Assessment of shoulder range of motion using a commercially available wearable sensor-a validation study

Effects of Different Inertial Measurement Unit Sensor-to-Segment Calibrations on Clinical 3-Dimensional Humerothoracic Joint Angles Estimation

Calibrating inertial measurement units (IMUs) involves converting orientation data from a local reference frame into a clinically meaningful reference system. Several solutions exist but little work has been done to compare different calibration methods with each other and an optical motion capture system. Thirteen healthy subjects with no signs of upper limb injury were recruited for this study and instrumented with IMU sensors and optical markers. Three IMU calibration methods were compared: N-pose calibration, functional calibration, and manual alignment. Subjects executed simple single-plane single-joint tasks for each upper limb joint as well as more complex multijoint tasks. We performed a 3-way analysis of variance on range of motion error, root mean squared error, and offset to assess differences between calibrations, tasks, and anatomical axes. Differences in the 3 IMU calibrations are minor and not statistically significant for most tasks and anatomical axes, with the exception of the offset interaction calibration × axes (P < .001, ηG2=.056). Specifically, manual alignment gives the best offset estimation on the abduction/adduction and internal/external rotation axes. Therefore, we recommend the use of a static N-pose calibration procedure as the preferred IMU calibration method to model the humerothoracic joint, as this setup is the simplest as it only requires accurate positioning of the trunk sensor.

Assessing the validity of a wearable shoulder motion tracking system through comparison with dartfish in patients undergoing shoulder joint replacement surgery

Objective assessments of shoulder motion are paramount for effective rehabilitation and evaluation of surgical outcomes. Inertial Measurement Units (IMU) have demonstrated promise in providing unbiased movement data. This study is dedicated to evaluating the concurrent construct validity and accuracy of a wearable IMU-based sensor system, called 'Motion Shirt', for the assessment of humero-thoracic motion arcs in patients awaiting shoulder replacement surgery. This evaluation was conducted by comparing Motion Shirt data with the Dartfish Motion Analyzer software during the Functional Impairment Test-Hand and Neck/Shoulder/Arm (FIT-HaNSA) test. Thirteen patients (age > 50), who were awaiting shoulder replacement surgery, were recruited. The Motion Shirt was employed to measure angular humero-thoracic movements in two planes during the FIT-HaNSA test. Simultaneously, two cameras recorded the participants' movements to provide reference data. Bland-Altman plots were generated to visualize agreement between the Motion Shirt and the reference data obtained from the Dartfish Motion Analyzer software. The data analysis on Bland-Altman plots revealed a substantial level of agreement between the Motion Shirt and Dartfish analysis in measuring humero-thoracic motion. In Task-1, no significant systematic errors were exhibited, with only 3.27% and 2.18% of points exceeding the limits of agreement (LOA) in both elevation and the Plane of Elevation (POE), signifying a high level of concordance. In Task-2, a high level of agreement was also observed in Elevation, with only 3.8% of points exceeding the LOA. However, 5.98% of points exceeded LOA in POE for Task-2. In Task-3, focused on sustained overhead activity, the Motion Shirt showed strong agreement with Dartfish in Elevation (2.44% points exceeded LOA), but in POE, 7.32% points exceeded LOA. The Motion Shirt demonstrated a robust concordance with Dartfish Motion Analyzer system in assessing humerothoracic motion during the FIT-HaNSA test. These results affirm the Motion Shirt's suitability for objective motion analysis in patients awaiting shoulder replacement surgery.

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.

Trends and Innovations in Wearable Technology for Motor Rehabilitation, Prediction, and Monitoring: A Comprehensive Review

(1) Background: Continuous health promotion systems are increasingly important, enabling decentralized patient care, providing comfort, and reducing congestion in healthcare facilities. These systems allow for treatment beyond clinical settings and support preventive monitoring. Wearable systems have become essential tools for health monitoring, but they focus mainly on physiological data, overlooking motor data evaluation. The World Health Organization reports that 1.71 billion people globally suffer from musculoskeletal conditions, marked by pain and limited mobility. (2) Methods: To gain a deeper understanding of wearables for the motor rehabilitation, monitoring, and prediction of the progression and/or degradation of symptoms directly associated with upper-limb pathologies, this study was conducted. Thus, all articles indexed in the Web of Science database containing the terms "wearable", "upper limb", and ("rehabilitation" or "monitor" or "predict") between 2019 and 2023 were flagged for analysis. (3) Results: Out of 391 papers identified, 148 were included and analyzed, exploring pathologies, technologies, and their interrelationships. Technologies were categorized by typology and primary purpose. (4) Conclusions: The study identified essential sensory units and actuators in wearable systems for upper-limb physiotherapy and analyzed them based on treatment methods and targeted pathologies.

Concurrent validity of inertial measurement units in range of motion measurements of upper extremity: A systematic review and meta-analysis

Inertial measurement units (IMUs) have proven to be valuable tools in measuring the range of motion (RoM) of human upper limb joints. Although several studies have reported on the validity of IMUs compared to the gold standard (optical motion capture system, OMC), a quantitative summary of the accuracy of IMUs in measuring RoM of upper limb joints is still lacking. Thus, the primary objective of this systematic review and meta-analysis was to determine the concurrent validity of IMUs for measuring RoM of the upper extremity in adults. Fifty-one articles were included in the systematic review, and data from 16 were pooled for meta-analysis. Concurrent validity is excellent for shoulder flexion-extension (Pearson's r = 0.969 [0.935, 0.986], ICC = 0.935 [0.749, 0.984], mean difference = -3.19 (p = 0.55)), elbow flexion-extension (Pearson's r = 0.954 [0.929, 0.970], ICC = 0.929 [0.814, 0.974], mean difference = 10.61 (p = 0.36)), wrist flexion-extension (Pearson's r = 0.974 [0.945, 0.988], mean difference = -4.20 (p = 0.58)), good to excellent for shoulder abduction-adduction (Pearson's r = 0.919 [0.848, 0.957], ICC = 0.840 [0.430, 0.963], mean difference = -7.10 (p = 0.50)), and elbow pronation-supination (Pearson's r = 0.966 [0.939, 0.981], ICC = 0.821 [0.696, 0.900]). There are some inconsistent results for shoulder internal-external rotation (Pearson's r = 0.939 [0.894, 0.965], mean difference = -9.13 (p < 0.0001)). In conclusion, the results support IMU as a viable instrument for measuring RoM of upper extremity, but for some specific joint movements, such as shoulder rotation and wrist ulnar-radial deviation, IMU measurements need to be used with caution.

Correlation Between Patient-Reported and Clinician-Measured Shoulder Range of Motion in Patients Undergoing Shoulder Surgery

INTRODUCTION

There has been increasing interest in remote measures of patients' health, both in the clinical and research settings. This study sought to evaluate correlations between patient-reported and clinician-measured (CM) shoulder range of motion (ROM).

METHODS

ROM measures including elevation, abduction, and internal rotation were recorded by a patient-reported picture-based survey and clinician measurement during each patient visit. A total of 13,842 visits over a 16-year period met inclusion criteria. Spearman correlation was performed to determine the correlation between patient-reported and CM elevation, abduction, and internal rotation. A subgroup analysis was conducted to evaluate motion in patients who underwent arthroplasty and arthroscopy.

RESULTS

Patients were 52.4% male with a median age of 67 years (range, 18 to 96). PR and CM shoulder ROM were gathered at 13,842 patient visits. Strong correlations between PR and CM elevation (r = 0.70) and internal rotation (r = 0.66) were found, as well as a moderate correlation between PR and CM abduction (r = 0.59). Strong correlations were found between all three PR and CM measures of motion in the arthroplasty subgroup (elevation r = 0.74, abduction r = 0.63, and internal rotation r = 0.64).

CONCLUSIONS

There is a strong correlation between patient-reported and CM shoulder elevation and internal rotation, as well as a moderate correlation between PR and CM abduction. This allows for a method of assessing patient motion without requiring an in-person visit.

LEVEL OF EVIDENCE

Level III Retrospective Cohort Study.

ISB recommendations on the definition, estimation, and reporting of joint kinematics in human motion analysis applications using wearable inertial measurement technology

There is widespread and growing use of inertial measurement technology for human motion analysis in biomechanics and clinical research. Due to advancements in sensor miniaturization, inertial measurement units can be used to obtain a description of human body and joint kinematics both inside and outside the laboratory. While algorithms for data processing continue to improve, a lack of standard reporting guidelines compromises the interpretation and reproducibility of results, which hinders advances in research and development of measurement and intervention tools. To address this need, the International Society of Biomechanics approved our proposal to develop recommendations on the use of inertial measurement units for joint kinematics analysis. A collaborative effort that incorporated feedback from the biomechanics community has produced recommendations in five categories: sensor characteristics and calibration, experimental protocol, definition of a kinematic model and subject-specific calibration, analysis of joint kinematics, and quality assessment. We have avoided an overly prescriptive set of recommendations for algorithms and protocols, and instead offer reporting guidelines to facilitate reproducibility and comparability across studies. In addition to a conceptual framework and reporting guidelines, we provide a checklist to guide the design and review of research using inertial measurement units for joint kinematics.

Assessing the Validity of the Ergotex IMU in Joint Angle Measurement: A Comparative Study with Optical Tracking Systems

An observational, repeated measures design was used in this study to assess the validity of the Ergotex Inertial Measurement Unit (IMU) against a 3D motion capture system for measuring trunk, hip, and shoulder angles in ten healthy adult males (38.8 ± 7.3 y, bodyweight 79.2 ± 115.9 kg, body height 179.1 ± 8.1 cm). There were minimal systematic differences between the devices, with the most significant discrepancy being 1.4 degrees for the 80-degree target angle, denoting Ergotex's precision in joint angle measurements. These results were statistically significant (p < 0.001), with predominantly trivial to small effect sizes, indicating high accuracy for clinical and biomechanical applications. Bland-Altman analysis showed Limits of Agreement (LoA) approximately ±2.5 degrees across all angles and positions, with overall LoA ranging from 3.6 to -2.4 degrees, reflecting Ergotex's consistent performance. Regression analysis indicated uniform variance across measurements, with minor heteroscedastic errors producing a negligible underestimation trend of around 0.5 degrees in some instances. In conclusion, the Ergotex IMU is a reliable tool for accurate joint angle measurements. It offers a practical and cost-effective alternative to more complex systems, particularly in settings where precise measurement is essential.

Wearables for Monitoring and Postural Feedback in the Work Context: A Scoping Review

Wearables offer a promising solution for simultaneous posture monitoring and/or corrective feedback. The main objective was to identify, synthesise, and characterise the wearables used in the workplace to monitor and postural feedback to workers. The PRISMA-ScR guidelines were followed. Studies were included between 1 January 2000 and 22 March 2023 in Spanish, French, English, and Portuguese without geographical restriction. The databases selected for the research were PubMed®, Web of Science®, Scopus®, and Google Scholar®. Qualitative studies, theses, reviews, and meta-analyses were excluded. Twelve studies were included, involving a total of 304 workers, mostly health professionals (n = 8). The remaining studies covered workers in the industry (n = 2), in the construction (n = 1), and welders (n = 1). For assessment purposes, most studies used one (n = 5) or two sensors (n = 5) characterised as accelerometers (n = 7), sixaxial (n = 2) or nonaxialinertial measurement units (n = 3). The most common source of feedback was the sensor itself (n = 6) or smartphones (n = 4). Haptic feedback was the most prevalent (n = 6), followed by auditory (n = 5) and visual (n = 3). Most studies employed prototype wearables emphasising kinematic variables of human movement. Healthcare professionals were the primary focus of the study along with haptic feedback that proved to be the most common and effective method for correcting posture during work activities.

Shoulder Range of Motion Measurement Using Inertial Measurement Unit-Concurrent Validity and Reliability

This study aimed to evaluate the reliability of the RSQ Motion sensor and its validity against the Propriometer and electronic goniometer in measuring the active range of motion (ROM) of the shoulder. The study included 15 volunteers (mean age 24.73 ± 3.31) without any clinical symptoms with no history of trauma, disease, or surgery to the upper limb. Four movements were tested: flexion, abduction, external and internal rotation. Validation was assessed in the full range of active shoulder motion. Reliability was revised in full active ROM, a fixed angle of 90 degrees for flexion and abduction, and 45 degrees for internal and external rotation. Each participant was assessed three times: on the first day by both testers and on the second day only by one of the testers. Goniometer and RSQ Motion sensors showed moderate to excellent correlation for all tested movements (ICC 0.61-0.97, LOA < 23 degrees). Analysis of inter-rater reliability showed good to excellent agreement between both testers (ICC 0.74-0.97, LOA 13-35 degrees). Analysis of intra-rater reliability showed moderate to a good agreement (ICC 0.7-0.88, LOA 22-37 degrees). The shoulder internal and external rotation measurement with RSQ Motion sensors is valid and reliable. There is a high level of inter-rater and intra-rater reliability for the RSQ Motion sensors and Propriometer.

Monitoring Scapular Kinematics through Wearable Magneto-Inertial Measurement Units: State of the Art and New Frontiers

Monitoring shoulder kinematics, including the scapular segment, is of great relevance in the orthopaedic field. Among wearable systems, magneto-inertial measurement units (M-IMUs) represent a valid alternative for applications in unstructured environments. The aim of this systematic literature review is to report and describe the existing methods to estimate 3D scapular movements through wearable systems integrating M-IMUs. A comprehensive search of PubMed, IEEE Xplore, and Web of Science was performed, and results were included up to May 2023. A total of 14 articles was included. The results showed high heterogeneity among studies regarding calibration procedures, tasks executed, and the population. Two different techniques were described, i.e., with the x-axis aligned with the cranial edge of the scapular spine or positioned on the flat surface of the acromion with the x-axis perpendicular to the scapular spine. Sensor placement affected the scapular motion and, also, the kinematic output. Further studies should be conducted to establish a universal protocol that reduces the variability among studies. Establishing a protocol that can be carried out without difficulty or pain by patients with shoulder musculoskeletal disorders could be of great clinical relevance for patients and clinicians to monitor 3D scapular kinematics in unstructured settings or during common clinical practice.

Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review

Inertial measurement units (IMUs) have become the mainstay in human motion evaluation outside of the laboratory; however, quantification of 3-dimensional upper limb motion using IMUs remains challenging. The objective of this systematic review is twofold. Firstly, to evaluate computational methods used to convert IMU data to joint angles in the upper limb, including for the scapulothoracic, humerothoracic, glenohumeral, and elbow joints; and secondly, to quantify the accuracy of these approaches when compared to optoelectronic motion analysis. Fifty-two studies were included. Maximum joint motion measurement accuracy from IMUs was achieved using Euler angle decomposition and Kalman-based filters. This resulted in differences between IMU and optoelectronic motion analysis of 4° across all degrees of freedom of humerothoracic movement. Higher accuracy has been achieved at the elbow joint with functional joint axis calibration tasks and the use of kinematic constraints on gyroscope data, resulting in RMS errors between IMU and optoelectronic motion for flexion-extension as low as 2°. For the glenohumeral joint, 3D joint motion has been described with RMS errors of 6° and higher. In contrast, scapulothoracic joint motion tracking yielded RMS errors in excess of 10° in the protraction-retraction and anterior-posterior tilt direction. The findings of this study demonstrate high-quality 3D humerothoracic and elbow joint motion measurement capability using IMUs and underscore the challenges of skin motion artifacts in scapulothoracic and glenohumeral joint motion analysis. Future studies ought to implement functional joint axis calibrations, and IMU-based scapula locators to address skin motion artifacts at the scapula, and explore the use of artificial neural networks and data-driven approaches to directly convert IMU data to joint angles.