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.

[1]  J. Iannotti,et al.  Intrarater and interrater reliability of three isometric dynamometers in assessing shoulder strength. , 1996, Journal of shoulder and elbow surgery.

[2]  C. Littlewood,et al.  Exercise for rotator cuff tendinopathy: a systematic review. , 2012, Physiotherapy.

[3]  J. García-Alsina,et al.  Angular position, range of motion and velocity of arm elevation: a study of consistency of performance. , 2005, Clinical biomechanics.

[4]  Annick Timmermans,et al.  Shoulder assessment according to the international classification of functioning by means of inertial sensor technologies: A systematic review. , 2017, Gait & posture.

[5]  G. Stelmach,et al.  Movement accuracy constraints in Parkinson’s disease patients , 2000, Neuropsychologia.

[6]  A. Carr,et al.  Shoulder pain: diagnosis and management in primary care , 2005, BMJ : British Medical Journal.

[7]  L M Bouter,et al.  Shoulder disorders in general practice: incidence, patient characteristics, and management. , 1995, Annals of the rheumatic diseases.

[8]  G E Stelmach,et al.  Stability of reach-to-grasp movement patterns in Parkinson's disease. , 1997, Brain : a journal of neurology.

[9]  K. Aminian,et al.  Enhancing clinically-relevant shoulder function assessment using only essential movements , 2015, Physiological measurement.

[10]  Terry K Koo,et al.  A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. , 2016, Journal Chiropractic Medicine.

[11]  N. Klopcar,et al.  Bilateral and unilateral shoulder girdle kinematics during humeral elevation. , 2006, Clinical biomechanics.

[12]  William D Middleton,et al.  The demographic and morphological features of rotator cuff disease. A comparison of asymptomatic and symptomatic shoulders. , 2006, The Journal of bone and joint surgery. American volume.

[13]  Jeffrey M. Hausdorff,et al.  SPARC: a new approach to quantifying gait smoothness in patients with Parkinson’s disease , 2018, Journal of NeuroEngineering and Rehabilitation.

[14]  F C T van der Helm,et al.  Requirements for upper extremity motions during activities of daily living. , 2005, Clinical biomechanics.

[15]  Kristin R Archer,et al.  Frequency and cost of claims by injury type from a state workers' compensation fund from 1998 through 2008. , 2014, Archives of physical medicine and rehabilitation.

[16]  Kamiar Aminian,et al.  Measuring upper limb function in children with hemiparesis with 3D inertial sensors , 2017, Child's Nervous System.

[17]  Diego Torricelli,et al.  Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: A review. , 2014, Clinical biomechanics.

[18]  Ilaria Carpinella,et al.  Robot-based rehabilitation of the upper limbs in multiple sclerosis: feasibility and preliminary results. , 2009, Journal of rehabilitation medicine.

[19]  Jaap Harlaar,et al.  Complete 3D kinematics of upper extremity functional tasks. , 2008, Gait & posture.

[20]  K. McGraw,et al.  Forming inferences about some intraclass correlation coefficients. , 1996 .

[21]  Andrea Giovanni Cutti,et al.  Shoulder biomechanics and the success of translational research , 2014, Medical & Biological Engineering & Computing.

[22]  Michelle Urwin,et al.  Estimating the burden of musculoskeletal disorders in the community: the comparative prevalence of symptoms at different anatomical sites, and the relation to social deprivation , 1998, Annals of the rheumatic diseases.

[23]  W. Nakano,et al.  Smoothness of the knee joint movement during the stance phase in patients with severe knee osteoarthritis , 2018, Asia-Pacific journal of sports medicine, arthroscopy, rehabilitation and technology.

[24]  Kamiar Aminian,et al.  Measurement Properties of the Smartphone-Based B-B Score in Current Shoulder Pathologies , 2015, Sensors.

[25]  S. Freter,et al.  Relationship between timed ‘up and go’ and gait time in an elderly orthopaedic rehabilitation population , 2000, Clinical rehabilitation.

[26]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[27]  Kamiar Aminian,et al.  Outcome evaluation in shoulder surgery using 3D kinematics sensors. , 2007, Gait & posture.

[28]  F C T van der Helm,et al.  A kinematical analysis of the shoulder after arthroplasty during a hair combing task. , 2006, Clinical biomechanics.

[29]  Joachim Hermsdörfer,et al.  Smoothness Metrics in Complex Movement Tasks , 2018, Front. Neurol..

[30]  C. Terwee,et al.  Self-reported physical functioning was more influenced by pain than performance-based physical functioning in knee-osteoarthritis patients. , 2006, Journal of clinical epidemiology.

[31]  P. Stratford,et al.  Assessing stability and change of four performance measures: a longitudinal study evaluating outcome following total hip and knee arthroplasty , 2005, BMC musculoskeletal disorders.

[32]  J. Brox,et al.  Agreement, reliability and validity in 3 shoulder questionnaires in patients with rotator cuff disease , 2008, BMC musculoskeletal disorders.

[33]  Etienne Burdet,et al.  A Robust and Sensitive Metric for Quantifying Movement Smoothness , 2012, IEEE Transactions on Biomedical Engineering.

[34]  Objective outcome evaluation using inertial sensors in subacromial impingement syndrome: a five-year follow-up study. , 2014, Physiological measurement.

[35]  B Grimm,et al.  Inertia based functional scoring of the shoulder in clinical practice. , 2014, Physiological measurement.