A novel IMU-based clinical assessment protocol for Axial Spondyloarthritis: a protocol validation study

The association of cervical and lumbar mobility with functional ability in axial spondyloarthritis: Insights from the CASTRO registry using Inertial Measurement Unit system

OBJECTIVE

This study aimed to evaluate the association of cervical and lumbar mobility with functional ability in patients with axial spondyloarthritis (axSpA) using an inertial measurement unit (IMU) sensor system, as well as the influence of disease duration on this association.

METHODS

This cross-sectional study included 156 patients with axSpA from the Córdoba axSpA Task Force Registry and Outcomes (CASTRO) registry. Spinal mobility was assessed with the IMU system and functional ability was measured using the Bath Ankylosing Spondylitis Functional Index (BASFI). Patients were categorized into non-longstanding (≤23 years) and longstanding (>23 years) groups based on the median disease duration. Univariable and multivariable linear regressions were conducted to evaluate the variability of BASFI explained by each spinal movement (coefficient of determination [R²]).

RESULTS

Multivariable linear regression analysis showed that cervical movements collectively explained 19.9 % (R2 = 0.199) of BASFI variability, while lumbar mobility accounted for 11.3 %. Among longstanding axSpA patients, cervical rotation (unstandardized regression coefficient [B] = -0.68, 95 % CI1.13 to -0.24) and lumbar flexion (B = 0.65, 95 % CI 0.05 to 1.24), were independently associated with the BASFI scores. In non-longstanding patients, lumbar mobility, particularly lumbar rotation (B = -0.51, 95 % CI0.97 to -0.05), showed a stronger association with functional ability.

CONCLUSIONS

This study suggests that cervical mobility is more strongly associated with functional ability than lumbar mobility in axSpA patients. However, the impact of cervical and lumbar mobility on functional ability varies with disease duration.

Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer

This data descriptor presents a comprehensive and replicable dataset and method for calculating the cervical range of motion (CROM) utilizing quaternion-based orientation analysis from Delsys inertial measurement unit (IMU) sensors. This study was conducted with 14 participants and analyzed 504 cervical movements in the Sagittal, Frontal and Horizontal planes. Validated against a Universal Goniometer and tested for reliability and reproducibility. Analysis showed strong validity in the sagittal plane (R = 0.828 ± 0.051) and moderate in the frontal (R = 0.573 ± 0.138), with limitations in the horizontal plane (R = 0.353 ± 0.122). Reliability was high across all planes (Sagittal: ICC = 0.855 ± 0.065, Frontal: ICC = 0.855 ± 0.015, Horizontal: ICC = 0.945 ± 0.005). Our model for CROM measurements is a valuable tool aiding diagnosis, treatment planning, and monitoring of cervical spine conditions. This study presents an accessible analysis process for biomechanical assessments in cervical and spinal fields. The dataset herein serves as a benchmark for state-of-the-art machine learning models predicting head/neck position, analyzing smoothness of movements, measuring standard motion patterns, and calibrating drift based on movement comparisons.

Can we reliably assess spine movement quality in clinics? A comparison of systems to evaluate movement reliability in a healthy population

Inertial measurement units (IMUs) have the potential to facilitate a large influx of spine movement and motor control data to help stratify low back pain (LBP) diagnosis and care; however, uncertainties related to validity and equipment/movement reliability are preventing widespread use and acceptance. This study evaluated the concurrent validity of Xsens DOT IMUs relative to gold-standard optical motion capture equipment, and compared within- and between-day reliability of both systems to track spine range of motion (ROM) and movement quality (MQ) by evaluating intraclass correlation coefficients (ICC), standard error of measurement (SEM), coefficient of variation (CV), and minimum detectable difference (MDD). ROM was evaluated during planar ROM movements, and local dynamic stability (LDS; λmax), mean absolute relative phase (MARP) and deviation phase (DP) were estimated from repetitive trunk flexion at 3 speeds, in 15 healthy controls to assess MQ. Results showed no statistically significant differences between systems for all metrics, and ICCs ≥ 0.86; therefore, validity was confirmed for tracking primary axis ROM and MQ. IMU data revealed that absolute (C7, T12, and S1) and relative (thoracic, lumbar, and total) ROM was the most reliable metric, followed by λmax, DP, and MARP. Reliability was similar between systems, suggesting that the poorer between-day reliability (higher SEM and CV, lower ICC) observed is attributable to movement variability and sensor placement rather than equipment error. The MDDs can provide thresholds to researchers and clinicians for identifying changes in MQ. Further standardization of evaluated movements/metrics, and patient subgrouping are suggested to improve reliability assessments and refine MDDs in future work.

A machine learning approach for the design optimization of a multiple magnetic and inertial sensors wearable system for the spine mobility assessment

BACKGROUND

Recently, magnetic and inertial measurement units (MIMU) based systems have been applied in the spine mobility assessment; this evaluation is essential in the clinical practice for diagnosis and treatment evaluation. The available systems are limited in the number of sensors, and neither develops a methodology for the correct placement of the sensors, seeking the relevant mobility information of the spine.

METHODS

This work presents a methodology for analyzing a system consisting of sixteen MIMUs to reduce the amount of information and obtain an optimal configuration that allows distinguishing between different body postures in a movement. Four machine learning algorithms were trained and assessed using data from the range of motion in three movements (Mov.1-Anterior hip flexion; Mov.2-Lateral trunk flexion; Mov.3-Axial trunk rotation) obtained from 12 patients with Ankylosing Spondylitis.

RESULTS

The methodology identified the optimal minimal configuration for different movements. The configuration showed good accuracy in discriminating between different body postures. Specifically, it had an accuracy of 0.963 ± 0.021 for detecting when the subject is upright or bending in Mov.1, 0.944 ± 0.038 for identifying when the subject is flexed to the left or right in Mov.2, and 0.852 ± 0.097 for recognizing when the subject is rotated to the right or left in Mov.3.

CONCLUSIONS

Our results indicate that the methodology developed results in a feasible configuration for practical clinical studies and paves the way for designing specific IMU-based assessment instruments.

TRIAL REGISTRATION

Study approved by the Local Ethics Committee of the General Hospital of Mexico "Dr. Eduardo Liceaga" (protocol code DI/03/17/471).

Towards Wearable and Portable Spine Motion Analysis Through Dynamic Optimization of Smartphone Videos and IMU Data

BACKGROUND

Monitoring spine kinematics is crucial for applications like disease evaluation and ergonomics analysis. However, the small scale of vertebrae and the number of degrees of freedom present significant challenges for noninvasive and convenient spine kinematics estimation.

METHODS

This study developed a dynamic optimization framework for wearable spine motion tracking at the intervertebral joint level by integrating smartphone videos and Inertia Measurement Units (IMUs) with dynamic constraints from a thoracolumbar spine model. Validation involved motion data from 10 healthy males performing static standing, dynamic upright trunk rotations, and gait. This data included rotations of ten IMUs on vertebrae and virtual landmarks from three smartphone videos preprocessed by OpenCap, an application leveraging computer vision for pose estimation. The kinematic measures derived from the optimized solution were compared against simultaneously collected infrared optical marker-based measurements and in vivo literature data. Solutions only based on IMUs or videos were also compared for accuracy evaluation.

RESULTS

The proposed optimization approach closely matched the reference data in the intervertebral or segmental rotation range, demonstrating minimal angular differences across all motions and the highest correlation in 3D rotations (maximal Pearson and intraclass correlation coefficients of 0.92 and 0.94, respectively). Time-series changes of joint angles also aligned well with the optical-marker reference.

CONCLUSION

Dynamic optimization of the spine simulation that integrates IMUs and computer vision outperforms the single-modality method.

SIGNIFICANCE

This markerless 3D spine motion capture method holds potential for spinal health assessment in large cohorts in real-world settings without dedicated laboratories.

Validation of Pelvis and Trunk Range of Motion as Assessed Using Inertial Measurement Units

Trunk and pelvis range of motion (ROM) is essential to perform activities of daily living. The ROM may become limited with aging or with neuromusculoskeletal disorders. Inertial measurement units (IMU) with out-of-the box software solutions are increasingly being used to assess motion. We hypothesize that the accuracy (validity) and reliability (consistency) of the trunk and pelvis ROM during steady-state gait in normal individuals as measured using the Opal APDM 6 sensor IMU system and calculated using Mobility Lab version 4 software will be comparable to a gold-standard optoelectric motion capture system. Thirteen healthy young adults participated in the study. Trunk ROM, measured using the IMU was within 5-7 degrees of the motion capture system for all three planes and within 10 degrees for pelvis ROM. We also used a triad of markers mounted on the sternum and sacrum IMU for a head-to-head comparison of trunk and pelvis ROM. The IMU measurements were within 5-10 degrees of the triad. A greater variability of ROM measurements was seen for the pelvis in the transverse plane. IMUs and their custom software provide a valid and reliable measurement for trunk and pelvis ROM in normal individuals, and important considerations for future applications are discussed.

Automated, IMU-based spine angle estimation and IMU location identification for telerehabilitation

BACKGROUND

Telerehabilitation is a promising avenue for improving patient outcomes and expanding accessibility. However, there is currently no spine-related assessment for telerehabilitation that covers multiple exercises.

METHODS

We propose a wearable system with two inertial measurement units (IMUs) to identify IMU locations and estimate spine angles for ten commonly prescribed spinal degeneration rehabilitation exercises (supine chin tuck head lift rotation, dead bug unilateral isometric hold, pilates saw, catcow full spine, wall angel, quadruped neck flexion/extension, adductor open book, side plank hip dip, bird dog hip spinal flexion, and windmill single leg). Twelve healthy subjects performed these spine-related exercises, and wearable IMU data were collected for spine angle estimation and IMU location identification.

RESULTS

Results demonstrated average mean absolute spinal angle estimation errors of 2.59∘ and average classification accuracy of 92.97%. The proposed system effectively identified IMU locations and assessed spine-related rehabilitation exercises while demonstrating robustness to individual differences and exercise variations.

CONCLUSION

This inexpensive, convenient, and user-friendly approach to spine degeneration rehabilitation could potentially be implemented at home or provide remote assessment, offering a promising avenue to enhance patient outcomes and improve accessibility for spine-related rehabilitation.

TRIAL REGISTRATION

No. E2021013P in Shanghai Jiao Tong University.

Validity and reliability of inertial measurement units used to measure motion of the lumbar spine: A systematic review of individuals with and without low back pain

Low back pain (LBP) is a leading cause of disability, resulting in aberrant movement. This movement is difficult to measure accurately in clinical practice and gold standard methods, such as optoelectronic systems involve the use of expensive laboratory equipment. Inertial measurement units (IMU) offer an alternative method of quantifying movement that is accessible in most environments. However, there is no consensus around the validity and reliability of IMUs for quantifying lumbar spine movements compared with gold standard measures. The aim of this systematic review was to establish concurrent validity and repeated measures reliability of using IMUs for the measurement of lumbar spine movements in individuals with and without LBP. A systematic search of electronic databases, incorporating PRISMA guidelines was completed, limited to the English language. 503 studies were identified where 15 studies met the inclusion criteria. Overall, 305 individuals were included, and 109 of these individuals had LBP. Weighted synthesis of the results demonstrated root mean squared differences of <2.4° compared to the gold standard and intraclass correlations >0.84 for lumbar spine movements. IMUs offer clinicians and researchers valid and reliable measurement of motion in the lumbar spine, comparable to laboratory methods, such as optoelectronic motion capture for individuals with and without LBP.

Investigating concurrent validity of inertial sensors to evaluate multiplanar spine movement

Inertial measurement units (IMUs) offer a portable and inexpensive alternative to traditional optical motion capture systems, and have potential to support clinical diagnosis and treatment of low back pain; however, due to a lack of confidence regarding the validity of IMU-derived metrics, their uptake and acceptance remain a challenge. The objective of this work was to assess the concurrent validity of the Xsens DOT IMUs for tracking multiplanar spine movement, and to evaluate concurrent validity and reliability for estimating clinically relevant metrics relative to gold-standard optical motion capture equipment. Ten healthy controls performed spine range of motion (ROM) tasks, while data were simultaneously tracked from IMUs and optical marker clusters placed over the C7, T12, and S1 vertebrae. Root mean square error (RMSE), mean absolute error (MAE), and intraclass correlation coefficients (ICC2,1) were calculated to assess validity and reliability of absolute (abs; C7, T12, and S1 sensors) and relative joint (rel; intersegmental thoracic, lumbar, and total) motion. Overall RMSEabs = 1.33°, MAEabs = 0.74° ± 0.69, and ICC2,1,abs = 0.953 across all movements, sensors, and planes. Results were slightly better for uniplanar movements when evaluating the primary rotation axis (prim) absolute ROM (MAEabs,prim = 0.56° ± 0.49; ICC2,1,abs,prim = 0.999). Similarly, when evaluating relative intersegmental motion, overall RMSErel = 2.39°, MAErel = 1.10° ± 0.96, and ICC2,1,rel = 0.950, and relative primary rotation axis achieved MAErel,prim = 0.87° ± 0.77, and ICC2,1,rel,prim = 0.994. Findings from this study suggest that these IMUs can be considered valid for tracking multiplanar spine movement, and may be used to objectively assess spine movement and neuromuscular control in clinics.

Evaluation of Upper Body and Lower Limbs Kinematics through an IMU-Based Medical System: A Comparative Study with the Optoelectronic System

In recent years, the use of inertial-based systems has been applied to remote rehabilitation, opening new perspectives for outpatient assessment. In this study, we assessed the accuracy and the concurrent validity of the angular measurements provided by an inertial-based device for rehabilitation with respect to the state-of-the-art system for motion tracking. Data were simultaneously collected with the two systems across a set of exercises for trunk and lower limbs, performed by 21 healthy participants. Additionally, the sensitivity of the inertial measurement unit (IMU)-based system to its malpositioning was assessed. Root mean square error (RMSE) was used to explore the differences in the outputs of the two systems in terms of range of motion (ROM), and their agreement was assessed via Pearson's correlation coefficient (PCC) and Lin's concordance correlation coefficient (CCC). The results showed that the IMU-based system was able to assess upper-body and lower-limb kinematics with a mean error in general lower than 5° and that its measurements were moderately biased by its mispositioning. Although the system does not seem to be suitable for analysis requiring a high level of detail, the findings of this study support the application of the device in rehabilitation programs in unsupervised settings, providing reliable data to remotely monitor the progress of the rehabilitation pathway and change in patient's motor function.

Effectiveness of Different Cervical Range of Motion Measurement Techniques for Home-Use to Prevent Cervical Spondylosis

Cervical spondylosis is a non-specific degenerative of cervical spine which results in spinal canal and nerve root foramen stenosis. The stenosis of the canals results in injury of spinal cord and nerve root. The nerve root compression causes a various symptom, such as referred pain and numbness in neck and upper extremities. Motion sensors allow for the tracking and observation of cervical movement activities with the purpose of preventing cervical spondylosis. In the proposed study, Inertia Measurement Unit (IMU) sensors and comparative 2- Dimensional Motion Capture (2D-MC) system were considered to determine the effective of cervical range of motion in various environments. The results indicated that both methods provided strong correlations of craniovertebral angles, with the IMU sensors showing a higher correlation coefficient than the 2D-MC system. Therefore, the craniovertebral angles from IMU sensors were utilized to identify the safety and warning zones of neck movements.Clinical Relevance- The degenerative of the cervical spine results in different degrees of severity in cervical spondylosis. To prevent further deterioration, it is recommended to adopt lifestyle changes, especially neck movement changes, that reduce the spinal cord or nerve root compression. An innovation that can detect harmful neck movements in real-time can provide feedback to users on whether they are moving their head into dangerous angles. By training regularly with this innovation, individuals can delay the onset and severity of cervical spondylosis symptoms and make adjustments to their lifestyles to prevent recurrence of the condition in the future.

Initial study on an expert system for spine diseases screening using inertial measurement unit

In recent times, widely understood spine diseases have advanced to one of the most urgetn problems where quick diagnosis and treatment are needed. To diagnose its specifics (e.g. to decide whether this is a scoliosis or sagittal imbalance) and assess its extend, various kind of imaging diagnostic methods (such as X-Ray, CT, MRI scan or ST) are used. However, despite their common use, some may be regarded as (to a level) invasive methods and there are cases where there are contraindications to using them. Besides, which is even more of a problem, these are very expensive methods and whilst their use for pure diagnostic purposes is absolutely valid, then due to their cost, they cannot rather be considered as tools which would be equally valid for bad posture screening programs purposes. This paper provides an initial evaluation of the alternative approach to the spine diseases diagnostic/screening using inertial measurement unit and we propose policy-based computing as the core for the inference systems. Although the methodology presented herein is potentially applicable to a variety of spine diseases, in the nearest future we will focus specifically on sagittal imbalance detection.

Cervical Proprioception Assessed through Targeted Head Repositioning: Validation of a Clinical Test Based on Optoelectronic Measures

Neck proprioception is commonly assessed with head repositioning tests. In such a test, an operator rotates the head of a blindfolded individual to a target position. After returning to the rest position, the participant actively repositions the head to the target. Joint Position Error (JPE) is the angular difference between the target angle (however oriented in a 3D space) and the actively reached positions (the smaller the difference, the better the proprioception). This study aimed to validate a head-to-target (HTT) repositioning test using an optoelectronic system for also measuring the components of the JPE in the horizontal, frontal, and sagittal planes. The head movements requested by the operator consisted of 30° left-right rotations and 25° flexion-extension. The operators or subjects could not obtain these movements without modest rotations in other planes. Two operators were involved. Twenty-six healthy participants (13 women) were recruited (mean (SD): 33.4 (6.3) years). The subjects’ JPE in the requested (intended) plane of motion (JPEint-component) was a few degrees only and smaller for flexion-extensions than for left-right rotations (right rotation: 5.39° (5.29°); left rotation: 5.03° (4.51°), extension: 1.79° (3.94°); flexion: 0.54° (4.35°)). Participants’ average error in unintended planes was around 1° or less. Inter-operator consistency and agreement were high. The smallest detectable change, at p < 0.05, for JPEint-component ranged between 4.5° and 6.98°. This method of optoelectronic measurement in HTT repositioning tests provides results with good metric properties, fostering application to clinical studies.

Kinematic Analysis of the Forward Head Posture Associated with Smartphone Use

Background: Frequent use of mobile devices has a known association with musculoskeletal neck pain. This study sought out to localize the region with greatest flexion in the cervical spine and explored the role of symmetry in maintaining the pose during texting. Methods: Three inertial measuring units (IMUs) superficially attached along the cervical spine divided the cervical spine into two measurable segments. Twenty-five subjects participated in the study and performed three tasks when using smartphones: sitting, standing, and walking. Data from each IMU were used to calculate the flexion of cervical divided into two segments: craniocervical junction (C0–C1) and subaxial (C1–C7). Results: The greatest flexion by far occurred at C0–C1. While sitting, standing, and walking, the mean flexion angles were 33.33 ± 13.56°, 27.50 ± 14.05°, and 32.03 ± 10.03° for the C0–C1 joint and −3.30 ± 10.10°, 2.50 ± 9.99°, and −1.05 ± 11.88° for the C2–C7 segment, respectively. There is a noticeable pattern of yaw movement of the head, with a slow rotation toward symmetry and a fast corrective movement toward the smartphone held in one hand. Conclusions: This study identified the region of greatest contribution toward forward flexion along the cervical parameters during various tasks involving smartphone use. With each task, the greatest contributor to head flexion was the C0–C1 joint. There is involuntary rotation of the cervical spine toward symmetry when texting.

Inter-rater and intra-rater reliability of isotonic exercise monitoring device for measuring active knee extension

Background

The goal of this study was to assess the reliability of electromyography and range of motion measurements obtained using a knee exercise monitoring system. This device was developed to collect data on knee exercise activities.

Methods

Twenty healthy individuals performed isotonic quadriceps exercises in this study. The vastus medialis surface electromyography (sEMG) and range of motion (ROM) of the knee were recorded during the exercise using the isotonic knee exercise monitoring device, the Mobi6-6b, and a video camera system. Each subject underwent a second measuring session at least 24 h after the first session. To determine reliability, the intraclass correlation coefficients (ICCs) and standard error of measurement (SEM) at the 95% confidence interval were calculated, and a Bland-Altman analysis was performed.

Results

For inter-rater reliability, the ICCs of the mean absolute value (MAV) and root mean square (RMS) of sEMG were 0.73 (0.49, 0.86) and 0.79 (0.61, 0.89), respectively. ROM had an ICC of 0.93 (0.02, 0.98). The intra-rater reliability of the MAV of the sEMG was 0.89 (0.71, 0.96) and the intra-rater reliability of RMS of the sEMG was 0.88 (0.70, 0.95). The ROM between days had an intra-rater reliability of 0.82 (0.54, 0.93). The Bland-Altman analysis demonstrated no systematic bias in the MAV and RMS of sEMG, but revealed a small, systematic bias in ROM (-0.8311 degrees).

Conclusion

For sEMG and range of motion measures, the isotonic knee exercise monitoring equipment revealed moderate to excellent inter- and intra-rater agreement. However, the confidence interval of ROM inter-rater reliability was quite large, indicating a small agreement bias; hence, the isotonic knee exercise monitor may not be suitable for measuring ROM. This isotonic knee exercise monitor could detect and collect information on a patient's exercise activity for the benefit of healthcare providers.

Validity and feasibility of remote measurement systems for functional movement and posture assessments in people with axial spondylarthritis

INTRODUCTION

This study aimed to estimate the criterion validity of functional movement and posture measurement using remote technology systems in people with and without Axial spondylarthritis (axSpA).

METHODS

Validity and agreement of the remote-technology measurement of functional movement and posture were tested cross-sectionally and compared to a standard clinical measurement by a physiotherapist. The feasibility of remote implementation was tested in a home environment. There were two cohorts of participants: people with axSpA and people without longstanding back pain. In addition, a cost-consequence analysis was performed.

RESULTS

Sixty-two participants (31 with axSPA, 53% female, age = 45(SD14), BMI = 26.6(SD4.6) completed the study. In the axSpA group, cervical rotation, lumbar flexion, lumbar side flexion, shoulder flexion, hip abduction, tragus-to-wall and thoracic kyphosis showed a significant moderate to strong correlation; in the non-back pain group, the same measures showed significant correlation ranging from weak to strong.

CONCLUSIONS

Although not valid for clinical use in its current form, the remote technologies demonstrated moderate to strong correlation and agreement in most functional and postural tests measured in people with AxSA. Testing the CV-aided system in a home environment suggests it is a safe and feasible method. Yet, validity testing in this environment still needs to be performed.

A Wearable System Based on Multiple Magnetic and Inertial Measurement Units for Spine Mobility Assessment: A Reliability Study for the Evaluation of Ankylosing Spondylitis

Spinal mobility assessment is essential for the diagnostic of patients with ankylosing spondylitis. BASMI is a routine clinical evaluation of the spine; its measurements are made with goniometers and tape measures, implying systematic errors, subjectivity, and low sensitivity. Therefore, it is crucial to develop better mobility assessment methods. The design, implementation, and evaluation of a novel system for assessing the entire spine’s motion are presented. It consists of 16 magnetic and inertial measurement units (MIMUs) communicated wirelessly with a computer. The system evaluates the patient’s movements by implementing a sensor fusion of the triaxial gyroscope, accelerometer, and magnetometer signals using a Kalman filter. Fifteen healthy participants were assessed with the system through six movements involving the entire spine to calculate continuous kinematics and maximum range of motion (RoM). The intrarater reliability was computed over the observed RoM, showing excellent reliability levels (intraclass correlation >0.9) in five of the six movements. The results demonstrate the feasibility of the system for further clinical studies with patients. The system has the potential to improve the BASMI method. To the best of our knowledge, our system involves the highest number of sensors, thus providing more objective information than current similar systems.