Utilization of motion analysis to quantify gait pathologies in spine surgery

Summary

Instrumented motion analysis is a method more and more often encountered in world literature with regards to objective gait analysis. Although it is a very modern and potentially beneficial method, it is burdened by its complexity, which results in its misunderstanding and infrequent use. Furthermore, there is a paucity of literature reviewing its individual components and summarizing gait characteristics in specific pathologies of the musculoskeletal system. Spine pathologies are amongst the most common diagnoses affecting physiological gait, making them a common target for motion analysis. Although in some cases we can recognize specific motion patterns of individual spine diagnoses at first glance, alteration of specific components of the gait cycle can only be determined via instrumented gait analysis. The following review aims to familiarize clinicians with this method, as they encounter patients presenting with spine pathologies on a daily basis. The first section introduces the basic of gait physiology including the gait cycle and its components. The second section describes the individual components of instrumented motion analysis and the tools it uses. Finally, it concludes by describing motion patterns of the most common spine pathologies, which are based on patient analysis in the authors` own laboratory complemented by a review of world literature.

Keywords:

Spine – gait – degeneration – motion analysis – gait cycle – instrumented measurement

This is an unauthorised machine translation into English made using the DeepL Translate Pro translator. The editors do not guarantee that the content of the article corresponds fully to the original language version.

Introduction

Gait disorders are among the most common reasons why patients with a spondylogenic diagnosis seek medical attention. Although this is a symptom that is entirely typical for spinal surgery, our options for its objective assessment are relatively limited. Clinicians are often limited to basic questions regarding the claudication interval or the localization of pain during walking, which are, to a certain extent, subjectively biased. Furthermore, the situation is complicated by the fact that few clinicians possess knowledge of the physiology and pathophysiology of the gait cycle. The effort to find a tool that would enable a detailed analysis of gait led to the development of instrumented motion analysis, which utilizes modern technology for a comprehensive examination of the patient. This is a tool that can be used in the diagnosis of movement disorders, to localize problematic anatomical regions, enabling targeted physical therapy, and finally to evaluate the therapeutic success of both surgical and non-surgical methods. The following overview aims to summarize the fundamentals of gait physiology, describe the basic methods of modern motion analysis, and characterize the most common pathological gait patterns encountered in spinal surgery.

 

Physiology of Gait

Definition of gait, gait cycle, individual phases of the gait cycle

Walking can be defined as the rhythmic movements of the limbs and trunk that enable locomotion in an upright position. Although the walking automatism is a reflex activity at the spinal level of the central nervous system, most authors consider human walking to be the result of higher nervous activity in the subcortical and cortical centers of the telencephalon [1]. The process itself is the result of coordination between the cortical region of the brain, the subcortical region of the brain, the spinal cord, the peripheral nerves, and the musculoskeletal system, which provides feedback to the cerebral cortex via afferent nerve fibers. The result is alternating movements of the trunk and limbs, which create a repetitive pattern known as the gait cycle. We define the gait cycle as the time interval between any two identical events during walking, e.g., the time span from heel contact with the ground to the heel of the same limb making contact with the ground again [2]. Depending on the activity being performed, we distinguish between the stance phase and the swing phase during the gait cycle. The stance phase is defined by the presence of the sole of the foot on the ground, which represents the transfer of the individual’s weight to the ground surface. It begins with the heel making contact with the ground and ends with the toes pushing off the ground. This part naturally accounts for about 60% of the walking cycle. The swing phase is defined by the sole of the foot being off the ground, which represents the transfer of the individual’s weight through space and physiologically accounts for 40% of the walking cycle.

During both phases, eight events are classically described as occurring in a defined sequence. From the perspective of gait, we describe the time interval during which both lower limbs are in contact with the ground (double-support phase) and the time interval during which only one lower limb is in contact with the ground (single-support phase) (Fig. 1) [3].

 

Standing phase

Heel strike (initial contact) –⁠ the first contact of the heel with the ground (double-support phase).

Full-foot strike (foot flat / loading response) –⁠ the entire sole comes into contact with the ground (single-support phase).

Midstance phase –⁠ the contralateral lower limb enters the swing phase, and the center of gravity gradually shifts forward (single-support phase).

Heel-off (heel-off / terminal stance) –⁠ the sole undergoes dorsiflexion and the heel pushes off the ground (single-support phase).

Toe-off (pre-swing) –⁠ the toe pushes off and the foot loses contact with the ground (double-support phase).

 

Swing phase

Acceleration (acceleration / initial swing) –⁠ the hip flexors are activated, accelerating the forward movement of the lower limb (single-support phase).

Midswing –⁠ the swinging lower limb moves over the stationary lower limb, which is in a central stance (single-support phase).

Deceleration –⁠ muscles are activated to slow down the movement of the swinging lower limb and prepare it for heel strike (single-support phase).

 

Development of Walking

The first sign of movement resembling walking is so-called reflex walking, which consists of alternating flexion and extension of the lower limbs when placed on a hard surface. It is present in newborns and infants up to 3 months of age, then disappears and reappears before the onset of full walking [4]. According to the WHO, independent walking appears between 8.2 and 17.6 months of age; however, this involves flat-footed walking without heel strike, which appears around 18 months of age. Later, walking matures with the involvement of trunk and upper limb movements in typical coordinated motions and an increase in stability. Adult-type walking can generally be observed around the age of 7 [5].

 

Gait Assessment in Clinical Practice

Early assessment methods relied on the relatively limited equipment available in a standard medical clinic and consisted primarily of observational gait analysis. Depending on the specified time and distance, we distinguish between 3-, 6-, or 10-minute gait tests, or 10-, 15-, or 30-meter gait tests [6,7]. Their advantages include validation due to long-term use, easily interpretable results, and simplicity of administration. However, a disadvantage is that the only output is walking speed. For this reason, gait analysis has been incorporated over the years into comprehensive scales most commonly used for neurodegenerative diagnoses, in which gait disturbance is one of the main clinical symptoms. Among the most commonly used are the Unified Parkinson’s Disease Rating Scale or the Scale for the Rating and Assessment of Ataxia [8]. Here, however, gait assessment is only one of many evaluated components. To enable a more comprehensive assessment of gait, instrumented gait analysis has been developed over the years. Depending on the modality being assessed, we distinguish three basic classes of instrumented motion analysis [9].

 

Kinematic Analysis

Definition: quantifies movement without evaluating movement forces. It assesses how the gait cycle proceeds and measures its components. It also analyzes the speed, acceleration, symmetry, and range of motion of individual anatomical segments.

 

Subtypes of kinematic analysis

Spatio-temporal analysis: evaluates gait cycle parameters—stride length, stride width, cadence, walking speed, etc.

Segmental and trunk analysis: evaluates the movement of selected anatomical segments and the center of mass (COM) of the trunk—e.g., pelvic tilt, trunk tilts and sway, shifts in the center of mass.

Joint analysis: evaluates the speed, range, and acceleration of movement in individual joints—e.g., range of motion (ROM), angular acceleration, angular velocity.

Coordination/symmetry analysis: evaluates whether the limbs and individual anatomical segments move in a coordinated manner, comparing the right and left sides.

 

Measurement tools

Optoelectronic instruments/video systems: use optical camera systems to detect optical markers or anatomical body parts.

3D analysis: uses a multi-camera system (6–12 cameras) positioned along all three basic planes (coronal, sagittal, axial). The cameras can track optical markers placed on the surface of defined anatomical landmarks on the individual to construct motion trajectories, as in a so-called marker-based system (e.g., Qualisys [Gothenburg, Sweden], Vicon [Oxford, UK], etc.). The second option is to use computer vision or AI to estimate the positions of individual body parts directly from a video recording of the movement as a so-called markerless system (e.g., Theia3D [Toronto, Canada], OpenPose [Carnegie Mellon University, Pittsburgh, PA, USA], etc.). The advantage is the comprehensiveness and accuracy of the data obtained from all three planes of motion, to which kinetic or EMG analysis data can be integrated. The disadvantages include the need for a specialized laboratory, high cost, the need for calibration, and human error in placing optical markers (Fig. 2).

2D analysis: uses a standard camera (e.g., a phone) or a high-speed camera system to analyze motion in only one plane (most commonly the sagittal or coronal plane). Cameras are positioned perpendicular to the plane of motion being examined and perform motion analysis with or without the use of optical markers (e.g., Dartfish [Fribourg, Switzerland], Kinovea [France]). The advantages include simplicity and the speed of data acquisition, low cost, and the ability to perform measurements outside a specialized laboratory. The disadvantages include the absence of data for the remaining two planes of motion, the inability to evaluate complex multiplanar movements, and the presence of parallax shift error (variation in measurements depending on the angle of the camera relative to the subject being evaluated).

Inertial/magnetic systems: use motion-detecting sensors that are placed directly on the person being examined.

Accelerometers: measure linear acceleration along one or more axes of motion, thereby detecting changes in direction and speed of the body part on which they are placed. We use the acquired data to calculate cadence and temporal parameters of the gait cycle (gait cycle duration, stance phase duration, swing phase duration, etc.).

Gyroscopes: measure angular velocity in three axes, thereby enabling the capture of angular velocity and movement in joints, or defined events of the gait cycle.

Inertial measurement units: these are systems that combine accelerometers and gyroscopes, thereby obtaining information on linear acceleration (translation) and angular velocity (rotation). The result is comprehensive motion tracking, which enables gait cycle reconstruction and 3D joint motion analysis.

 

Kinetic analysis

Definition: quantifies the forces and torques that initiate movement, while simultaneously evaluating the force effects of movement on the ground and individual parts of the human body.

 

Subtypes of Kinetic Analysis

Analysis of ground reaction forces (GRF): Upon impact, the sole of the foot exerts a certain force on the ground. According to Newton’s Third Law, the ground then exerts an equal and opposite force on the sole (ground reaction force). The resulting evaluated parameters are curves of the individual GRF components, where, based on the orientation of the force, we distinguish the vertical component of GRF (axial body load), the anteroposterior component of GRF (propulsive/braking forces), and the mediolateral component of GRF (balance maintenance). It is also possible to analyze force impulse, the symmetry of step forces in the dominant and non-dominant limbs, or the center of pressure (COP) of the ground reaction force vector.

Foot pressure distribution analysis: evaluates the distribution and differences in pressure forces on the sole of the foot during the stance phase of the gait cycle. The evaluated parameters include peak foot pressure, foot loading pattern, and regional pressure assessment (heel, metatarsals, toes).

Joint kinetics: utilizes a combination of GRF, kinematic data, and anthropometric data (length and mass of anatomical segments) to estimate forces and moments within joints. The output includes forces acting within the joint in a specific anatomical plane, moments within the joint, joint reaction forces, etc.

 

Measurement tools

Force sensors: are typically integrated into flat force plates, which allow for the capture of GRF when the sole strikes the platform and record them in the form of force-time curves. Another option is the integration of force sensors into a treadmill, which enables the continuous generation of force-time curves over multiple gait cycles.

Pressure sensors: These can also take the form of pressure platforms that measure foot contact while wearing shoes or barefoot. However, they can also be built into special shoe inserts that measure pressure distribution on the foot during everyday activities.

 

EMG analysis

Definition: measures the electrical activity of muscles, thereby allowing the assessment of when and how strongly muscle contraction occurs during the gait cycle. It allows for the evaluation of the timing of muscle contraction, muscle coordination, and muscle compensation mechanisms.

 

Subtypes of EMG analysis

Qualitative EMG analysis: evaluates the activation timing and coordination of individual muscles or muscle groups during the various phases of the gait cycle. It is used to assess muscle synergy and the timing of agonist/antagonist activation throughout the gait cycle. The following parameters are evaluated: activation time, deactivation time, the time interval between activation and deactivation, and contraction patterns.

Quantitative EMG analysis: evaluates EMG amplitude and EMG intensity using root mean square (RMS). It is used for the indirect assessment of muscle effort, muscle fatigue, and muscle work during walking.

EMG modeling: links EMG measurements with kinematic and kinetic parameters to estimate muscle force, forces and moments acting on joints, or energy expenditure during walking.

 

Measurement tools

Surface EMG: This is the most commonly used tool for EMG analysis of movement due to its non-invasive nature. It consists of adhesive electrodes placed over the target muscle to measure the action potentials of its motor units. Its disadvantages include difficulty in capturing action potentials from deep muscles and susceptibility to motion artifacts.

Needle EMG: This method is used infrequently due to its invasive nature. It consists of thin needle electrodes that are inserted through the skin into the muscle fibers of the muscles being examined and measure the action potential of their motor units. An advantage is the ability to assess small or deep-seated muscles. A disadvantage is its invasiveness, which generally precludes repeated measurements.

Some assessment modalities (2D kinematic analysis, kinetic analysis using pressure-sensing insoles, surface EMG, etc.) allow for testing in real-world settings (home activities, sports environments, hospital wards). Comprehensive analyses that utilize integrated systems of kinematic, kinetic, and EMG analysis, however, require testing in specialized laboratories (Fig. 3), with walking performed either across the laboratory floor or on a treadmill. Individual analyses and tools can be used separately or in combinations depending on the available equipment and the specific problem being addressed. A long-standing problem with instrumented analyses was the interpretation of results, which were often a mix of various analytical methods and which, moreover, could show deviations between individual laboratories due to differing instrument calibration. Different examination protocols and the human factor played a role here and continue to do so, e.g., when applying optical markers over defined anatomical points. The situation was further complicated by the absence of a standardized examination, with each laboratory typically creating its own control group against which it then compared the study sample. A significant advance was the development of validated scoring systems, which generally simplify the interpretation of motion analysis into a single value. The longest-used system is the Gillette Gait Index, which combines 16 spatial-kinematic parameters to yield a single value. This value can then be used to compare patients with physiological and non-physiological gait [10]. However, a problem remained in that the index was primarily designed to analyze the gait of pediatric patients with cerebral palsy, not adult patients. Furthermore, each laboratory had to create its own control group of healthy individuals. In 2008, Schwartz and Rozumalski presented the Gait Deviation Index in their publication * *, which was developed based on more than 6,000 gait cycles and derived from 15 spatial kinematic variables [11]. The index is reported as a value ≤ 100, where individuals with a score of 100 have a completely physiological gait, and a decrease of 10 points corresponds to one standard deviation of kinesiological parameters from normative values. The most recent of the commonly used scoring systems is the Gait Profile Score, first described in 2009. This is presented as a single value derived from nine kinematic parameters that form the patient’s movement analysis profile (Fig. 4) [12]. An advantage is the ability to analyze individual components of the patient’s movement profile to determine which anatomical region is the primary source of pathological gait (Fig. 5). Using the same methodology, Ropars developed the EMG-Profile score, which utilizes EMG data obtained from selected muscle groups instead of kinematic data [13].

 

The Relationship Between the Spine and Gait

The spinal column consists of bony, ligamentous, muscular, and nervous components. The bony component consists of the vertebrae, which, together with the skull, form the axial skeleton. At the cranial end, the first and second vertebrae are connected to the skull bone via the so-called cervicocranial junction; caudally, the sacrum is connected to the pelvic ring via the sacroiliac joint. The individual vertebrae are connected to one another by a complex system of articular and ligamentous connections, which ultimately form a functional unit with the spine. These connections include symphysis (intervertebral discs), syndesmosis (facet joints), and virtually immobile synchondrosis (sacral vertebrae). The complex of two vertebrae and an intervertebral disc then forms a so-called spinal motion segment; under normal circumstances, there are 24 of these, and their movements combine to form overall spinal motion. Stability to the entire system is provided by a complex of short and long spinal ligaments that prevent excessive movement of individual segments. The muscular component of the spine is represented by the system of deep back muscles located in the deepest—fourth—layer. Nervous tissue is represented by the spinal cord and the spinal nerve roots extending from it, whose posterior branches (radices dorsales) provide innervation to the deep back muscles and whose anterior branches (radices ventrales) provide innervation to the limbs and the ventral portion of the trunk. All four tissue elements contribute to the postural function of the spine, which under physiological conditions enables effective standing and walking. A prerequisite for effective standing and walking is balance between the regions of the so-called spinal curve. This is characterized by a lordotic posture of the highly mobile regions of the spine (cervical and lumbar) and a kyphotic posture of the rigid regions of the spine (thoracic and sacral). When this balance is maintained, the patient is within the so-called cone of effective posture, described by Jean Dubousset in the 1970s [14]. This is an advantageous situation for the patient, as they do not need to exert increased muscular effort to maintain an upright posture. If the balance between the individual regions of the spinal curve is disrupted, the individual’s posture shifts outside the cone of efficiency. The result is increased work by the paravertebral muscles, leading to their faster fatigue, localized back pain, and the need to change position to allow for muscle relaxation. During walking itself, the swaying motion of the pelvis is transmitted to the mobile lumbar segment of the spinal column, which then performs cyclic flexion and extension to compensate for the shifting center of gravity of the trunk. The coordination of pelvic and spinal movements is referred to as the lumbopelvic rhythm [15].

 

Movement analysis in spondylogenic pathologies

Spinal disorders affect gait in various ways. Gait disturbances can result from musculoskeletal or neurogenic conditions, or from hyperalgesia. Among the most common neurogenic causes are degenerative spinal canal stenosis and cervical myelopathy syndrome. One of the common musculoskeletal causes is sacroiliac joint dysfunction. All of the conditions mentioned typically involve a significant component of pain, which further exacerbates the gait disturbance. The basic characteristics of the gait analysis for each pathological condition are summarized in Table 1.

 

Degenerative lumbar stenosis

Degenerative lumbar stenosis is a condition characterized by progressive narrowing of the cross-sectional area of the spinal canal, most commonly affecting patients over the age of 65 [16]. A typical clinical manifestation is neurogenic pseudoclaudication, characterized by paresthesia, dysesthesia, and cramping pain occurring during walking with a progressively shortening claudication interval [17]. The clinical picture is typically dominated by the symmetry of symptoms, which may be accompanied by radicular syndrome and a typical relief posture in a forward-leaning position [18]. Kinematically, step length is usually shortened, as demonstrated in studies by Sun, Fujita, and our research group [19–21]. The reason is likely instability caused by a shift of the center of gravity ventrally in an attempt to achieve a relieving forward lean, which leads to a shortening of the swing phase of the gait cycle and consequently to shorter steps. At the same time, step width tends to increase, as demonstrated by Kim et al., among others, who attribute this finding to the presence of trunk sway, which occurs in patients with neurogenic pseudoclaudication [22,23]. Furthermore, the swing phase of the gait cycle and single-limb support are typically shortened, with a correspondingly prolonged stance phase and double-limb support. These are parameters closely related to step length and associated with the dynamic shift of the trunk’s center of gravity, as noted by Loske et al. [24]. At the same time, walking speed and cadence tend to be reduced, while step duration is longer. An interesting explanation for these parameters is provided by the study by Conrad et al., which attributes the overall slowing to impaired proprioception resulting from compression of the distal roots of the cauda equina innervating the acral portion of the lower limbs [25]. The result is impaired movement correction, which is particularly critical when walking on uneven surfaces, requiring greater concentration while walking and generally slowing it down. In segmental and trunk analysis, the pelvic, hip, and ankle regions are most commonly affected. In the pelvic region, we described increased pelvic rigidity with a reduced range of craniocaudal and rotational motion compared to the control group [21]. A similar finding was also described by Bumann et al., who explain the phenomenon as an effort to prevent excessive lumbar extension, which exacerbates neurogenic pseudoclaudication, leading to fixation of the pelvic tilt, including the sacrum [26]. In the hip region, a limitation of hip joint extension is often observed; the hip is maintained in semiflexion during walking to compensate for the ventral shift of the trunk’s center of gravity [27]. In the ankle region, plantar flexion is typically limited, which is usually a consequence of a shorter stride that prevents maximum push-off. Kinetic parameters using pressure plates were evaluated in a study by Weie et al., which described more pronounced pressure changes in the forefoot during the stance phase with a faster shift of the center of gravity from the rear half of the sole to the front due to walking in a forward-leaning posture [28]. A number of authors then investigated electromyographic differences between patients with lumbar stenosis and a control group. The studies by Nuesche et al. and Urbanschitz et al. both described increased activity in the paravertebral muscles and in the gluteus medius and gluteus minimus muscles; the study by Kim et al. further supplemented these findings with increased activity in the tensor fasciae latae muscle [22,29,30]. The authors explain the increased activity of the paravertebral muscles by a more pronounced tendency toward non-physiological forward flexion, the need to stabilize the spinal segments against painful movements, and finally, their fatty atrophy, which requires greater activity of the remaining muscle fibers. Excessive activity of the gluteus medius muscle is then linked to increased pelvic rigidity and also to a wide-based gait in the presence of relative instability.

 

Cervical myelopathy

Cervical myelopathy syndrome is a set of symptoms resulting from spinal cord compression due to a narrow spinal canal. It most commonly occurs as a result of chronic degenerative changes characteristic of spondylosis or ossification of the posterior longitudinal ligament [31]. This results in symptoms that include paresthesia of the extremities, spasticity, sensorimotor atrophy, sphincter dysfunction, and, above all, gait disturbance [32]. Gait disturbance arises from a combination of sensory impairment in the lower extremities, spasticity, ataxia, and motor weakness. Kinematics analysis shows characteristics similar to those seen in degenerative stenosis. Typically, step length is reduced and step width is increased, which Malone et al. and Maezawa et al. attribute to impaired plantar proprioception, which forces patients to walk with a wider base, and impaired stability, particularly when standing on one leg [33,34]. Once again, the swing phase of the gait cycle and single-limb support are shortened, while the stance phase and double-limb support are prolonged—a phenomenon first described by Kuhtz-Buschbeck [35]. Both findings demonstrate patients’ preference for standing with support from both legs, as they have significantly impaired sensory afferentation. At the same time, walking speed and, consequently, cadence are also reduced, as demonstrated by most studies evaluating these parameters [33–35]. The explanation lies again in impaired sensation in the lower limbs, but also in spasticity, which slows the rhythm of flexor and extensor alternation and, consequently, the entire gait. Segmental and trunk kinematic analysis of cervical spondylogenic myelopathy was examined in detail by Maezawa et al., who described reduced flexion in all three axial joints of the lower limb—the hip, knee, and ankle. In the hip and ankle regions, reduced flexion is explained by spasticity associated with upper motor neuron syndrome, as authors such as Yoon et al. and Maezawa et al. described an inverse relationship between the clinical severity of myelopathy and the degree of reduction in maximum flexion [34,36]. The explanation lies in muscle hypertonicity, which mechanically restricts the physiological range of motion of the joints. We then associate the reduction in ankle plantar flexion with a shortened stride length and flight phase of the gait cycle. The result is a decrease in the individual’s propulsive force. Kinetic analysis was addressed in studies by Malone et al. and Kitade et al., who described a decrease in propulsive force on the ground along with a decrease in flexion torque in the hip and ankle joints. An interesting characteristic is the undulating movement of the knee into a “genu recurvatum” pattern, which occurs during the stance phase of the gait cycle due to the knee joint bearing the individual’s full body weight [33,37]. Electromyographic analysis was then performed by Haddas et al., who found no difference in the maximum amplitude (peak EMG) in the individual muscles of the lower limbs, but paradoxically described it in the medial deltoid muscle. However, they revealed a significant difference in the “time-to-peak EMG” (the time required to reach maximum contraction) in the multifidi muscles, erector spinae muscles, semitendinosus muscle, tibialis anterior muscle, and deltoid muscle [38]. The study by Malone et al. then described prolonged activation of the biceps femoris and rectus femoris muscles, which the authors explain as a compensatory effort to stabilize the proximal portion of the lower limbs and trunk in the presence of acral proprioceptive impairment [39].

 

Sacroiliac Joint Dysfunction

Sacroiliac (SI) joint dysfunction is a painful condition that primarily manifests as back pain, contributing to up to 30% of all cases [40]. It is most commonly caused by degenerative changes in the articular surfaces, but it can also occur secondarily as a result of trauma or iatrogenically following surgical procedures. A typical clinical manifestation is localized pain associated with changes in position, with pseudoradicular radiation from the lower back through the hip joint to the knee. There are few scientific studies conducting motion analysis in patients with sacroiliac dysfunction. At the same time, interpreting the results is problematic, as studies often examine different patient cohorts. For example, Busso et al. performed motion analysis on 21 patients who underwent surgical stabilization of the SI joint due to trauma; Hermanns et al. studied female patients with postpartum SI joint dysfunction; and Mar et al. studied a cohort with unilateral SI joint dysfunction [41–43]. Our research group then published one of the few studies examining the movement profile of patients with bilateral degenerative SI joint dysfunction [44]. The results of kinematic analysis varied across studies. While the study by Busso et al. demonstrated significant changes in all spatiotemporal kinematic parameters, the study by Mar et al. demonstrated a significant change only in step width, which was shorter in patients with SI dysfunction [41,43]. In our cohort, we found a significantly shorter stride length, a shorter swing phase, and a longer double-limb support phase in patients with SI dysfunction [44]. Similar results were reported by Hermans et al., who additionally described lower cadence and walking speed [42]. Segmental and trunk kinematic analysis of our cohort then revealed reduced hip abduction and reduced ankle plantar flexion in patients with SI dysfunction. Differences in hip movements and pelvic tilt were described in studies by Mar et al. and Hermans et al. They explain this as an attempt by patients to avoid micro-movements of the SI joint that occur with increased pressure of the femoral head into the acetabulum, e.g., during hip abduction [42,43]. Reduced ankle plantar flexion is likely a consequence of a shorter stride, which prevents the patient from achieving the maximum possible push-off. In kinetic analysis of patients with SI dysfunction, lower ground reaction forces are typically observed on the affected side compared to the unaffected side [43]. The reason is likely the unloading of the lower limb and a pathological shift in the center of gravity. This phenomenon is evident both during walking and when rising from a seated position, as demonstrated by the study by Capobianca et al. [45]. Only the study by Feeney et al. evaluated EMG analysis of patients with SI dysfunction during walking. Although the study by Capobianca et al. also performed EMG analysis of patients with SI dysfunction, in this case the patients were standing up from a seated position, not walking [45,46]. However, both studies described greater activity of the trunk muscles in an effort to limit the lumbopelvic rhythm, which reduces painful micro-movements of the SI joint. Another interesting finding was the detection of muscular dyssynergy between the latissimus dorsi and gluteus maximus muscles. These are powerful muscles that are normally connected via the thoracolumbar fascia, whose increased tension dynamically stabilizes the SI joint. A disruption of the synergistic effect of these two muscles is one of the proposed etiologies of primary SI dysfunction.

 

Conclusion

The use of motion analysis methods in spinal surgery currently has a largely theoretical dimension. This is due to the limited availability of testing and, above all, the limited ability to interpret the results, which requires the presence of a person with expertise in the physiology and pathophysiology of gait. At the same time, it is important to recognize that although this is a highly sensitive tool for detecting movement pathologies, it is not specific to individual movement disorders. The situation is further complicated by the fact that the average spine surgery patient typically has a medical history indicating multiple diagnoses that affect the physiology of gait. To effectively utilize motion analysis tools, it is advisable to decide before the actual measurement which specific parameters the examiner will evaluate (e.g., how cadence and forces acting on the knee joint differ in a patient with cervical myelopathy compared to a healthy control). In our opinion, to utilize motion analysis in the diagnosis of specific pathologies, it will be necessary to automate the system or use one of the artificial intelligence tools. A suitable tool appears to be the Timm Library, a library of pre-trained machine learning models that evaluate image inputs, which has already been used in the past by Chabaane et al. to evaluate gait in both pediatric and adult patients with movement disorders [47]. We consider the use of motion analysis to evaluate therapeutic success by comparing pre -⁠ and post-operative examinations to be more beneficial. The entire process would certainly benefit from a centralized database of completed examinations, which would eliminate the need to create normative and pathological motion analyses for each newly established laboratory. However, this has long been difficult to implement due to differing measurement protocols, kinematic models, and the lack of trained specialists focused on system setup and the placement of optical markers.

Financial Support

The following article was financially supported by an internal grant from Krajská zdravotní a. s. (IG9-217111041), which included the entire team of co-authors.

 

Ethical aspects

The patients shown in the images have consented to the publication of their anonymized photographs.

 

Conflict of Interest

The authors declare that they have no conflict of interest regarding the subject of the study.

 

Table 1. Basic characteristics of the motion analysis of individual spinal pathologies.

 

	Kinematic parameters			Kinetic parameters	EMG parameters
	Spatio-temporal parameters		Segmental analysis
	Reduced	Increased
Degenerative lumbar stenosis	¯ Stride length ¯ Swing phase ¯ 1-limb support ¯ walking speed ¯ cadence	­ stride width ­ stance phase ­ 2-limb support	¯ hip extension ¯ ankle plantar flexion ¯ craniocaudal and rotational movement of the pelvis	­ pressure in the forefoot	­ contraction intensity (RMS) of the gluteus medius ­ contraction intensity (RMS) of the paravertebral muscles
Cervical myelopathy	¯ stride length ¯ swing phase ¯ 1-limb support ¯ walking speed ¯ cadence	­ stride width ­ stance phase ­ 2-limb support	¯ hip flexion ¯ knee flexion ¯ ankle flexion	¯ propulsive forces ¯ hip flexion torque ¯ hip flexion torque ankle	­ maximum amplitude of the deltoid muscle ­ time to peak Prolonged activation of the biceps femoris and rectus femoris muscles
Sacroiliac joint dysfunction	¯ stride length ¯ swing phase ¯ walking speed ¯ cadence	­ 2-limb support	¯ hip abduction ¯ ankle plantar flexion	¯ reaction forces on the ground on the affected side	early activation of the paravertebral muscles dyssynergy of the latissimus dorsi and gluteus maximus muscles

RMS –⁠ root mean square