Clinical Gait Analysis on a Patient Undergoing Surgical Correction of Kyphosis from Severe Ankylosing Spondylitis

Haddas, Ram; Belanger, Theodore A.

doi:10.14444/4018

Cited by 15 publications

(7 citation statements)

References 16 publications

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“…The quantitative analysis of human motion, and especially gait, with cameras, optoelectronic systems, wearable inertial devices, electromyography systems, force plates, and pressure sensors is widely employed for the scientific and clinical investigations of several pathologies. Indeed, the study of gait pattern alterations in patients suffering from spinal disorders is a very active area of research . Traditional gait analysis aims at the measurement of spatiotemporal parameters such as walking velocity, stride and step lengths, cadence, and duration of the stance and swing phases; kinematic parameters such as the angles of rotation of the various joints; kinetic parameters such as forces and moments in the joints, which typically involve the use of force platforms.…”

Section: Applications Of Ai and ML In Spine Researchmentioning

confidence: 99%

Artificial intelligence and machine learning in spine research

2019

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Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those used in spine research. Then, we describe the applications of AI and ML to problems related to the spine which have been published so far, including the localization of vertebrae and discs in radiological images, image segmentation, computer‐aided diagnosis, prediction of clinical outcomes and complications, decision support systems, content‐based image retrieval, biomechanics, and motion analysis. Finally, we briefly discuss major ethical issues related to the use of AI in healthcare, namely, accountability, risk of biased decisions as well as data privacy and security, which are nowadays being debated in the scientific community and by regulatory agencies.

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Section: Applications Of Ai and ML In Spine Researchmentioning

confidence: 99%

Artificial intelligence and machine learning in spine research

2019

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“…Shiba et al [ 25 ] demonstrated significant differences in sagittal alignment between dynamic and static parameters in patients with degenerative lumbar kyphoscoliosis through gait analysis. Similarly, Haddas et al [ 26 ] evaluated kinematics, ground reaction forces, and electromyography results by gait analysis and found significant changes in the spine and lower extremity values in the abnormal spinal sagittal alignment.…”

Section: Introductionmentioning

confidence: 99%

The Kinematic and Kinetic Responses of the Trunk and Lower Extremity Joints during Walking with and without the Spinal Orthosis

Wang

Guo

et al. 2022

IJERPH

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Spinal orthoses are an effective option for restoring the spine to its original position and controlling poor posture. However, the effects of poor posture and spinal orthoses on the kinematics and kinetics of trunk and lower extremity joints remain unclear. A six-camera Vicon motion capture system and two AMTI force plates were employed to collect gait parameters, including joint angle (spine, thorax, hip, knee, and ankle), range of motion (ROM), and ground reaction forces (GRFs). Furthermore, joint moments and joint reaction forces (JRFs) were calculated using a full-body musculoskeletal model in OpenSim. One-way repeated-measures ANOVA (p < 0.05) was used to compare significant differences among three trial conditions. These three conditions were walking in a normal posture, poor posture, and spinal orthosis. The results showed that spine ROM in the coronal and transverse plane was significantly lower when walking with a spinal orthosis compared to walking in normal and poor posture (p < 0.05). Compared to normal posture, the lumbar moments and back compressive forces were significantly increased when walking in poor posture (p < 0.05). However, when walking with a spinal orthosis, there was a significant decrease in trunk moments and reaction forces compared to walking in poor posture (p < 0.05). Individuals with poor posture could potentially induce instability and disorders, as evidenced by an increase in trunk moments and JRF compared to the normal posture. Spinal orthosis not only restricts spine ROM but also reduces the load on the spine and thus increases balance and stability.

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“…[6][7][8] Many musculoskeletal and neurological disorders, including CSM, result in altered gait patterns. [9][10][11][12][13][14][15][16][17] These include a slower gait speed, decreased cadence, extended double support duration and stride time, shorter stride and step length, wider step width, and alter muscular activity compared with healthy controls. 13,[18][19][20][21][22] In addition, CSM patients present with more anterior pelvis tilt, larger lumbar lordosis, less cervical lordosis, and less head flexion at the beginning of the gait cycle in comparison to healthy controls.…”

Section: Introductionmentioning

confidence: 99%

“…CSM is characterized by a wide variety of clinical presentations, which can include neck pain, numbness or weakness in the extremities, hand clumsiness, and classically, gait, and balance disturbances 6–8. Many musculoskeletal and neurological disorders, including CSM, result in altered gait patterns 9–17. These include a slower gait speed, decreased cadence, extended double support duration and stride time, shorter stride and step length, wider step width, and alter muscular activity compared with healthy controls 13,18–22.…”

Section: Introductionmentioning

confidence: 99%

Fear-avoidance and Patients’ Reported Outcomes are Strongly Correlated With Biomechanical Gait Parameters in Cervical Spondylotic Myelopathy Patients

Haddas

Boah

Block

2020

Clinical Spine Surgery: A Spine Publication

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Objective: The aim was to explores whether fear-avoidance is associated with altered gait patterns in cervical spinal myelopathy (CSM) patients.Summary of Background Data: Fear-avoidance is associated with activity restriction and emotional distress in chronic pain patients and with poorer spine surgery outcomes. In adults with spinal deformity, fear and avoidance correlates with gait pattern disruptions. Patients having CSM also display distorted gait.Methods: Ninety CSM patients completed the Tampa Scale for Kinesiophobia (TSK) questionnaire, and the Fear-avoidance Beliefs Questionnaire (FABQ). Each patient performed a series of gait trials. Pearson's product correlation analysis was used to determine the relationship between the self-reported fear of movement measures and the objective gait biomechanical data. Results:The TSK total score was correlated with walking speed (P = 0.003), cadence (P = 0.012), stride (P = 0.010) and step (P = 0.036) time, and stride (P = 0.018) and step (P = 0.035) length. The FABQ physical dimension was correlated with walking speed (P < 0.001), cadence (P < 0.001), stride (P < 0.001) and step (P = 0.006) time, stride (P < 0.001) and step (P < 0.001) length, and gait deviation index (P < 0.001). The FABQ work dimension was correlated with walking speed (P = 0.001), cadence (P = 0.001), stride (P = 0.001) and step (P = 0.008) time, and stride (P = 0.014) and step (P = 0.002) length.Conclusions: These results provide a framework for further investigation of the relationship between psychosocial factors and objectively measured function in patients with CSM. This study demonstrates a strong correlation between fear and avoidance of movement, as measured with the TSK and FABQ and multiple biomechanical gait parameters, as measured with gait analysis. The current results may imply that fear and avoidance may compound and worsen functional deficits arising from CSM, and strongly suggest that fear and avoidance beliefs should be included as a component of presurgical diagnostic process for CSM patients.

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Clinical Gait Analysis on a Patient Undergoing Surgical Correction of Kyphosis from Severe Ankylosing Spondylitis

Abstract: Background

Cited by 15 publications

References 16 publications

Artificial intelligence and machine learning in spine research

Artificial intelligence and machine learning in spine research

The Kinematic and Kinetic Responses of the Trunk and Lower Extremity Joints during Walking with and without the Spinal Orthosis

Fear-avoidance and Patients’ Reported Outcomes are Strongly Correlated With Biomechanical Gait Parameters in Cervical Spondylotic Myelopathy Patients

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