Inertia based functional scoring of the shoulder in clinical practice

Differences in Tridimensional Shoulder Kinematics between Asymptomatic Subjects and Subjects Suffering from Rotator Cuff Tears by Means of Inertial Sensors: A Cross-Sectional Study

Background: The aim of this study was to analyze differences in three-dimensional shoulder kinematics between asymptomatic subjects and patients who were diagnosed with rotator cuff tears. Methods: This cross-sectional study recruited 13 symptomatic subjects and 14 asymptomatic subjects. Data were obtained from three inertial sensors placed on the humerus, scapula and sternum. Kinematic data from the glenohumeral, scapulothoracic and thoracohumeral joints were also calculated. The participants performed shoulder abductions and flexions. The principal angles of movements and resultant vectors in each axis were studied. Results: The glenohumeral joint showed differences in abduction (p = 0.001) and flexion (p = 0.000), while differences in the scapulothoracic joint were only significant during flexion (p = 0.001). The asymptomatic group showed higher velocity values in all sensors for both movements, with the differences being significant (p < 0.007). Acceleration differences were found in the scapula during abduction (p = 0.001) and flexion (p = 0.014), as well as in the sternum only during shoulder abduction (p = 0.022). Conclusion: The results showed kinematic differences between the patients and asymptomatic subjects in terms of the mobility, velocity and acceleration variables, with lower values for the patients.

Discriminating the precision of inertial sensors between healthy and damaged shoulders during scaption movement: A cross-sectional study

BACKGROUND

Shoulder assessment in rehabilitation is focused on kinematic properties due to the variability of symptomatology and clinical expression of shoulder injuries.

AIM

To perform a receiver operating characteristic analysis of the kinematic variables involved in the functional mobility of the shoulder that allow the identification of discriminating variables between healthy and diseased shoulders during scaption motion.

METHOD

Analytical cross-sectional study of diagnostic effectiveness was performed in 27 subjects suffering from shoulder damage and 14 asymptomatic controls. Scaption kinematics were evaluated using four inertial sensors placed on the humerus, scapula, forearm and sternum. Three variables (mobility, velocity and acceleration) were obtained from each sensor and the norm of the resultant vector was calculated from each axis. A discriminatory receiver operating characteristic analysis was performed, obtaining the area under the curve, sensitivity and specificity.

FINDINGS

Significant differences from both the resultant vectors and the axis depended on the body segment analysed were observed. Greater movement velocity and acceleration were observed in the asymptomatic group. Receiver operating characteristic analysis, scapular protraction-retraction mobility distinguished with a diagnostic sensitivity of 83.3% and specificity of 90.9% between asymptomatic and shoulder-damaged patients. These diagnosis values were 83.3% and 72.7% for scapular anterior-posterior velocity. Scapular kinematics, in terms of mobility and velocity, are the key variables in shoulder assessment.

INTERPRETATION

This study discriminated between patients suffering from shoulder damage and asymptomatic subjects based on shoulder kinematics during scaption motion. Scapular mobility and velocity were found to be key variables in shoulder assessment, along with the humerus.

Automatic Functional Shoulder Task Identification and Sub-task Segmentation Using Wearable Inertial Measurement Units for Frozen Shoulder Assessment

Advanced sensor technologies have been applied to support frozen shoulder assessment. Sensor-based assessment tools provide objective, continuous and quantitative information for evaluation and diagnosis. However, the current tools for assessment of functional shoulder tasks mainly rely on manual operation. It may cause several technical issues to the reliability and usability of the assessment tool, including manual bias during the recording and additional efforts for data labeling. To tackle these issues, this pilot study aims to propose an automatic functional shoulder task identification and sub-task segmentation system using inertial measurement units to provide reliable shoulder task labeling and sub-task information for clinical professionals. The proposed method combines machine learning models and rule-based modification to identify shoulder tasks and segment sub-tasks accurately. A hierarchical design is applied to enhance the efficiency and performance of the proposed approach. Nine healthy subjects and nine frozen shoulder patients are invited to perform five common shoulder tasks in the lab-based and clinical environments, respectively. The experimental results show that the proposed method can achieve 87.11% F-score for shoulder task identification, and 83.23% F-score and 427 mean absolute time errors (milliseconds) for sub-task segmentation. The proposed approach demonstrates the feasibility of the proposed method to support reliable evaluation for clinical assessment.

Adherence Tracking With Smart Watches for Shoulder Physiotherapy in Rotator Cuff Pathology: Protocol for a Longitudinal Cohort Study

Background

Physiotherapy is essential for the successful rehabilitation of common shoulder injuries and following shoulder surgery. Patients may receive some training and supervision for shoulder physiotherapy through private pay or private insurance, but they are typically responsible for performing most of their physiotherapy independently at home. It is unknown how often patients perform their home exercises and if these exercises are performed correctly without supervision. There are no established tools for measuring this. It is, therefore, unclear if the full benefit of shoulder physiotherapy treatments is being realized.

Objective

The proposed research will (1) validate a smartwatch and machine learning (ML) approach for evaluating adherence to shoulder exercise participation and technique in a clinical patient population with rotator cuff pathology; (2) quantify the rate of home physiotherapy adherence, determine the effects of adherence on recovery, and identify barriers to successful adherence; and (3) develop and pilot test an ethically conscious adherence-driven rehabilitation program that individualizes patient care based on their capacity to effectively participate in their home physiotherapy.

Methods

This research will be conducted in 2 phases. The first phase is a prospective longitudinal cohort study, involving 120 patients undergoing physiotherapy for rotator cuff pathology. Patients will be issued a smartwatch that will record 9-axis inertial sensor data while they perform physiotherapy exercises both in the clinic and in the home setting. The data collected in the clinic under supervision will be used to train and validate our ML algorithms that classify shoulder physiotherapy exercise. The validated algorithms will then be used to assess home physiotherapy adherence from the inertial data collected at home. Validated outcome measures, including the Disabilities of the Arm, Shoulder, and Hand questionnaire; Numeric Pain Rating Scale; range of motion; shoulder strength; and work status, will be collected pretreatment, monthly through treatment, and at a final follow-up of 12 months. We will then relate improvement in patient outcomes to measured physiotherapy adherence and patient baseline variables in univariate and multivariate analyses. The second phase of this research will involve the evaluation of a novel rehabilitation program in a cohort of 20 patients. The program will promote patient physiotherapy engagement via the developed technology and support adherence-driven care decisions.

Results

As of December 2019, 71 patients were screened for enrollment in the noninterventional validation phase of this study; 65 patients met the inclusion and exclusion criteria. Of these, 46 patients consented and 19 declined to participate in the study. Only 2 patients de-enrolled from the study and data collection is ongoing for the remaining 44.

Conclusions

This study will provide new and important insights into shoulder physiotherapy adherence, the relationship between adherence and recovery, barriers to better adherence, and methods for addressing them.

International Registered Report Identifier (IRRID)

DERR1-10.2196/17841

Instrumented assessment of shoulder function: A study of inertial sensor based methods

BACKGROUND

Inertial sensors have the potential to provide objective and practical methods to assess joint and limb function in the clinical setting. The aim of this study is to evaluate the psychometric properties of inertial sensor metrics in the assessment of patients with subacromial shoulder pain.

METHODS

25 patients with unilateral subacromial shoulder pain and 50 control subjects were recruited. Assessments were carried out on both shoulders for all participants during a short movement procedure. Patients had assessments repeated after receiving three months of physiotherapy. Inertial metrics evaluated included a smoothness measure and speed and power scores derived from the range of angular velocity and acceleration profiles. Individual shoulder scores and asymmetry scores were both evaluated in terms of reliability, known-group validity, convergent validity and responsiveness.

FINDINGS

Regression analysis identified age to be a significant predictor for all scores, therefore an age matched sub-cohort of control subjects was used for comparative analyses. All scores demonstrated inter-rater reliability (ICC = 0.48-0.82), were able to differentiate pathological from healthy shoulders (AUC = 0.62-0.91) and displayed significant changes following treatment. Scores derived from the range of acceleration and velocity profiles demonstrated the largest effect sizes (Cohens d = 0.8-1.35), and displayed the highest correlation with the Oxford Shoulder Score (r = -0.40 - -0.58).

INTERPRETATION

The scores investigated demonstrate good psychometric properties and have potential to complement existing methods of assessment in the clinical or research setting. Further work is required to fully understand their clinical relevance and optimise assessment methods and interpretation.

Assessment of abduction motion in patients with rotator cuff tears: an analysis based on inertial sensors

Background

Reduced range of motion in the shoulder can be a source of functional limitation. The use of inertial sensors to quantify movement in addition to more common clinical assessments of the shoulder may allow clinicians to understand that they are potentially unnoticed by visual identification. The aim of this study was to generate an explanatory model for shoulder abduction based on data from inertial sensors.

Method

A cross-sectional study was carried out to generate an explanatory model of shoulder abduction based on data from inertial sensors. Shoulder abduction of thirteen older adults suffering from shoulder dysfunction was recorded with two inertial sensors placed on the humerus and scapula. Movement variables (maximum angular mobility, angular peak of velocity, peak of acceleration) were used to explain the functionality of the upper limb assessed using the Upper Limb Functional Index (ULFI). The abduction movement of the shoulder was explained by six variables related to the mobility of the shoulder joint complex. A multivariate analysis of variance (MANOVA) was used to explain the results obtained on the functionality of the upper limb.

Results

The MANOVA model based on angular mobility explained 69% of the variance of the ULFI value (r-squared = 0.69). The most relevant variables were the abduction-adduction of the humerus and the medial/lateral rotation of the scapula.

Conclusions

The method used in the present study reveals the potential importance of the analysis of the scapular and humeral movements for comprehensive evaluation of the upper limb. Further research should include a wider sample and may seek to use this assessment technique in a range of potential clinical applications.

Wrist-Based Accelerometers and Visual Analog Scales as Outcome Measures for Shoulder Activity During Daily Living in Patients With Rotator Cuff Tendinopathy: Instrument Validation Study

BACKGROUND

Shoulder pain secondary to rotator cuff tendinopathy affects a large proportion of patients in orthopedic surgery practices. Corticosteroid injections are a common intervention proposed for these patients. The clinical evaluation of a response to corticosteroid injections is usually based only on the patient's self-evaluation of his function, activity, and pain by multiple questionnaires with varying metrological qualities. Objective measures of upper extremity functions are lacking, but wearable sensors are emerging as potential tools to assess upper extremity function and activity.

OBJECTIVE

This study aimed (1) to evaluate and compare test-retest reliability and sensitivity to change of known clinical assessments of shoulder function to wrist-based accelerometer measures and visual analog scales (VAS) of shoulder activity during daily living in patients with rotator cuff tendinopathy convergent validity and (2) to determine the acceptability and compliance of using wrist-based wearable sensors.

METHODS

A total of 38 patients affected by rotator cuff tendinopathy wore wrist accelerometers on the affected side for a total of 5 weeks. Western Ontario Rotator Cuff (WORC) index; Short version of the Disability of the Arm, Shoulder, and Hand questionnaire (QuickDASH); and clinical examination (range of motion and strength) were performed the week before the corticosteroid injections, the day of the corticosteroid injections, and 2 and 4 weeks after the corticosteroid injections. Daily Single Assessment Numeric Evaluation (SANE) and VAS were filled by participants to record shoulder pain and activity. Accelerometer data were processed to extract daily upper extremity activity in the form of active time; activity counts; and ratio of low-intensity activities, medium-intensity activities, and high-intensity activities.

RESULTS

Daily pain measured using VAS and SANE correlated well with the WORC and QuickDASH questionnaires (r=0.564-0.815) but not with accelerometry measures, amplitude, and strength. Daily activity measured with VAS had good correlation with active time (r=0.484, P=.02). All questionnaires had excellent test-retest reliability at 1 week before corticosteroid injections (intraclass correlation coefficient [ICC]=0.883-0.950). Acceptable reliability was observed with accelerometry (ICC=0.621-0.724), apart from low-intensity activities (ICC=0.104). Sensitivity to change was excellent at 2 and 4 weeks for all questionnaires (standardized response mean=1.039-2.094) except for activity VAS (standardized response mean=0.50). Accelerometry measures had low sensitivity to change at 2 weeks, but excellent sensitivity at 4 weeks (standardized response mean=0.803-1.032).

CONCLUSIONS

Daily pain VAS and SANE had good correlation with the validated questionnaires, excellent reliability at 1 week, and excellent sensitivity to change at 2 and 4 weeks. Daily activity VAS and accelerometry-derived active time correlated well together. Activity VAS had excellent reliability, but moderate sensitivity to change. Accelerometry measures had moderate reliability and acceptable sensitivity to change at 4 weeks.

Variations in glenohumeral movement control when implementing an auditory feedback system: A pilot study

Introduction: Human motor control requires a learning process and it can be trained by means of various sensory feedback sources.Objective: To determine variations in glenohumeral movement control by learning in young adults exposed to an auditory feedback system while they perform object translation tasks classified by difficulty level.Materials and methods: The study involved 45 volunteers of both sexes (22 women), aged between 18 and 32 years. Glenohumeral movement control was measured by means of the root mean square (RMS) of the accelerometry signal, while task execution speed (TES) was measured using an accelerometer during the execution of the task according to its difficulty (easy, moderate and hard) in four stages of randomized intervention (control, pre-exposure, exposure-with auditory feedback, and post-exposure).Results: Statistically significant differences (p<0.001) were found between the pre-exposure and exposure stages and between pre-exposure and post-exposure stages. A significant increase (p <0.001) in TES was identified between the pre-exposure and exposure stages for tasks classified as easy and hard, respectively.Conclusion: The use of an auditory feedback system in young adults without pathologies enhanced learning and glenohumeral movement control without reducing TES. This effect was maintained after the feedback, so the use of this type of feedback system in healthy individuals could result in a useful strategy for the training of motor control of the shoulder.

Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch

OBJECTIVE

Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders. However, adherence to these protocols is often poor and typically worse for unsupervised home exercise programs. Currently, there are limited tools available for objective measurement of adherence in the home setting. The goal of this study was to develop and evaluate the potential for performing home shoulder physiotherapy monitoring using a commercial smartwatch.

APPROACH

Twenty healthy adult subjects with no prior shoulder disorders performed seven exercises from an evidence-based rotator cuff physiotherapy protocol, while 6-axis inertial sensor data was collected from the active extremity. Within an activity recognition chain (ARC) framework, four supervised learning algorithms were trained and optimized to classify the exercises: k-nearest neighbor (k-NN), random forest (RF), support vector machine classifier (SVC), and a convolutional recurrent neural network (CRNN). Algorithm performance was evaluated using 5-fold cross-validation stratified first temporally and then by subject.

MAIN RESULTS

Categorical classification accuracy was above 94% for all algorithms on the temporally stratified cross validation, with the best performance achieved by the CRNN algorithm (99.4%). The subject stratified cross validation, which evaluated classifier performance on unseen subjects, yielded lower accuracies scores again with CRNN performing best (88.9%).

SIGNIFICANCE

This proof of concept study demonstrates the technical feasibility of a smartwatch device and supervised machine learning approach to more easily monitor and assess the at-home adherence of shoulder physiotherapy exercise protocols.

Shoulder assessment according to the international classification of functioning by means of inertial sensor technologies: A systematic review

This review investigates current protocols using Inertial Measurement Units (IMUs) in shoulder research, and outlines future paths regarding IMU use for shoulder research. Different databases were searched for relevant articles. Criteria for study selection were (1) research in healthy persons or persons with shoulder problems, (2) IMUs applied as assessment tool for the shoulder (in healthy subjects and shoulder patients) or upper limb (in shoulder patients), (3) peer-reviewed, full-text papers in English or Dutch. Studies with less than five participants and without ethical approval were excluded. Data extraction included (1) study design, (2) participant characteristics, (3) type/brand of IMU, (4) tasks included in the assessment protocol, and (5) outcomes. Risk of bias was assessed using the Downs and Black checklist. Scapulothoracic/glenohumeral and humerothoracic kinematics were reported in respectively 10 and 27 of the 37 included papers. Only one paper in healthy persons assessed, next to scapulothoracic/glenohumeral kinematics, other upper limb joints. IMUs' validity and reliability to capture shoulder function was limited. Considering applied protocols, 39% of the protocols was located on the International-Classification-of-Functioning (ICF) function level, while 38% and 23% were on the 'capacity' and 'actual performance'-sublevel, of the ICF-activity level. Most available IMU-research regarding the shoulder is clinically less relevant, given the widely reported humerothoracic kinematics which do not add to clinical-decision-making, and the absence of protocols assessing the complete upper limb chain. Apart from knowledge on methodological pitfalls and opportunities regarding the use of IMUs, this review provides future research paths.

Heightened clinical utility of smartphone versus body-worn inertial system for shoulder function B-B score

Background

The B-B Score is a straightforward kinematic shoulder function score including only two movements (hand to the Back + lift hand as to change a Bulb) that demonstrated sound measurement properties for patients for various shoulder pathologies. However, the B-B Score results using a smartphone or a reference system have not yet been compared. Provided that the measurement properties are comparable, the use of a smartphone would offer substantial practical advantages. This study investigated the concurrent validity of a smartphone and a reference inertial system for the measurement of the kinematic shoulder function B-B Score.

Methods

Sixty-five patients with shoulder conditions (with rotator cuff conditions, adhesive capsulitis and proximal humerus fracture) and 20 healthy participants were evaluated using a smartphone and a reference inertial system. Measurements were performed twice, alternating between two evaluators. The B-B Score differences between groups, differences between devices, relationship between devices, intra- and inter-evaluator reproducibility were analysed.

Results

The smartphone mean scores (SD) were 94.1 (11.1) for controls and 54.1 (18.3) for patients (P < 0.01). The difference between devices was non-significant for the control (P = 0.16) and the patient group (P = 0.81). The analysis of the relationship between devices showed 0.97 ICC, −0.6 bias and −13.2 to 12.0 limits of agreement (LOA). The smartphone intra-evaluator ICC was 0.92, the bias 1.5 and the LOA −17.4 to 20.3. The smartphone inter-evaluator ICC was 0.92, the bias 1.5 and the LOA −16.9 to 20.0.

Conclusions

The B-B Score results measured with a smartphone were comparable to those of an inertial system. While single measurements diverged in some cases, the intra- and inter-evaluator reproducibility was excellent and was equivalent between devices. The B-B score measured with a smartphone is straightforward and as efficient as a reference inertial system measurement.

Studying upper-limb kinematics using inertial sensors: a cross-sectional study

Background

In recent years, there has been a great interest in analyzing upper-limb kinematics in order to investigate scapulohumeral rhythm, as its alteration has been associated with shoulder joint complex injuries. The use of inertial sensors is presented as a convenient and portable analysis method for studying kinematics in terms of angular mobility and linear acceleration. The aim of this study was to analyze upper-limbs kinematics in the three anatomical axes, obtained by inertial sensors.

Results

Descriptive graphics of analytical tasks performed were obtained. The main difference in mobility between the scapula and humerus was found in pitch axis for abduction (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\bar{\text{X}}}$$\end{document}X¯ = 107.6°, SD = 9.3°) and flexion (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\bar{\text{X}}}$$\end{document}X¯ = 113.1°, SD = 9.3°).

Conclusion

The use of inertial sensors for human kinematics analysis is favorable. Although this study identified movement patterns, and supports inertial sensors as a useful device to analyze upper-limb kinematics, further studies with subjects with shoulder pathology to establish differences in movement patterns and scapulohumeral rhythm between healthy and pathological shoulders should be carried out.

Studying Upper-Limb Kinematics Using Inertial Sensors Embedded in Mobile Phones

BACKGROUND

In recent years, there has been a great interest in analyzing upper-limb kinematics. Inertial measurement with mobile phones is a convenient and portable analysis method for studying humerus kinematics in terms of angular mobility and linear acceleration.

OBJECTIVE

The aim of this analysis was to study upper-limb kinematics via mobile phones through six physical properties that correspond to angular mobility and acceleration in the three axes of space.

METHODS

This cross-sectional study recruited healthy young adult subjects. Humerus kinematics was studied in 10 young adults with the iPhone4. They performed flexion and abduction analytical tasks. Mobility angle and lineal acceleration in each of its axes (yaw, pitch, and roll) were obtained with the iPhone4. This device was placed on the right half of the body of each subject, in the middle third of the humerus, slightly posterior. Descriptive statistics were calculated.

RESULTS

Descriptive graphics of analytical tasks performed were obtained. The biggest range of motion was found in pitch angle, and the biggest acceleration was found in the y-axis in both analytical tasks. Focusing on tridimensional kinematics, bigger range of motion and acceleration was found in abduction (209.69 degrees and 23.31 degrees per second respectively). Also, very strong correlation was found between angular mobility and linear acceleration in abduction (r=.845) and flexion (r=.860).

CONCLUSIONS

The use of an iPhone for humerus tridimensional kinematics is feasible. This supports use of the mobile phone as a device to analyze upper-limb kinematics and to facilitate the evaluation of the patient.

Objective outcome evaluation using inertial sensors in subacromial impingement syndrome: a five-year follow-up study

Shoulder-related dysfunction is the second most common musculoskeletal disorder and is an increasing burden on health-care systems. Commonly used clinical questionnaires suffer from subjectivity, pain dominance and a ceiling effect. Objective functional measurement has been identified as a relevant issue in clinical rehabilitation. Inertia based motion analysis (IMA) is a new generation of objective outcome assessment tool; it can produce objective movement parameters while being fast, cheap and easy to operate. In this prospective study, an inertial sensor comprising a three-dimensional accelerometer and gyroscope is attached at the humerus to measure shoulder movements during two motion tasks in patients with subacromial impingement syndrome at baseline and at five-year after treatment. One hundred healthy subjects served as healthy reference database and 15 patients were measured pre- and post-treatment. IMA was better able to detect improvement in shoulder movements compared to the clinical questionnaires (Disability of Arm, Shoulder and Hand (DASH) and Simple Shoulder Test (SST); p < 0.05) and was hardly correlated with the clinical questionnaires (Pearson R = 0.39). It may therefore add an objective functional dimension to outcome assessment. The fast assessment (t < 5 min) of a simple motion test makes it suitable for routine clinical follow-up.