Measurement of Upper Limb Range of Motion Using Wearable Sensors: A Systematic Review

CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection

Sleep posture, a vital aspect of sleep wellness, has become a crucial focus in sleep medicine. Studies show that supine posture can lead to a higher occurrence of obstructive sleep apnea, while lateral posture might reduce it. For bedridden patients, frequent posture changes are essential to prevent ulcers and bedsores, highlighting the importance of monitoring sleep posture. This paper introduces CHMMConvScaleNet, a novel method for sleep posture recognition using pressure signals from limited piezoelectric ceramic sensors. It employs a Movement Artifact and Rollover Identification (MARI) module to detect critical rollover events and extracts multi-scale spatiotemporal features using six sub-convolution networks with different-length adjacent segments. To optimize performance, a Continuous Hidden Markov Model (CHMM) with rollover features is presented. We collected continuous real sleep data from 22 participants, yielding a total of 8583 samples from a 32-sensor array. Experiments show that CHMMConvScaleNet achieves a recall of 92.91%, precision of 91.87%, and accuracy of 93.41%, comparable to state-of-the-art methods that require ten times more sensors to achieve a slightly improved accuracy of 96.90% on non-continuous datasets. Thus, CHMMConvScaleNet demonstrates potential for home sleep monitoring using portable devices.

Key Fundamentals and Examples of Sensors for Human Health: Wearable, Non-Continuous, and Non-Contact Monitoring Devices

The increasing demand for personalized healthcare, particularly among individuals requiring continuous health monitoring, has driven significant advancements in sensor technology. Wearable, non-continuous monitoring, and non-contact sensors are leading this innovation, providing novel methods for monitoring vital signs and physiological data in both clinical and home settings. However, there is a lack of comprehensive comparative studies assessing the overall functionality of these technologies. This paper aims to address this gap by presenting a detailed comparative analysis of selected wearable, non-continuous monitoring, and non-contact sensors used for health monitoring. To achieve this, we conducted a comprehensive evaluation of various sensors available on the market, utilizing key indicators such as sensor performance, usability, associated platforms functionality, data management, battery efficiency, and cost-effectiveness. Our findings highlight the strengths and limitations of each sensor type, thus offering valuable insights for the selection of the most appropriate technology based on specific healthcare needs. This study has the potential to serve as a valuable resource for researchers, healthcare providers, and policymakers, contributing to a deeper understanding of existing user-centered health monitoring solutions.

Validity Analysis of Monocular Human Pose Estimation Models Interfaced with a Mobile Application for Assessing Upper Limb Range of Motion

Human Pose Estimation (HPE) is a computer vision application that utilizes deep learning techniques to precisely locate Key Joint Points (KJPs), enabling the accurate description of a person's pose. HPE models can be extended to facilitate Range of Motion (ROM) assessment by leveraging patient photographs. This study aims to evaluate and compare the performance of HPE models for assessing upper limbs ROM. A physiotherapist evaluated the degrees of ROM in shoulders (flexion, extension, and abduction) and elbows (flexion and extension) for fifty-two participants using both Universal Goniometer (UG) and five HPE models. Participants were instructed to repeat each movement three times to obtain measurements with the UG, then positioned while photos were captured using the NLMeasurer mobile application. The paired t-test, bias, and error measures were employed to evaluate the difference and agreement between measurement methods. Results indicated that the MoveNet Thunder INT16 model exhibited superior performance. Root Mean Square Errors obtained through this model were <10° in 8 of 10 analyzed movements. HPE models demonstrated better performance in shoulder flexion and abduction movements while exhibiting unsatisfactory performance in elbow flexion. Challenges such as image perspective distortion, environmental lighting conditions, images in monocular view, and complications in the pose may influence the models' performance. Nevertheless, HPE models show promise in identifying KJPs and facilitating ROM measurements, potentially enhancing convenience and efficiency in assessments. However, their current accuracy for this application is unsatisfactory, highlighting the need for caution when considering automated upper limb ROM measurement with them. The implementation of these models in clinical practice does not diminish the crucial role of examiners in carefully inspecting images and making adjustments to ensure measurement reliability.

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.

How do digital range of motion measurement devices 'measure-up' to traditional goniometry in assessing shoulder range of motion? A systematic review and meta-analysis

Background

Shoulder range of motion (ROM) is traditionally measured using universal goniometry. However, novel devices to measure shoulder ROM digitally are becoming increasingly available. We aimed to synthesise the current evidence to answer: 1) what technologies are currently in use? 2) Are they reliable? 3) How do they compare to goniometry?

Methods

Systematic review of the literature was conducted according to PRISMA guidelines. MEDLINE, Embase, CINAHL, Emcare and Cochrane databases were searched to identify studies comparing a digital device measuring shoulder ROM to goniometry in participants > = 18years. Quality of studies was assessed using COSMIN risk of bias tool. End points included device validity compared to goniometry and intra-rater reliability.

Results

15 articles were included, representing 372 participants and 608 shoulders, and reporting data for five device categories; infrared/RGB-D, 3D-motion-analysis, combined 3D/infra-red, 2D-video-analysis and virtual-reality. Nine studies reported mean bias and 95% limits of agreement (LOA) compared to goniometry. Pooled mean bias was -0.25 degrees (-1.25, 0.75 95% LOA, random effects model) overall. This did not differ by device type (p = 0.83), sensor or non-sensor-based devices (p = 0.62) or plane of movement (p = 0.91).

Conclusions

These devices compare well to goniometry and represent a possible means of increasing efficiency and facilitating telemedicine.

Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review From Designers' Perspective

BACKGROUND

Motion tracking technologies serve as crucial links between physical activities and health care insights, facilitating data acquisition essential for analyzing and intervening in physical activity. Yet, systematic methodologies for evaluating motion tracking data, especially concerning user activity recognition in health care applications, remain underreported.

OBJECTIVE

This study aims to systematically review motion tracking in daily living and physical activities, emphasizing the critical interaction among devices, users, and environments from a design perspective, and to analyze the process involved in health care application research. It intends to delineate the design and application intricacies in health care contexts, focusing on enhancing motion tracking data's accuracy and applicability for health monitoring and intervention strategies.

METHODS

Using a systematic review, this research scrutinized motion tracking data and their application in health care and wellness, examining studies from Scopus, Web of Science, EBSCO, and PubMed databases. The review used actor network theory and data-enabled design to understand the complex interplay between humans, devices, and environments within these applications.

RESULTS

Out of 1501 initially identified studies, 54 (3.66%) were included for in-depth analysis. These articles predominantly used accelerometer and gyroscope sensors (n=43, 80%) to monitor and analyze motion, demonstrating a strong preference for these technologies in capturing both dynamic and static activities. While incorporating portable devices (n=11, 20%) and multisensor configurations (n=16, 30%), the application of sensors across the body (n=15, 28%) and within physical spaces (n=17, 31%) highlights the diverse applications of motion tracking technologies in health care research. This diversity reflects the application's alignment with activity types ranging from daily movements to specialized scenarios. The results also reveal a diverse participant pool, including the general public, athletes, and specialized groups, with a focus on healthy individuals (n=31, 57%) and athletes (n=14, 26%). Despite this extensive application range, the focus primarily on laboratory-based studies (n=39, 72%) aimed at professional uses, such as precise activity identification and joint functionality assessment, emphasizes a significant challenge in translating findings from controlled environments to the dynamic conditions of everyday physical activities.

CONCLUSIONS

This study's comprehensive investigation of motion tracking technology in health care research reveals a significant gap between the methods used for data collection and their practical application in real-world scenarios. It proposes an innovative approach that includes designers in the research process, emphasizing the importance of incorporating data-enabled design framework. This ensures that motion data collection is aligned with the dynamic and varied nature of daily living and physical activities. Such integration is crucial for developing health applications that are accessible, intuitive, and tailored to meet diverse user needs. By leveraging a multidisciplinary approach that combines design, engineering, and health sciences, the research opens new pathways for enhancing the usability and effectiveness of health technologies.

Enhancing accuracy and convenience of golf swing tracking with a wrist-worn single inertial sensor

In this study, we address two technical challenges to enhance golf swing trajectory accuracy using a wrist-worn inertial sensor: orientation estimation and drift error mitigation. We extrapolated consistent sensor orientation from specific address-phase signal segments and trained the estimation with a convolutional neural network. We then mitigated drift error by applying a constraint on wrist speed at the address, backswing top, and finish, and ensuring that the wrist's finish displacement aligns with a virtual circle on the 3D swing plane. To verify the proposed methods, we gathered data from twenty male right-handed golfers, including professionals and amateurs, using a driver and a 7-iron. The orientation estimation error was about 60% of the baseline, comparable to studies requiring additional sensor information or calibration poses. The drift error was halved and the single-inertial-sensor tracking performance across all swing phases was about 17 cm, on par with multimodal approaches. This study introduces a novel signal processing method for tracking rapid, wide-ranging motions, such as a golf swing, while maintaining user convenience. Our results could impact the burgeoning field of daily motion monitoring for health care, especially with the increasing prevalence of wearable devices like smartwatches.

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.

Intraoperative Angle Measurement of Anatomical Structures: A Systematic Review

Ensuring precise angle measurement during surgical correction of orientation-related deformities is crucial for optimal postoperative outcomes, yet there is a lack of an ideal commercial solution. Current measurement sensors and instrumentation have limitations that make their use context-specific, demanding a methodical evaluation of the field. A systematic review was carried out in March 2023. Studies reporting technologies and validation methods for intraoperative angular measurement of anatomical structures were analyzed. A total of 32 studies were included, 17 focused on image-based technologies (6 fluoroscopy, 4 camera-based tracking, and 7 CT-based), while 15 explored non-image-based technologies (6 manual instruments and 9 inertial sensor-based instruments). Image-based technologies offer better accuracy and 3D capabilities but pose challenges like additional equipment, increased radiation exposure, time, and cost. Non-image-based technologies are cost-effective but may be influenced by the surgeon's perception and require careful calibration. Nevertheless, the choice of the proper technology should take into consideration the influence of the expected error in the surgery, surgery type, and radiation dose limit. This comprehensive review serves as a valuable guide for surgeons seeking precise angle measurements intraoperatively. It not only explores the performance and application of existing technologies but also aids in the future development of innovative solutions.

Concurrent Validity of the Ergotex Device for Measuring Low Back Posture

Highlighting the crucial role of monitoring and quantifying lumbopelvic rhythm for spinal curvature, the Ergotex IMU, a portable, lightweight, cost-effective, and energy-efficient technology, has been specifically designed for the pelvic and lumbar area. This study investigates the concurrent validity of the Ergotex device in measuring sagittal pelvic tilt angle. We utilized an observational, repeated measures design with healthy adult males (mean age: 39.3 ± 7.6 y, body mass: 82.2 ± 13.0 kg, body height: 179 ± 8 cm), comparing Ergotex with a 3D optical tracking system. Participants performed pelvic tilt movements in anterior, neutral, and posterior conditions. Statistical analysis included paired samples t-tests, Bland-Altman plots, and regression analysis. The findings show minimal systematic error (0.08° overall) and high agreement between the Ergotex and optical tracking, with most data points falling within limits of agreement of Bland-Altman plots (around ±2°). Significant differences were observed only in the anterior condition (0.35°, p < 0.05), with trivial effect sizes (ES = 0.08), indicating that these differences may not be clinically meaningful. The high Pearson's correlation coefficients across conditions underscore a robust linear relationship between devices (r > 0.9 for all conditions). Regression analysis showed a standard error of estimate (SEE) of 1.1° with small effect (standardized SEE < 0.26 for all conditions), meaning that the expected average deviation from the true value is around 1°. These findings validate the Ergotex as an effective, portable, and cost-efficient tool for assessing sagittal pelvic tilt, with practical implications in clinical and sports settings where traditional methods might be impractical or costly.

Upper limb modeling and motion extraction based on multi-space-fusion

Modeling and motion extraction of human upper limbs are essential for interpreting the natural behavior of upper limb. Owing to the high degrees of freedom (DOF) and highly dynamic nature, existing upper limb modeling methods have limited applications. This study proposes a generic modeling and motion extraction method, named Primitive-Based triangular body segment method (P-BTBS), which follows the physiology of upper limbs, allows high accuracy of motion angles, and describes upper-limb motions with high accuracy. For utilizing the upper-limb modular motion model, the motion angles and bones can be selected as per the research topics (The generic nature of the study targets). Additionally, P-BTBS is suitable in most scenarios for estimating spatial coordinates (The generic nature of equipment and technology). Experiments in continuous motions with seven DOFs and upper-limb motion description validated the excellent performance and robustness of P-BTBS in extracting motion information and describing upper-limb motions, respectively. P-BTBS provides a new perspective and mathematical tool for human understanding and exploration of upper-limb motions, which theoretically supports upper-limb research.

Assessing Spatiotemporal and Quality Alterations in Paretic Upper Limb Movements after Stroke in Routine Care: Proposal and Validation of a Protocol Using IMUs versus MoCap

Accurate assessment of upper-limb movement alterations is a key component of post-stroke follow-up. Motion capture (MoCap) is the gold standard for assessment even in clinical conditions, but it requires a laboratory setting with a relatively complex implementation. Alternatively, inertial measurement units (IMUs) are the subject of growing interest, but their accuracy remains to be challenged. This study aims to assess the minimal detectable change (MDC) between spatiotemporal and quality variables obtained from these IMUs and MoCap, based on a specific protocol of IMU calibration and measurement and on data processing using the dead reckoning method. We also studied the influence of each data processing step on the level of between-system MDC. Fifteen post-stroke hemiparetic subjects performed reach or grasp tasks. The MDC for the movement time, index of curvature, smoothness (studied through the number of submovements), and trunk contribution was equal to 10.83%, 3.62%, 39.62%, and 25.11%, respectively. All calibration and data processing steps played a significant role in increasing the agreement. The between-system MDC values were found to be lower or comparable to the between-session MDC values obtained with MoCap, meaning that our results provide strong evidence that using IMUs with the proposed calibration and processing steps can successfully and accurately assess upper-limb movement alterations after stroke in clinical routine care conditions.

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.

Shoulder Range of Motion Measurement Using Inertial Measurement Unit-Validation with a Robot Arm

The invention of inertial measurement units allowed the construction of sensors suitable for human motion tracking that are more affordable than expensive optical motion capture systems, but there are a few factors influencing their accuracy, such as the calibration methods and the fusion algorithms used to translate sensor readings into angles. The main purpose of this study was to test the accuracy of a single RSQ Motion sensor in comparison to a highly precise industrial robot. The secondary objectives were to test how the type of sensor calibration affects its accuracy and whether the time and magnitude of the tested angle have an impact on the sensor's accuracy. We performed sensor tests for nine repetitions of nine static angles made by the robot arm in eleven series. The chosen robot movements mimicked shoulder movements in a range of motion test (flexion, abduction, and rotation). The RSQ Motion sensor appeared to be very accurate, with a root-mean-square error below 0.15°. Furthermore, we found a moderate-to-strong correlation between the sensor error and the magnitude of the measured angle but only for the sensor calibrated with the gyroscope and accelerometer readings. Although the high accuracy of the RSQ Motion sensors was demonstrated in this paper, they require further study on human subjects and comparisons to the other devices known as the gold standards in orthopedics.

The swing performance Index: Developing a single-score index of golf swing rotational biomechanics quantified with 3D kinematics

Introduction

Golf swing generates power through coordinated rotations of the pelvis and upper torso, which are highly consistent among professionals. Currently, golf performance is graded on handicap, length-of-shot, and clubhead-speed-at-impact. No performance indices are grading the technique of pelvic and torso rotations. As an initial step toward developing a performance index, we collected kinematic metrics of swing rotational biomechanics and hypothesized that a set of these metrics could differentiate between amateur and pro players. The aim of this study was to develop a single-score index of rotational biomechanics based on metrics that are consistent among pros and could be derived in the future using inertial measurement units (IMU).

Methods

Golf swing rotational biomechanics was analyzed using 3D kinematics on eleven professional (age 31.0 ± 5.9 years) and five amateur (age 28.4 ± 6.9 years) golfers. Nine kinematic metrics known to be consistent among professionals and could be obtained using IMUs were selected as candidate variables. Oversampling was used to account for dataset imbalances. All combinations, up to three metrics, were tested for suitability for factor analysis using Kaiser-Meyer-Olkin tests. Principal component analysis was performed, and the logarithm of Euclidean distance of principal components between golf swings and the average pro vector was used to classify pro vs. amateur golf swings employing logistic regression and leave-one-out cross-validation. The area under the receiver operating characteristic curve was used to determine the optimal set of kinematic metrics.

Results

A single-score index calculated using peak pelvic rotational velocity pre-impact, pelvic rotational velocity at impact, and peak upper torso rotational velocity post-impact demonstrated strong predictive performance to differentiate pro (mean ± SD:100 ± 10) vs. amateur (mean ± SD:82 ± 4) golfers with an AUC of 0.97 and a standardized mean difference of 2.12.

Discussion

In this initial analysis, an index derived from peak pelvic rotational velocity pre-impact, pelvic rotational velocity at impact, and peak upper torso rotational velocity post-impact demonstrated strong predictive performance to differentiate pro from amateur golfers. Swing Performance Index was developed using a limited sample size; future research is needed to confirm results. The Swing Performance Index aims to provide quantified feedback on swing technique to improve performance, expedite training, and prevent injuries.

Validity and Reliability of Wearable Motion Sensors for Clinical Assessment of Shoulder Function in Brachial Plexus Birth Injury

The modified Mallet scale (MMS) is commonly used to grade shoulder function in brachial plexus birth injury (BPBI) but has limited sensitivity and cannot grade scapulothoracic and glenohumeral mobility. This study aims to evaluate if the addition of a wearable inertial movement unit (IMU) system could improve clinical assessment based on MMS. The system validity was analyzed with simultaneous measurements with the IMU system and an optical camera system in three asymptomatic individuals. Test-retest and interrater reliability were analyzed in nine asymptomatic individuals and six BPBI patients. IMUs were placed on the upper arm, forearm, scapula, and thorax. Peak angles, range of motion, and average joint angular speed in the shoulder, scapulothoracic, glenohumeral, and elbow joints were analyzed during mobility assessments and MMS tasks. In the validity tests, clusters of reflective markers were placed on the sensors. The validity was high with an error standard deviation below 3.6°. Intraclass correlation coefficients showed that 90.3% of the 69 outcome scores showed good-to-excellent test-retest reliability, and 41% of the scores gave significant differences between BPBI patients and controls with good-to-excellent test-retest reliability. The interrater reliability was moderate to excellent, implying that standardization is important if the patient is followed-up longitudinally.

Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review

Background

With the advent of smart sensing technology, mobile and wearable devices can provide continuous and objective monitoring and assessment of motor function outcomes.

Objective

We aimed to describe the existing scientific literature on wearable and mobile technologies that are being used or tested for assessing motor functions in mobility-impaired and healthy adults and to evaluate the degree to which these devices provide clinically valid measures of motor function in these populations.

Methods

A systematic literature review was conducted by searching Embase, MEDLINE, CENTRAL (January 1, 2015, to June 24, 2020), the United States and European Union clinical trial registries, and the United States Food and Drug Administration website using predefined study selection criteria. Study selection, data extraction, and quality assessment were performed by 2 independent reviewers.

Results

A total of 91 publications representing 87 unique studies were included. The most represented clinical conditions were Parkinson disease (n=51 studies), followed by stroke (n=5), Huntington disease (n=5), and multiple sclerosis (n=2). A total of 42 motion-detecting devices were identified, and the majority (n=27, 64%) were created for the purpose of health care–related data collection, although approximately 25% were personal electronic devices (eg, smartphones and watches) and 11% were entertainment consoles (eg, Microsoft Kinect or Xbox and Nintendo Wii). The primary motion outcomes were related to gait (n=30), gross motor movements (n=25), and fine motor movements (n=23). As a group, sensor-derived motion data showed a mean sensitivity of 0.83 (SD 7.27), a mean specificity of 0.84 (SD 15.40), a mean accuracy of 0.90 (SD 5.87) in discriminating between diseased individuals and healthy controls, and a mean Pearson r validity coefficient of 0.52 (SD 0.22) relative to clinical measures. We did not find significant differences in the degree of validity between in-laboratory and at-home sensor-based assessments nor between device class (ie, health care–related device, personal electronic devices, and entertainment consoles).

Conclusions

Sensor-derived motion data can be leveraged to classify and quantify disease status for a variety of neurological conditions. However, most of the recent research on digital clinical measures is derived from proof-of-concept studies with considerable variation in methodological approaches, and much of the reviewed literature has focused on clinical validation, with less than one-quarter of the studies performing analytical validation. Overall, future research is crucially needed to further consolidate that sensor-derived motion data may lead to the development of robust and transformative digital measurements intended to predict, diagnose, and quantify neurological disease state and its longitudinal change.

Biomechanics beyond the lab: Remote technology for osteoarthritis patient data-A scoping review

The objective of this project is to produce a review of available and validated technologies suitable for gathering biomechanical and functional research data in patients with osteoarthritis (OA), outside of a traditionally fixed laboratory setting. A scoping review was conducted using defined search terms across three databases (Scopus, Ovid MEDLINE, and PEDro), and additional sources of information from grey literature were added. One author carried out an initial title and abstract review, and two authors independently completed full-text screenings. Out of the total 5,164 articles screened, 75 were included based on inclusion criteria covering a range of technologies in articles published from 2015. These were subsequently categorised by technology type, parameters measured, level of remoteness, and a separate table of commercially available systems. The results concluded that from the growing number of available and emerging technologies, there is a well-established range in use and further in development. Of particular note are the wide-ranging available inertial measurement unit systems and the breadth of technology available to record basic gait spatiotemporal measures with highly beneficial and informative functional outputs. With the majority of technologies categorised as suitable for part-remote use, the number of technologies that are usable and fully remote is rare and they usually employ smartphone software to enable this. With many systems being developed for camera-based technology, such technology is likely to increase in usability and availability as computational models are being developed with increased sensitivities to recognise patterns of movement, enabling data collection in the wider environment and reducing costs and creating a better understanding of OA patient biomechanical and functional movement data.

Concurrent validity of DorsaVi wireless motion sensor system Version 6 and the Vicon motion analysis system during lifting

Background

Wearable sensor technology may allow accurate monitoring of spine movement outside a clinical setting. The concurrent validity of wearable sensors during multiplane tasks, such as lifting, is unknown. This study assessed DorsaVi Version 6 sensors for their concurrent validity with the Vicon motion analysis system for measuring lumbar flexion during lifting.

Methods

Twelve participants (nine with, and three without back pain) wore sensors on T12 and S2 spinal levels with Vicon surface markers attached to those sensors. Participants performed 5 symmetrical (lifting from front) and 20 asymmetrical lifts (alternate lifting from left and right). The global-T12-angle, global-S2-angle and the angle between these two sensors (relative-lumbar-angle) were output in the sagittal plane. Agreement between systems was determined through-range and at peak flexion, using multilevel mixed-effects regression models to calculate root mean square errors and standard deviation. Mean differences and limits of agreement for peak flexion were calculated using the Bland Altman method.

Results

For through-range measures of symmetrical lifts, root mean squared errors (standard deviation) were 0.86° (0.78) at global-T12-angle, 0.90° (0.84) at global-S2-angle and 1.34° (1.25) at relative-lumbar-angle. For through-range measures of asymmetrical lifts, root mean squared errors (standard deviation) were 1.84° (1.58) at global-T12-angle, 1.90° (1.65) at global-S2-angle and 1.70° (1.54) at relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of symmetrical lifts, was − 0.90° (-6.80 to 5.00) for global-T12-angle, 0.60° (-2.16 to 3.36) for global-S2-angle and − 1.20° (-8.06 to 5.67) for relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of asymmetrical lifts was − 1.59° (-8.66 to 5.48) for global-T12-angle, -0.60° (-7.00 to 5.79) for global-S2-angle and − 0.84° (-8.55 to 6.88) for relative-lumbar-angle.

Conclusion

The root means squared errors were slightly better for symmetrical lifts than they were for asymmetrical lifts. Mean differences and 95% limits of agreement showed variability across lift types. However, the root mean squared errors for all lifts were better than previous research and below clinically acceptable thresholds. This research supports the use of lumbar flexion measurements from these inertial measurement units in populations with low back pain, where multi-plane lifting movements are assessed.

A Comprehensive Analysis of the Validity and Reliability of the Perception Neuron Studio for Upper-Body Motion Capture

The Perception Neuron Studio (PNS) is a cost-effective and widely used inertial motion capture system. However, a comprehensive analysis of its upper-body motion capture accuracy is still lacking, before it is being applied to biomechanical research. Therefore, this study first evaluated the validity and reliability of this system in upper-body capturing and then quantified the system's accuracy for different task complexities and movement speeds. Seven participants performed simple (eight single-DOF upper-body movements) and complex tasks (lifting a 2.5 kg box over the shoulder) at fast and slow speeds with the PNS and OptiTrack (gold-standard optical system) collecting kinematics data simultaneously. Statistical metrics such as CMC, RMSE, Pearson's r, R², and Bland-Altman analysis were utilized to assess the similarity between the two systems. Test-retest reliability included intra- and intersession relations, which were assessed by the intraclass correlation coefficient (ICC) as well as CMC. All upper-body kinematics were highly consistent between the two systems, with CMC values 0.73-0.99, RMSE 1.9-12.5°, Pearson's r 0.84-0.99, R² 0.75-0.99, and Bland-Altman analysis demonstrating a bias of 0.2-27.8° as well as all the points within 95% limits of agreement (LOA). The relative reliability of intra- and intersessions was good to excellent (i.e., ICC and CMC were 0.77-0.99 and 0.75-0.98, respectively). The paired t-test revealed that faster speeds resulted in greater bias, while more complex tasks led to lower consistencies. Our results showed that the PNS could provide accurate enough upper-body kinematics for further biomechanical performance analysis.

Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor-software system: A validation study

Background and  Aims

Wearable inertial sensors may offer additional kinematic parameters of the shoulder compared to traditional instruments such as goniometers when elaborate and time-consuming data processing procedures are undertaken. However, in clinical practice simple-real time motion analysis is required to improve clinical reasoning. Therefore, the aim was to assess the criterion validity between a portable "off-the-shelf" sensor-software system (IMU) and optical motion (Mocap) for measuring kinematic parameters during active shoulder movements.

Methods

24 healthy participants (9 female, 15 male, age 29 ± 4 years, height 177 ± 11 cm, weight 73 ± 14 kg) were included. Range of motion (ROM), total range of motion (TROM), peak and mean angular velocity of both systems were assessed during simple (abduction/adduction, horizontal flexion/horizontal extension, vertical flexion/extension, and external/internal rotation) and complex shoulder movements. Criterion validity was determined using intraclass-correlation coefficients (ICC), root mean square error (RMSE) and Bland and Altmann analysis (bias; upper and lower limits of agreement).

Results

ROM and TROM analysis revealed inconsistent validity during simple (ICC: 0.040-0.733, RMSE: 9.7°-20.3°, bias: 1.2°-50.7°) and insufficient agreement during complex shoulder movements (ICC: 0.104-0.453, RMSE: 10.1°-23.3°, bias: 1.0°-55.9°). Peak angular velocity (ICC: 0.202-0.865, RMSE: 14.6°/s-26.7°/s, bias: 10.2°/s-29.9°/s) and mean angular velocity (ICC: 0.019-0.786, RMSE:6.1°/s-34.2°/s, bias: 1.6°/s-27.8°/s) were inconsistent.

Conclusions

The "off-the-shelf" sensor-software system showed overall insufficient agreement with the gold standard. Further development of commercial IMU-software-solutions may increase measurement accuracy and permit their integration into everyday clinical practice.

Biomechanical Assessment of Post-Stroke Patients' Upper Limb before and after Rehabilitation Therapy Based on FES and VR

Stroke is a medical condition characterized by the rapid loss of focal brain function. Post-stroke patients attend rehabilitation training to prevent the degeneration of physical function and improve upper limb movements and functional status after stroke. Promising rehabilitation therapies include functional electrical stimulation (FES), exergaming, and virtual reality (VR). This work presents a biomechanical assessment of 13 post-stroke patients with hemiparesis before and after rehabilitation therapy for two months with these three methods. Patients performed two tests (Maximum Forward Reach and Apley Scratching) where maximum angles, range of motion, angular velocities, and execution times were measured. A Wilcoxon test was performed (p = 0.05) to compare the variables before and after the therapy for paretic and non-paretic limbs. Significant differences were found in range of motion in flexion–extension, adduction–abduction, and internal–external rotation of the shoulder. Increases were found in flexion–extension, 17.98%, and internal–external rotation, 18.12%, after therapy in the Maximum Forward Reach Test. For shoulder adduction–abduction, the increase found was 20.23% in the Apley Scratching Test, supporting the benefits of rehabilitation therapy that combines FES, exergaming, and VR in the literature.

Validation of the Perception Neuron system for full-body motion capture

Recent advancements in Inertial Measurement Units (IMUs) offers the possibility of its use as a cost effective and portable alternative to traditional optoelectronic motion capture systems in analyzing biomechanical performance. One such commercially available IMU is the Perception Neuron motion capture system (PNS). The accuracy of the PNS had been tested and was reported to be a valid method for assessing the upper body range of motion to within 5° RMSE. However, testing of the PNS was limited to upper body motion involving functional movement within a single plane. Therefore, the purpose of this study is to further validate the Perception Neuron system with reference to a conventional optoelectronic motion capture system (VICON) through the use of dynamic movements (e.g., walking, jogging and a multi-articular sports movement with object manipulation) and to determine its feasibility through full-body kinematic analysis. Validation was evaluated using Pearson’s R correlation, RMSE and Bland-Altman estimates. Present findings suggest that the PNS performed well against the VICON motion analysis system with most joint angles reporting a RMSE of < 4° and strong average Pearson’s R correlation of 0.85, with the exception of the shoulder abduction/adduction where RMSE was larger and Pearson’s R correlation at a moderate level. Bland-Altman analysis revealed that most joint angles across the different movements had a mean bias of less than 10°, except for the shoulder abduction/adduction and elbow flexion/extension measurements. It was concluded that the PNS may not be the best substitute for traditional motion analysis technology if there is a need to replicate raw joint angles. However, there was adequate sensitivity to measure changes in joint angles and would be suitable when normalized joint angles are compared and the focus of analysis is to identify changes in movement patterns.

The Reliability of the Microsoft Kinect and Ambulatory Sensor-Based Motion Tracking Devices to Measure Shoulder Range-of-Motion: A Systematic Review and Meta-Analysis

Advancements in motion sensing technology can potentially allow clinicians to make more accurate range-of-motion (ROM) measurements and informed decisions regarding patient management. The aim of this study was to systematically review and appraise the literature on the reliability of the Kinect, inertial sensors, smartphone applications and digital inclinometers/goniometers to measure shoulder ROM. Eleven databases were screened (MEDLINE, EMBASE, EMCARE, CINAHL, SPORTSDiscus, Compendex, IEEE Xplore, Web of Science, Proquest Science and Technology, Scopus, and PubMed). The methodological quality of the studies was assessed using the consensus-based standards for the selection of health Measurement Instruments (COSMIN) checklist. Reliability assessment used intra-class correlation coefficients (ICCs) and the criteria from Swinkels et al. (2005). Thirty-two studies were included. A total of 24 studies scored "adequate" and 2 scored "very good" for the reliability standards. Only one study scored "very good" and just over half of the studies (18/32) scored "adequate" for the measurement error standards. Good intra-rater reliability (ICC > 0.85) and inter-rater reliability (ICC > 0.80) was demonstrated with the Kinect, smartphone applications and digital inclinometers. Overall, the Kinect and ambulatory sensor-based human motion tracking devices demonstrate moderate-good levels of intra- and inter-rater reliability to measure shoulder ROM. Future reliability studies should focus on improving study design with larger sample sizes and recommended time intervals between repeated measurements.

Monitoring daily shoulder activity before and after reverse total shoulder arthroplasty using inertial measurement units

BACKGROUND

The purpose of this study was to use at-home, portable, continuous monitoring technologies to record arm motion and activity preoperatively and postoperatively after reverse total shoulder arthroplasty (RTSA).

METHODS

Thirty-three patients indicated for RTSA were monitored preoperatively and 3 and 12 months postoperatively. Inertial measurement units were placed on the sternum and upper arm of the operative limb, recording humeral motion relative to the torso for the duration of a waking day. Elevation events per hour (EE/h) > 90°, time spent at >90°, and activity intensity were calculated and compared between time points. Patient-reported outcome measures were also collected at all time points.

RESULTS

At 3 (P = .040) and 12 (P = .010) months after RTSA, patients demonstrated a significantly greater number of EE/h > 90° compared with preoperatively. There were no significant differences (P ≥ .242) in the amount of time spent at different elevation angles at any time point or in arm activity intensity. Overall, 95% of the day was spent at elevation angles < 60°, and 90% of the day was spent in a low- or moderate-intensity state. Pearson correlations demonstrated relationships between forward elevation and the number of EE/h (r = 0.395, P = .001) and the number of EE/h > 90° (r = 0.493, P < .001).

CONCLUSION

After RTSA, patients significantly increase the frequency of arm elevation to higher angles. However, we found no differences in the amount of time spent at different elevation angles. Overall, after RTSA, >95% of the day was spent at elevation angles < 60° and <1% of the day was spent at >90° of elevation.

Inertial-Based Human Motion Capture: A Technical Summary of Current Processing Methodologies for Spatiotemporal and Kinematic Measures

Inertial-based motion capture (IMC) has been suggested to overcome many of the limitations of traditional motion capture systems. The validity of IMC is, however, suggested to be dependent on the methodologies used to process the raw data collected by the inertial device. The aim of this technical summary is to provide researchers and developers with a starting point from which to further develop the current IMC data processing methodologies used to estimate human spatiotemporal and kinematic measures. The main workflow pertaining to the estimation of spatiotemporal and kinematic measures was presented, and a general overview of previous methodologies used for each stage of data processing was provided. For the estimation of spatiotemporal measures, which includes stride length, stride rate, and stance/swing duration, measurement thresholding and zero-velocity update approaches were discussed as the most common methodologies used to estimate such measures. The methodologies used for the estimation of joint kinematics were found to be broad, with the combination of Kalman filtering or complimentary filtering and various sensor to segment alignment techniques including anatomical alignment, static calibration, and functional calibration methods identified as being most common. The effect of soft tissue artefacts, device placement, biomechanical modelling methods, and ferromagnetic interference within the environment, on the accuracy and validity of IMC, was also discussed. Where a range of methods have previously been used to estimate human spatiotemporal and kinematic measures, further development is required to reduce estimation errors, improve the validity of spatiotemporal and kinematic estimations, and standardize data processing practices. It is anticipated that this technical summary will reduce the time researchers and developers require to establish the fundamental methodological components of IMC prior to commencing further development of IMC methodologies, thus increasing the rate of development and utilisation of IMC.

Measures of Interjoint Coordination Post-stroke Across Different Upper Limb Movement Tasks

Background: Deficits in interjoint coordination, such as the inability to move out of synergy, are frequent symptoms in stroke subjects with upper limb impairments that hinder them from regaining normal motor function. Kinematic measurements allow a fine-grained assessment of movement pathologies, thereby complementing clinical scales, like the Fugl–Meyer Motor Assessment of the Upper Extremity (FMMA-UE). The study goal was to investigate the effects of the performed task, the tested arm, the dominant affected hand, upper limb function, and age on spatiotemporal parameters of the elbow, shoulder, and trunk. The construct validity of the metrics was examined by relating them with each other, the FMMA-UE, and its arm section.

Methods: This is a cross-sectional observational study including chronic stroke patients with mild to moderate upper limb motor impairment. Kinematic measurements were taken using a wearable sensor suit while performing four movements with both upper limbs: (1) isolated shoulder flexion, (2) pointing, (3) reach-to-grasp a glass, and (4) key insertion. The kinematic parameters included the joint ranges of shoulder abduction/adduction, shoulder flexion/extension, and elbow flexion/extension; trunk displacement; shoulder–elbow correlation coefficient; median slope; and curve efficiency. The effects of the task and tested arm on the metrics were investigated using a mixed-model analysis. The validity of metrics compared to clinically measured interjoint coordination (FMMA-UE) was done by correlation analysis.

Results: Twenty-six subjects were included in the analysis. The movement task and tested arm showed significant effects (p < 0.05) on all kinematic parameters. Hand dominance resulted in significant effects on shoulder flexion/extension and curve efficiency. The level of upper limb function showed influences on curve efficiency and the factor age on median slope. Relations with the FMMA-UE revealed the strongest and significant correlation for curve efficiency (r = 0.75), followed by shoulder flexion/extension (r = 0.68), elbow flexion/extension (r = 0.53), and shoulder abduction/adduction (r = 0.49). Curve efficiency additionally correlated significantly with the arm subsection, focusing on synergistic control (r = 0.59).

Conclusion: The kinematic parameters of the upper limb after stroke were influenced largely by the task. These results underpin the necessity to assess different relevant functional movements close to real-world conditions rather than relying solely on clinical measures.

Study Registration: clinicaltrials.gov, identifier NCT03135093 and BASEC-ID 2016-02075.

Quantifying Pathological Synergies in the Upper Extremity of Stroke Subjects With the Use of Inertial Measurement Units: A Pilot Study

BACKGROUND

Stroke is one of the main causes of disability in the world, causing loss of motor function on mainly one side of the body. A proper assessment of motor function is required to help to direct and evaluate therapy. Assessment is currently performed by therapists using observer-based standardized clinical assessment protocols. Sensor-based technologies can be used to objectively quantify the presence and severity of motor impairments in stroke patients.

METHODS

In this work, a minimally obstructive distributed inertial sensing system, intended to measure kinematics of the upper extremity, was developed and tested in a pilot study, where 10 chronic stroke subjects performed the arm-related tasks from the Fugl-Meyer Assessment protocol with the affected and non-affected side.

RESULTS

The pilot study showed that the developed distributed measurement system was adequately sensitive to show significant differences in stroke subjects' arm postures between the affected and non-affected side. The presence of pathological synergies can be analysed using the measured joint angles of the upper limb segments, that describe the movement patterns of the subject.

CONCLUSION

Features measured by the system vary from the assessed FMA-UE sub-score showing its potential to provide more detailed clinical information.

The Reliability and Validity of Wearable Inertial Sensors Coupled with the Microsoft Kinect to Measure Shoulder Range-of-Motion

Background: Objective assessment of shoulder joint active range of motion (AROM) is critical to monitor patient progress after conservative or surgical intervention. Advancements in miniature devices have led researchers to validate inertial sensors to capture human movement. This study investigated the construct validity as well as intra- and inter-rater reliability of active shoulder mobility measurements using a coupled system of inertial sensors and the Microsoft Kinect (HumanTrak). Methods: 50 healthy participants with no history of shoulder pathology were tested bilaterally for fixed and free ROM: (1) shoulder flexion, and (2) abduction using HumanTrak and goniometry. The repeat testing of the standardised protocol was completed after seven days by two physiotherapists. Results: All HumanTrak shoulder movements demonstrated adequate reliability (intra-class correlation (ICC) ≥ 0.70). HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.93 and 0.85) than goniometry (ICCs: 0.75 and 0.53) for measuring free shoulder flexion and abduction AROM, respectively. Similarly, HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.81 and 0.94) than goniometry (ICCs: 0.70 and 0.93) for fixed flexion and abduction AROM, respectively. Construct validity between HumanTrak and goniometry was adequate except for free abduction. The differences between raters were predominately acceptable and below ±10°. Conclusions: These results indicated that the HumanTrak system is an objective, valid and reliable way to assess and track shoulder ROM.

Wearable Health Devices in Health Care: Narrative Systematic Review

BACKGROUND

With the rise of mobile medicine, the development of new technologies such as smart sensing, and the popularization of personalized health concepts, the field of smart wearable devices has developed rapidly in recent years. Among them, medical wearable devices have become one of the most promising fields. These intelligent devices not only assist people in pursuing a healthier lifestyle but also provide a constant stream of health care data for disease diagnosis and treatment by actively recording physiological parameters and tracking metabolic status. Therefore, wearable medical devices have the potential to become a mainstay of the future mobile medical market.

OBJECTIVE

Although previous reviews have discussed consumer trends in wearable electronics and the application of wearable technology in recreational and sporting activities, data on broad clinical usefulness are lacking. We aimed to review the current application of wearable devices in health care while highlighting shortcomings for further research. In addition to daily health and safety monitoring, the focus of our work was mainly on the use of wearable devices in clinical practice.

METHODS

We conducted a narrative review of the use of wearable devices in health care settings by searching papers in PubMed, EMBASE, Scopus, and the Cochrane Library published since October 2015. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion.

RESULTS

A total of 82 relevant papers drawn from 960 papers on the subject of wearable devices in health care settings were qualitatively analyzed, and the information was synthesized. Our review shows that the wearable medical devices developed so far have been designed for use on all parts of the human body, including the head, limbs, and torso. These devices can be classified into 4 application areas: (1) health and safety monitoring, (2) chronic disease management, (3) disease diagnosis and treatment, and (4) rehabilitation. However, the wearable medical device industry currently faces several important limitations that prevent further use of wearable technology in medical practice, such as difficulties in achieving user-friendly solutions, security and privacy concerns, the lack of industry standards, and various technical bottlenecks.

CONCLUSIONS

We predict that with the development of science and technology and the popularization of personalized health concepts, wearable devices will play a greater role in the field of health care and become better integrated into people's daily lives. However, more research is needed to explore further applications of wearable devices in the medical field. We hope that this review can provide a useful reference for the development of wearable medical devices.

Design, Validity, and Reliability of a New Test, Based on an Inertial Measurement Unit System, for Measuring Cervical Posture and Motor Control in Children with Cerebral Palsy

OBJECTIVE

The aim of this study was to design and propose a new test based on inertial measurement unit (IMU) technology, for measuring cervical posture and motor control in children with cerebral palsy (CP) and to evaluate its validity and reliability.

METHODS

Twenty-four individuals with CP (4-14 years) and 24 gender- and age-matched controls were evaluated with a new test based on IMU technology to identify and measure any movement in the three spatial planes while the individual is seated watching a two-minute video. An ellipse was obtained encompassing 95% of the flexion/extension and rotation movements in the sagittal and transversal planes. The protocol was repeated on two occasions separated by 3 to 5 days. Construct and concurrent validity were assessed by determining the discriminant capacity of the new test and by identifying associations between functional measures and the new test outcomes. Relative reliability was determined using the intraclass correlation coefficient (ICC) for test-retest data. Absolute reliability was obtained by the standard error of measurement (SEM) and the Minimum Detectable Change at a 90% confidence level (MDC90).

RESULTS

The discriminant capacity of the area and both dimensions of the new test was high (Area Under the Curve ≈ 0.8), and consistent multiple regression models were identified to explain functional measures with new test results and sociodemographic data. A consistent trend of ICCs higher than 0.8 was identified for CP individuals. Finally, the SEM can be considered low in both groups, although the high variability among individuals determined some high MDC90 values, mainly in the CP group.

CONCLUSIONS

The new test, based on IMU data, is valid and reliable for evaluating posture and motor control in children with CP.

Assessment of Upper Limb Movement Impairments after Stroke Using Wearable Inertial Sensing

Precise and objective assessments of upper limb movement quality after strokes in functional task conditions are an important prerequisite to improve understanding of the pathophysiology of movement deficits and to prove the effectiveness of interventions. Herein, a wearable inertial sensing system was used to capture movements from the fingers to the trunk in 10 chronic stroke subjects when performing reach-to-grasp activities with the affected and non-affected upper limb. It was investigated whether the factors, tested arm, object weight, and target height, affect the expressions of range of motion in trunk compensation and flexion-extension of the elbow, wrist, and finger during object displacement. The relationship between these metrics and clinically measured impairment was explored. Nine subjects were included in the analysis, as one had to be excluded due to defective data. The tested arm and target height showed strong effects on all metrics, while an increased object weight showed effects on trunk compensation. High inter- and intrasubject variability was found in all metrics without clear relationships to clinical measures. Relating all metrics to each other resulted in significant negative correlations between trunk compensation and elbow flexion-extension in the affected arm. The findings support the clinical usability of sensor-based motion analysis.

Wearable Motion Sensor Device to Facilitate Rehabilitation in Patients With Shoulder Adhesive Capsulitis: Pilot Study to Assess Feasibility

BACKGROUND

Adhesive capsulitis (AC) of the shoulder is a common disorder that painfully reduces the shoulder range of motion (ROM) among middle-aged individuals. Although physical therapy with home-based exercises is widely advised to restore ROM in the treatment of AC, clinical results vary owing to inconsistent patient compliance.

OBJECTIVE

In this study, we aimed to verify the feasibility of a treatment model that involves applying a wearable motion sensor device to assist patients conduct home-based exercises to improve training compliance and the accuracy of exercises, with the ultimate goal of improving the functional recovery of patients with AC.

METHODS

The motion sensor device was comprised of inertial measurement unit-based sensors and mobile apps for patients and physicians, offering shoulder mobility tracing, home-based exercise support, and progress monitoring. The interrater reliability of shoulder mobility measurement using the motion sensor device on 10 healthy participants and 15 patients with AC was obtained using an intraclass correlation coefficient analysis and compared with the assessments performed by two highly experienced physicians. A pilot prospective control trial was then carried out to allocate the 15 patients with AC to two groups: home-based exercise group and motion sensor-assisted rehabilitation group. Changes in active and passive shoulder ROM, pain and functional scores, and exercise completion rates were compared between the groups during a treatment period of 3 months.

RESULTS

Shoulder ROM, as measured using the motion sensor device, exhibited good to excellent reliability based on the comparison with the measurements of two physicians (intraclass correlation coefficient range, 0.771 to 0.979). Compared with patients with AC in the home-based exercise group, those in the motion sensor-assisted rehabilitation group exhibited better shoulder mobility and functional recovery and a higher exercise completion rate during and after 3 months of rehabilitation.

CONCLUSIONS

Motion sensor device-assisted home-based rehabilitation for the treatment of AC is a useful treatment model for telerehabilitation that enhances the compliance of patients through training, thus improving functional recovery. This helps overcome important obstacles in physiotherapy at home by providing comprehensible and easily accessible exercise instructions, enhancing compliance, ensuring the correctness of exercise, and monitoring the progress of patients.

Determining anatomical frames via inertial motion capture: A survey of methods

Despite the exponential growth in using inertial measurement units (IMUs) for biomechanical studies, future growth in "inertial motion capture" is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. This paper systematically surveys a large number (N = 112) of studies from 2000 to 2018 that employ four broad categories of methods to address this challenge across a range of body segments and joints. We categorize these methods as: (1) Assumed Alignment methods, (2) Functional Alignment methods, (3) Model Based methods, and (4) Augmented Data methods. Assumed Alignment methods, which are simple and commonly used, require the researcher to visually align the IMU sense axes with the underlying anatomical axes. Functional Alignment methods, also commonly used, relax the need for visual alignment but require the subject to complete prescribed movements. Model Based methods further relax the need for prescribed movements but instead assume a model for the joint. Finally, Augmented Data methods shed all of the above assumptions, but require data from additional sensors. Significantly different estimates of the underlying anatomical axes arise both across and within these categories, and to a degree that renders it difficult, if not impossible, to compare results across studies. Consequently, a significant future need remains for creating and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology's potential for biomechanical studies.

Concurrent Validity and Reliability of an Inertial Measurement Unit for the Assessment of Craniocervical Range of Motion in Subjects with Cerebral Palsy

Objective: This study aimed to determine the validity and reliability of Inertial Measurement Units (IMUs) for the assessment of craniocervical range of motion (ROM) in patients with cerebral palsy (CP). Methods: twenty-three subjects with CP and 23 controls, aged between 4 and 14 years, were evaluated on two occasions, separated by 3 to 5 days. An IMU and a Cervical Range of Motion device (CROM) were used to assess craniocervical ROM in the three spatial planes. Validity was assessed by comparing IMU and CROM data using the Pearson correlation coefficient, the paired t-test and Bland–Altman plots. Intra-day and inter-day relative reliability were determined using the Intraclass Correlation Coefficient (ICC). The Standard Error of Measurement (SEM) and the Minimum Detectable Change at a 90% confidence level (MDC₉₀) were obtained for absolute reliability. Results: High correlations were detected between methods in both groups on the sagittal and frontal planes (r > 0.9), although this was reduced in the case of the transverse plane. Bland–Altman plots indicated bias below 5º, although for the range of cervical rotation in the CP group, this was 8.2º. The distance between the limits of agreement was over 23.5º in both groups, except for the range of flexion-extension in the control group. ICCs were higher than 0.8 for both comparisons and groups, except for inter-day comparisons of rotational range in the CP group. Absolute reliability showed high variability, with most SEM below 8.5º, although with worse inter-day results, mainly in CP subjects, with the MDC₉₀ of rotational range achieving more than 20º. Conclusions: IMU application is highly correlated with CROM for the assessment of craniocervical movement in CP and healthy subjects; however, both methods are not interchangeable. The IMU error of measurement can be considered clinically acceptable; however, caution should be taken when this is used as a reference measure for interventions.

Efficient Multiaxial Shoulder-Motion Tracking Based on Flexible Resistive Sensors Applied to Exosuits

This article describes the performance of a flexible resistive sensor network to track shoulder motion. This system monitors every gesture of the human shoulder in its range of motion except rotations around the longitudinal axis of the arm. In this regard, the design considers the movement of the glenohumeral, acromioclavicular, sternoclavicular, and scapulothoracic joints. The solution presented in this work considers several sensor configurations and compares its performance with a set of inertial measurement units (IMUs). These devices have been put together in a shoulder suit with Optitrack visual markers in order to be used as pose ground truth. Optimal configurations of flexible resistive sensors, in terms of accuracy requirements and number of sensors, have been obtained by applying principal component analysis techniques. The data provided by each configuration are then mapped onto the shoulder pose by using neural network algorithms. According to the results shown in this article, a set of flexible resistive sensors can be an adequate alternative to IMUs for multiaxial shoulder pose tracking in open spaces. Furthermore, the system presented can be easily embedded in fabric or wearable devices without obstructing the user's motion.

Development of a Post-stroke Upper Limb Rehabilitation Wearable Sensor for Use in Sub-Saharan Africa: A Pilot Validation Study

The development of context-appropriate sensor technologies could alleviate the significant burden of stroke in Sub-Saharan African rehabilitation clinicians and health care facilities. However, many commercially available wearable sensors are beyond the financial capabilities of the majority of African persons. In this study, we evaluated the concurrent validity of a low-cost wearable sensor (i.e., the outREACH sensor) to measure upper limb movement kinematics of 31 healthy persons, using an 8-camera Vicon motion capture system as the reference standard. The outREACH sensor showed high correlation (r range: 0.808-0.990) and agreement (mean difference range: -1.60 to 1.10) with the reference system regardless of task or kinematic parameter. Moreover, Bland-Altman analyses indicated that there were no significant systematic errors present. This study indicates that upper limb movement kinematics can be accurately measured using the outREACH sensor, and have the potential to enhance stroke evaluation and rehabilitation in sub-Saharan Africa.

Validity and Reliability of a New Optoelectronic System for Measuring Active Range of Motion of Upper Limb Joints in Asymptomatic and Symptomatic Subjects

The aim of this study was to evaluate the validity of the Veloflex infrared dynamic angle-meter (Veloflex-IDA) and the intra- and inter-rater reliability when measuring the ranges of motion (ROMs) of the upper limb joints. Thirty-five healthy and 20 symptomatic participants were evaluated. Twelve upper limb movements were measured in two sessions with the Veloflex-IDA, which is a device composed of a camera that tracks the trajectory of retro-reflective markers. In addition, a goniometer was used in the first session to evaluate concurrent validity. Validity and agreement were evaluated by Pearson correlation coefficient (r) and Bland-Altmann plots. Intra- and inter-rater reliability were evaluated using intra-class correlation (ICC), standard error of measurement (SEM), and minimal detectable change (MDC). Both instruments showed excellent correlation for all movements (r range from 0.992 to 0.999). The intra- and inter-rater reliability were excellent (ICC range from 0.95 to 0.99 and 0.90 to 0.98, respectively). Intra-rater reliability showed SEMs <1.38% and <5.19% and inter-rater reliability SEMs <2.26% and <5.22% for asymptomatic and symptomatic, respectively. Veloflex-IDA is a valid and reliable alternative to measure the upper limb joints' ROM and it can be used in clinical practice and research after basic training.

Does the Femoral Head Size in Hip Arthroplasty Influence Lower Body Movements during Squats, Gait and Stair Walking? A Clinical Pilot Study Based on Wearable Motion Sensors

A hip prosthesis design with larger femoral head size may improve functional outcomes compared to the conventional total hip arthroplasty (THA) design. Our aim was to compare the range of motion (RoM) in lower body joints during squats, gait and stair walking using a wearable movement analysis system based on inertial measurement units (IMUs) in three age-matched male groups: 6 males with a conventional THA (THAC), 9 with a large femoral head (LFH) design, and 8 hip- and knee-asymptomatic controls (CTRL). We hypothesized that the LFH design would allow a greater hip RoM, providing movement patterns more like CTRL, and a larger side difference in hip RoM in THAC when compared to LFH and controls. IMUs were attached to the pelvis, thighs and shanks during five trials of squats, gait, and stair ascending/descending performed at self-selected speed. THAC and LFH participants completed the Hip dysfunction and Osteoarthritis Outcome Score (HOOS). The results showed a larger hip RoM during squats in LFH compared to THAC. Side differences in LFH and THAC groups (operated vs. non-operated side) indicated that movement function was not fully recovered in either group, further corroborated by non-maximal mean HOOS scores (LFH: 83 ± 13, THAC: 84 ± 19 groups, vs. normal function 100). The IMU system may have the potential to enhance clinical movement evaluations as an adjunct to clinical scales.

Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review

Motion capture systems are recognized as the gold standard for joint angle calculation. However, studies using these systems are restricted to laboratory settings for technical reasons, which may lead to findings that are not representative of real-life context. Recently developed commercial and home-made inertial measurement sensors (M/IMU) are potentially good alternatives to the laboratory-based systems, and recent technology improvements required a synthesis of the current evidence. The aim of this systematic review was to determine the criterion validity and reliability of M/IMU for each body joint and for tasks of different levels of complexity. Five different databases were screened (Pubmed, Cinhal, Embase, Ergonomic abstract, and Compendex). Two evaluators performed independent selection, quality assessment (consensus-based standards for the selection of health measurement instruments [COSMIN] and quality appraisal tools), and data extraction. Forty-two studies were included. Reported validity varied according to task complexity (higher validity for simple tasks) and the joint evaluated (better validity for lower limb joints). More studies on reliability are needed to make stronger conclusions, as the number of studies addressing this psychometric property was limited. M/IMU should be considered as a valid tool to assess whole body range of motion, but further studies are needed to standardize technical procedures to obtain more accurate data.