinct markers represented in the joint kinematic graphs in figure 2. For example, the timing of peak knee flexion and peak plantarflexion occur earlier in the right leg than the left leg, the right leg was more abducted during the stance phase, and the right side of the pelvis was more posteriorly rotated during this phase as well. The combined right hip abduction and right-side pelvis posterior rotation suggests that the client placed more weight on her left leg during the stance phase compared to the stance phase of the opposite limb. The increase in pelvic rotation angle after toe-off may also indicate that she rotated her pelvis forward to continue forward motion. Because these are bilateral comparisons, inferences are relative to the contralateral limb. The gait of the client with a supposed femoral neuropathy requires more pelvis rotation in order to maintain a consistent walking pattern.

The sit-to-stand movement is a typical daily activity requiring adequate lower-extremity joint strength. Analyzing the biomechanics of the sit-to-stand allows clinicians and orthopedic surgeons to quantify and better understand the effects of surgical interventions on movement performance of daily activities [17,18]. In this study, we asked the client to stand up from a sitting position at a self-selected pace while we examined the movement quality and determined the influence of the neural condition on the performance. There were no visual bilateral differences in the sit-to-stand movement, and these visual assessments were confirmed by the similar joint angle measurements. However, we discovered that the right limb applied 8% less knee extension moment and 32% less knee power production than those of the left limb. On the contrary, the right limb elicited 11% more hip extension moment and 7% more hip power production than those of the left limb. The greater right hip contribution appeared to be a compensatory mechanism used by the client to offset the right knee weakness. The increased right hip and decreased right knee extension moments reflected an altered muscular requirement to achieve symmetrical movement patterns in sit-to-stand. Finally, the total power produced by the left limb was greater (14% more) than that of the right limb, this imbalance of power production between limbs implied that the left limb was favored by the client and was used to offset the right limb weakness during sit-to-stand, a typical daily activity.

Performing clinical gait analyses in laboratory settings has numerous benefits, including being conducted in a controlled and normalized environment, having access to precise equipment, and being able to incorporate multiple assessments. However, laboratory settings are sometime impractical for certain populations and other forms of data collection are more appropriate. As an alternative to laboratory-based analyses, the introduction of wearable technology can increase the time period of gait monitoring, can be more convenient, and can improve the ability for researchers to use different environments for data collection. Within clinical gait analysis, triaxial accelerometers have been used to successfully measure kinematic and spatial-temporal variables [19,20]. Because of testing environment flexibility provided by wearable technology, researchers have begun to expand research beyond the laboratory. The accuracy of wearable technology must be analyzed prior to its use in definitive research. In one case, step counts recorded by commercially available physical activity trackers were compared with laboratory collected step count data, and none of the physical activity trackers reached the industry standard for accuracy [21]. However, the application of machine learning algorithms to data from a triaxial accelerometer has potential for improving the interpretation data collected outside of a laboratory [22]. As an additional form of wearable technology, plantar pressure insoles can be used as a less expensive alternative to force plates to measure GRFs. This form of insole has been used to accurately assess GRF during gait [23] and during a dynamic balance task [24]. Wearable technology may influence research participation and reduce environmental limitations, but laboratory based clinical gait analyses should not be wholly abandoned. Using exclusively wearable technology limits researcher’s ability to quantify joint kinematic and kinetic data. In the present case study, the collected kinetic data aided in the interpretation of movement patterns and muscular imbalances.

In conclusion, although movement patterns remained generally symmetrical between the two limbs, joint positioning, joint power, and internal joint moments were different between legs. Strengthening the right limb would be beneficial for equalizing the differences between legs, and there are some clear impairments in motor function that might be in part explained by damage to the right femoral nerve. Future follow-up testing might include assessments of nerve conduction velocity and detailed analysis of other functional movements looking more closely at the quality of joint control and coordination. These assessments might help better discover how the impairments in muscular strength and percent activation level would impact tasks performed in a more challenging environment (e.g. regaining and maintaining balance when gait is perturbed). Wearable technology may be an avenue allowing for additional data collection in different environments outside of the laboratory.


Observing a client’s gait can provide a preliminary understanding of movement patterns and bilateral differences. However, using motion capture and force plate technology can improve the depth of gait analysis. In the present case, the client presented potential femoral neuropathy in the right lower extremity. Through a clinical gait and functional movement analysis, it was determined that the client was able to maintain ‘typical’ movement patterns because of bilaterally imbalanced levels of power production and internal joint moments. Differences between knee and hip joint moments correspond with decreased knee extensor muscles capacity, which supports the suggested femoral neuropathy.


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