Name: Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation (Video) | JoVE Journal
Uploaded: 2024-12-13T12:20:00.000+00:00
Duration: 6 min 28 s
Description: Learn how Camera Lab enables precise movement analysis for personalized rehabilitation in low back pain patients. This innovative tool guides tailored treatment plans and improves patient outcomes through accurate biomechanical assessment.

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This study is part of the project NODES which has received funding from the MUR - M4C2 1.5 of PNRR with grant agreement no. ECS00000036.

Before data collection, all patients included were provided with an informed consent form to review and sign, ensuring their understanding and agreement to participate in the study. Researchers granted the patient's privacy throughout all the study procedures, and they maintained compliance with ethical principles outlined in the Declaration of Helsinki32.
1. Organization of CameraLab setting
<ol>
	<li>Turn on the touch screen of the interactive monitor, the central control hub of the video analysis system (see Figure 1 for further details), and push the power button.</li>
	<li>Position of the four high-velocity cameras according to the distances indicated in Figure 2.</li>
	<li>Connect the four cameras to the interactive monitor: insert the network cables into their corresponding doors.</li>
	<li>Start the camera interface for viewing images in real-time. Click on the icon Video Analysis System to open the software.</li>
</ol>
2. Initial patient interview
<ol>
	<li>Provide the informed consent form for review and signature.</li>
	<li>Collect and note down agraphic and anthropometric data.</li>
	<li>Position the patient in the center of the video analysis system with four high-velocity cameras at 3 m each from the patient according to the distances indicated in Figure 2.</li>
</ol>
3. Assessment with functional movement screen (FMS) in accordance with current guidelines33,34
<ol>
	<li>Ask the patient to perform a warm-up.
	<ol>
		<li>Low-intensity cycling: Ask the patient to pedal while maintaining the seat height to allow for easy achievement of 0° knee extension. Adjust the resistance to prevent fatigue throughout the 12 min duration.</li>
		<li>Lower limb stretching exercise: Ask the patient to lie in a supine position. Ask the patient to hug one thigh at a time to his chest with his hands clasped behind it. Then, perform 3 sets of 10 repetitions of knee extension on each leg.</li>
		<li>Core activation: Instruct the patient to start from a supine position with hips flexed and feet flat on the ground. Ask the patient to perform 15 hip extensions, reaching the bridge position for 3 sets, with a 15-s rest between sets.</li>
	</ol>
	</li>
	<li>Administer to the patient the FMS Test (cameras off), including deep squats, Hurdle steps, Inline lunges, shoulder mobility, active straight leg raises, trunk stability push-ups, and rotatory stability, in accordance with the FMS guidelines33,34.</li>
</ol>
4. System acquisition
<ol>
	<li>Ask the patient to perform two different repetitions of the movements to gain confidence with the motor pattern of the test. Subsequently, ask the patient to perform 2 trials recorded with the innovative assessment tool. Include the movements mentioned below.
	<ol>
		<li>Front squat, no hand: Ask the patient to assume the starting position by positioning the feet approximately shoulder width apart and aligned on the sagittal plane. Have the patient position arms extended forward with a bar resting on the arms. Then, ask the patient to descend as far as possible into a squat position while keeping the torso upright, keeping the heels and bar in place. Hold the downward position for a count of one, then return to the starting position.</li>
		<li>Lower Body Motor Control Screen (LB-MCS) (for each side): Ask the patient to assume the position, arms stretched forward and standing only on the foot of the side being evaluated, the contralateral lower limb is kept with the knee extended and with the foot not resting on the ground. Then, ask the patient to descend as far as possible into a squat position while keeping the torso upright and the foot resting in position. Hold the position down for a count of one, then return to the starting position.</li>
	</ol>
	</li>
	<li>Press the Start button to start recording. The system starts data acquisition until the end of the exercise.</li>
	<li>Press Stop to stop the data acquisition. The system provided a video file stored in a specific folder.</li>
</ol>
5. Data analysis on interactive monitor
<ol>
	<li>Create the patient's folder on the interactive monitor with the recorded videos: right-click on the desktop to open the Desktop menu, choose New Folder, type the name of the new folder, and press Return.</li>
	<li>Open the video selected (Front squat no hand and LB-MCS for right side and LB-MCS for left side).
	<ol>
		<li>For front squat, no hand trial, follow steps 5.2.1.1-5.2.1.8.
		<ol>
			<li>Select the frame from the video generated in lateral views at the point of maximum descent.</li>
			<li>Start video annotation tool for image analysis by double clicking on the Own icon.</li>
			<li>Insert the frame into the report.</li>
			<li>Select the joints in the lateral frame (shoulder, hip, knee, and ankle) by touching the interactive monitor and drawing the skeleton of the limb and trunk axis (see Figure 4). The video annotation tool automatically gives target angles (hip and knee).</li>
			<li>Give scores based on the cut-off (see Table 1) in steps 5.2.1.6-5.2.1.7.</li>
			<li>Lower limb control score: Give a score of 0 if the hip-foot axis does not match the patella with the knee residing medial to the hip-foot axis, give a score of 1 if the hip-foot axis does match the patella laterally, and give a score of 2 if the hip-foot axis does match the patella medially.</li>
			<li>Motor strategy score. Give a score of 0 if active knee flexion &gt; 110° and hip flexion &gt; 100°, give a score of 1 if active knee flexion &gt; 110° or hip flexion &gt; 100°, and give a score of 2 is given if active knee flexion ≤ 110° and hip flexion ≤ 100°.</li>
			<li>Add the lower limb control score and the motor strategy score to calculate the total row score.</li>
		</ol>
		</li>
		<li>For LB-MCS for right side and left side, follow steps 5.2.2.1-5.2.2.11.
		<ol>
			<li>Select the frame from the video generated in both lateral and frontal views at the point of maximum descent.</li>
			<li>Start video annotation tool for image analysis by double clicking on the Own icon.</li>
			<li>Insert the frame into the report.</li>
			<li>Select the joint in the frontal frame (trunk axis, hips, and ankle of the side on the floor) by touching the interactive monitor and drawing the skeleton of the limb and trunk axis (see Figure 5).</li>
			<li>Select the joint in the lateral frame (shoulder, hip, knee, and ankle) by touching the interactive monitor and drawing the skeleton of the limb and trunk axis (see Figure 5). The video annotation tool automatically gives target angles (hip and knee).</li>
			<li>Give scores based on the cut-off (see Table 1) in steps 5.2.2.8-5.2.2.10.</li>
			<li>Lower limb control score: Give a score of 0 if the hip-foot axis does not match the patella with the knee residing medial to the hip-foot axis, give a score of 1 if the hip-foot axis does match the patella laterally, and give a score of 2 if the hip-foot axis does match the patella medially.</li>
			<li>Pelvic tilt score: Give a score of 0 if the pelvic angle does tilt ≥ 15° compared to the horizontal plane, give a score of 1 if the pelvic angle does tilt between 10°-15° compared to the horizontal plane, and give a score of 2 if the pelvic angle does tilt ≤ 10° compared to the horizontal plane.</li>
			<li>Trunk control score: Give a score of 0 if the deviation of the column segment from the perpendicular plane ≥ 15°, give a score of 1 if the deviation of the column segment from the perpendicular plane is between 10°-15°, and give a score of 2 if the deviation of the column segment from the perpendicular plane ≤ 10°.</li>
			<li>Motor strategy score. Give a score of 0 if active knee flexion &gt; 110° and hip flexion &gt; 100°, give a score of 1 if active knee flexion &gt; 110° or hip flexion &gt; 100°, and give a score of 2 if active knee flexion ≤ 110° and hip flexion ≤ 100°.</li>
			<li>Calculate the total row score, which is the sum of the lower limb control score, pelvic tilt score, trunk control score, and motor strategy Score.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Process indications and return the test results to the patient.</li>
</ol>
Figure 1 shows the schematic representation of the protocol.
<img alt="CameraLab process flowchart; patient assessment steps; data acquisition; FMS evaluation method." class="xfigimg" src="/files/ftp_upload/67006/67006fig01.jpg" data-altupdatedat="1788304762000" data-alt="Figure 1"> 
Figure 1: Schematic representation of the protocol. This figure illustrates the step-by-step process of the study protocol. <a href="https://www.jove.com/files/ftp_upload/67006/67006fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Innovative Video-Based Tool for Precision Assessment and Rehabilitation of LBP

The authors declare no conflicts of interest.

In this study, we investigated the integration of the CameraLab system into the rehabilitation management of patients with LBP. The findings of this study suggested that this innovative digital solution provides valuable objective data on movement pattern analysis, enhancing the precision and effectiveness of clinical rehabilitation practice in musculoskeletal pain. LBP is a common and complex condition characterized by a multidimensional disability, including biomechanical, psychological, and social determinants 2,8,9,10,11,12. The approach reported in this case series allowed to target several factors characterizing LBP and addressing different domains as reported by the positive results in pain intensity, physical functioning, HR-QoL, and kinesiophobia.
More in detail, the findings of the case reports presented showed a consistent reduction in pain intensity by targeting specific movement patterns and biomechanical dysfunctions identified through the assessment tool. Interestingly, similar results were shown by Marich et al.45 in their study on musculoskeletal pain using a comparable assessment method. In their research, Marich et al.45 reported a potential link between movement patterns and functional limitations in individuals with chronic LBP. These findings highlighted the need for targeted interventions aimed at optimizing movement dysfunctions to reduce pain and improve functional outcomes in individuals with chronic LBP. Improvements in physical functioning and HR-QoL were shown in the three cases, as evidenced by increases in SF-12 PCS and MCS scores. Similarly, the study by Letafatkar et al.46 highlighted the effects of sensorimotor training protocols in improving proprioceptive system function, lumbar movement control, and HR-QoL for patients with chronic nonspecific LBP. The study underlined that a sensorimotor training program with innovative solutions led to consistent improvements in proprioception, lumbar movement control, and Hr-QoL46.
Kinesiophobia, is a common psychological barrier in individuals with LBP, often leading to avoidance behaviors and functional impairment47. The rehabilitation intervention with CameraLab successfully improved the fear of movement by providing objective feedback on movement patterns and biomechanics. By improving confidence in patients&#39; ability to move safely and efficiently, the assessment tool might reduce kinesiophobia and promote active participation in rehabilitation activities. In this context, there has been a growing interest and investment in digital innovation and technological solutions within the field of rehabilitation25,26,48,49,50,51,52. This trend is driven by several factors, including advancements in sensor technology49,50, the increasing availability of portable devices25, and the growing recognition of the potential benefits of integrating digital tools into healthcare practices52. Digital solutions offer the promise of enhancing the delivery of rehabilitation services by providing objective data, improving patient engagement, and facilitating personalized treatment approaches53.
Several conditions might worsen LBP symptoms. In this context, Zaina et al.54 provided a comprehensive overview of the complexity of LBP in patients with and without scoliosis, highlighting that this condition significantly influences both physical and psychological aspects of health. This study highlights how advanced video-based motion analysis technology can accurately capture movement patterns and postural imbalances that contribute to LBP in a patient with scoliosis. This technology offers detailed insights into the biomechanical factors underlying pain that traditional assessment methods may underestimate. By enabling precise and objective assessment of motion, the approach described here provides a valuable tool for clinicians to develop more effective and personalized treatment plans, thereby improving patient outcomes.
Traditional methods of movement assessment, such as observational techniques or subjective clinical evaluations, are related to biases and difficulties in standardization20,27,28. In contrast, digital technologies, such as motion capture systems, inertial sensors, and computer vision algorithms, enable clinicians to capture and analyze movement data with a high degree of accuracy and reliability20. By quantifying movement parameters objectively, the assessment tool has shown the potential to identify biomechanical abnormalities, track progress over time, and tailor interventions to individual patient needs. Moreover, LBP can negatively impact disorders of kinesiological chains during movements, such as squats, through altered movement patterns. One study found that individuals with chronic LBP exhibit greater hip and knee range of motion relative to ankle ROM than those without LBP. These findings suggest that people with LBP overload their hip and knee joints more during squats, which may contribute to their condition55.
Moreover, Frontera et al.56 highlighted the importance of health policy and health services research in improving rehabilitation practices in real-life settings. The ability to accurately analyze and document movement patterns offers a significant advancement in rehabilitation. In support of this, our findings demonstrate that video analysis technology not only provides detailed biomechanical insights but also supports the development of more personalized and effective treatment strategies. This is in line with the study by Frontera et al.56, which aims to integrate research findings into clinical practice to bridge the gap between research and rehabilitation, ultimately strengthening the quality and accessibility of care for patients with LBP. By targeting specific movement patterns, CameraLab-guided interventions might enhance functional outcomes but might also have positive implications in the long-term, reducing recurrence rates of LBP and improving overall HR-QoL.
Besides these positive considerations, this study is not free from limitations. While CameraLab offers significant advantages in movement assessment, a specific initial setup and calibration of the system is necessary before rehabilitation starts. Moreover, the findings of the present manuscript are based on a small sample size, which aligns with the methodological framework of the case series. Although this approach allows for an in-depth analysis of each case, caution should be posed on the generalizability of the study results. Moreover, different cases with heterogeneous causes of LBP were assessed in this case series. However, this study might offer preliminary insights about an innovative technology that might be further studied in larger cohort studies with homogeneous samples. Lastly, the cost and availability of the technology may limit its widespread adoption in clinical settings. On the other hand, it should be noted that this technology might be one of the most inexpensive and cost-effective in rehabilitation settings compared to similar movement pattern analysis systems. In accordance with other similar movement pattern analysis systems, there might be a risk of bias in inter-operator repeatability, landmark identification, or selection of the maximum descent point57. To address these limitations, we ensure that all personnel involved in the technique are adequately trained and experienced. Future research should aim to validate the effectiveness of this assessment tool further in larger patient populations and compare its outcomes with traditional rehabilitation approaches.
In conclusion, our study suggests that the CameraLab system could have a role in the rehabilitation management of patients with LBP. By providing objective data on movement patterns and facilitating targeted interventions, the assessment tool has the potential to improve outcomes and implement clinical practice. Further research is needed to fully understand its implications and optimize its integration into routine care.

Low back pain (LBP) is a complex and prevalent musculoskeletal condition severely affecting physical functioning and Health-related Quality of Life (HR-QoL)1,2. LBP is a growing global public health problem, consistently ranking as a major cause of disability and limitations in function in daily life. According to the Global Burden of Disease (GBD) 2021 study, the prevalence of LBP is increasing, estimating nearly 619 million people worldwide in 2020. The study highlights that LBP represents a substantial portion of years lived with disability, with prevalence observed primarily in individuals aged 45 to 64 years3. Due to the aging of the population, its prevalence is expected to rise in the future decades while growing research is currently focusing on innovative approaches to improve the management of this condition4,5,6. The 2019 GBD analysis further confirms these findings, indicating that LBP remains a prevalent condition in several regions of the world, with a strong impact on HR-QoL7. Projections suggest that without effective intervention, the prevalence and burden of LBP will continue to grow, necessitating comprehensive global approach for prevention and management3,7.
While the optimal therapeutic strategy is typically based on the precise pathophysiology of LBP, different therapeutic approaches have been suggested to address the multifaceted management of this disabling condition8,9,10,11,12. The WHO Rehabilitation Guide provides a comprehensive framework for global rehabilitation practices, emphasizing their critical role in managing chronic LBP13. These guidelines underline the need for an integrated and personalized approach to the patient, addressing the biopsychosocial aspects of chronic pain management. This involves a coordinated effort among multidisciplinary healthcare professionals to provide non-surgical interventions based on scientific evidence and tailored to the individual needs of each patient. A comprehensive approach is essential to reduce variability in care, improve quality of life, and improve overall outcomes for those with LBP. The guidance also highlights the importance of accessibility and equity in rehabilitation services, ensuring that interventions are feasible and acceptable in different contexts, thus supporting universal health coverage and improving global public health13.
In this context, it is interesting to notice that patients with LBP are frequently characterized by crucial biomechanical changes that should be precisely addressed for an effective rehabilitation approach14,15,16. These alterations might include deviations in spinal alignment17, muscle imbalances18, joint stiffness or hypermobility19, aberrant movement patterns20, asymmetries in muscle activation12, and compromised neuromuscular control21,22. As a result, identifying and addressing these specific biomechanical changes are crucial for tailoring rehabilitation programs to target the underlying mechanisms contributing to LBP and facilitating optimal recovery outcomes23,24.
In this context, assessment methods for movement patterns might include motion inertial sensors, force plates, standardized observational tests, and qualitative observation criteria25,26,27,28,29,30. Motion inertial sensors, while offering portability and ease of use, have limitations primarily related to data accuracy and reliability. Their measurements can be affected by sensor drift, orientation errors, and signal noise, leading to inaccuracies in movement analysis29. Additionally, motion inertial sensors may have limited capacity to assess complex movement patterns accurately, especially in dynamic activities, including rapid movements or changes in direction20. Force plates, although valuable for quantifying ground reaction forces and kinetics during movement, have limitations regarding their spatial and temporal resolution30. They may not provide detailed information on movement quality or kinematic patterns and are primarily focused on assessing forces exerted on the ground rather than the movement patterns30. On the other hand, qualitative observation criteria, while useful for capturing qualitative aspects of movement, lack standardization and may vary between observers lacking in standardization and reliably27,28. Interestingly, the recent review by van Dijk et al.20 underlined that only specific domains of movement quality (such as range of motion (ROM) and gate analysis) were effectively assessed by objective methods in patients with LBP and significantly differed by the general population.
As a result, objective and quantifiable methods for movement assessment are lacking, and several challenges still affect both the intervention and monitoring processes for patients with LBP20. Moreover, the barriers to the effective integration of these tools into routine clinical practice further improve the challenges associated with effectively addressing LBP conditions.
Taken together, this evidence suggests that there remains a substantial gap in knowledge regarding digital instruments designed for evaluating movement quality during functional exercises. Furthermore, the implications of integrating precise movement assessment analysis into the rehabilitation process have yet to be fully characterized.
Therefore, here we present a case series introducing CameraLab system, an innovative digital solution that provides objective data about movement pattern analysis in patients with LBP. In some cases, instrumental examinations with X-Rays have little indication regarding rehabilitation implications in patients with LBP. In this case, the functional assessment with motion capture could fill this gap and provide answers to rehabilitation needs31. In this case series, we showed the effective integration of the innovative assessment tool into the comprehensive rehabilitation management of patients with LBP, underlining the functional and objective data achieved with this technological solution in order to enhance the precision and effectiveness of clinical rehabilitation practice in people with LBP.

<table><tbody><tr><td>ApowerREC</td><td>Apowersoft</td><td>https://www.apowersoft.com/record-all-screen</td><td>This screen recorder serves to capture and annotate screen activity during analysis sessions</td></tr><tr><td>Functional Movement Screen kit</td><td>Functional Movement Systems Inc., Chatham, VA</td><td>N/A</td><td>Funtional Movement Screen kit consisting of a two-inch by six-inch board, one four-foot-long dowel, two short dowels, and an elastic cord, is used to administer the FMS test.</td></tr><tr><td>Hikvision Cameras IP POE DOME</td><td>Hikvision</td><td>DS-2CD1623G0-IZ</td><td>The cameras are equipped to record precise motion sequences and to capture dynamic movements with exceptional speed and detail.</td></tr><tr><td>Kinovea</td><td>Kinovea</td><td>Version 0.9.5</td><td>Kinovea is a video annotation tool designed for sport analysis. It features utilities to capture, slow down, compare, annotate and measure motion in videos.</td></tr><tr><td>Sharp Big Pad (PN-85 TH1)</td><td>Sharp Corporation</td><td>PN-85 TH1</td><td>The PN-85TH1 interactive BIG PAD monitor combines &quot;4K reading&quot; and the &quot;Pen-on-Paper&quot; user experience with the high precision of InGlass touch technology. Includes whiteboard and wireless capabilities to further enhance the customer experience</td></tr><tr><td>Synology Surveillance Station&amp;nbsp;</td><td>Synology</td><td>N/A</td><td>Robust and versatile Video Management System (VMS) designed to turn Synology Network Attached Storage (NAS) devices into centralized surveillance solutions</td></tr></tbody></table>

biomechanical changes related to low back pain: an innovative tool for movement pattern assessment and treatment evaluation in rehabilitation

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation

Low back pain (LBP) is a highly prevalent disorder frequently related to biomechanical alterations. Movement pattern assessments have a role in the rehabilitation management of patients with LBP; however, a precise assessment is challenging in routine clinical settings. Thus, this study aims to assess the biomechanical alterations related to LBP through the development and application of an innovative assessment tool named CameraLab. Patients with LBP were assessed through a video analysis system. The movement pattern assessment tool includes a touchscreen interface and four high-velocity cameras, enabling real-time data acquisition during movement assessments. The cameras capture dynamic movements, facilitating a thorough examination of motor function. A video analysis software application is employed for precise angle assessments and joint tracking. Three patients with LBP were assessed, demonstrating positive results in pain intensity, functional independence, and overall well-being. The integration of advanced technology highlighted the movement pattern alterations and contributed to tailored rehabilitation strategies. The study offers a paradigm shift toward precision rehabilitation. This innovative approach provides valuable insights into the biomechanical changes related to LBP, fostering a deeper understanding for clinicians and paving the way for effective personalized interventions in the management of LBP.

This study shows the role of an innovative tool for assessing and treating biomechanical alterations in low back pain (LBP) patients. Three LBP patients demonstrated improved pain intensity and functional independence post-assessment. The technology aids in tailored rehabilitation strategies, offering insights into LBP biomechanics for personalized interventions.

Low back pain (LBP) is a highly prevalent disorder frequently related to biomechanical alterations. Movement pattern assessments have a role in the ...

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Learn how Camera Lab enables precise movement analysis for personalized rehabilitation in low back pain patients. This innovative tool guides tailored treatment plans and improves patient outcomes through accurate biomechanical assessment.

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation (Video) | JoVE Journal

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation

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