Reliability of a Smartphone Compared With an Inertial Sensor to Measure Shoulder Mobility: Cross-Sectional Study

Background The shoulder is one of the joints with the greatest mobility within the human body and its evaluation is complex. An assessment can be conducted using questionnaires or functional tests, and goniometry can complement the information obtained in this assessment. However, there are now validated devices that can provide more information on the realization of movement, such as inertial sensors. The cost of these devices is usually high and they are not available to all clinicians, but there are also inertial sensors that are implemented in mobile phones which are cheaper and widely available. Results from the inertial sensors integrated into mobile devices can have the same reliability as those from dedicated sensors. Objective This study aimed to validate the use of the Nexus 4 smartphone as a measuring tool for the mobility of the humerus during shoulder movement compared with a dedicated InertiaCube3 (Intersense) sensor. Methods A total of 43 subjects, 27 affected by shoulder pathologies and 16 asymptomatic, participated in the study. Shoulder flexion, abduction, and scaption were measured using an InertiaCube3 and a Nexus 4 smartphone, which were attached to the participants to record the results simultaneously. The interclass correlation coefficient (ICC) was calculated based on the 3 movements performed. Results The smartphone reliably recorded the velocity values and simultaneously recorded them alongside the inertial sensor. The ICCs of the 3 gestures and for each of the axes of movement were analyzed with a 95% CI. In the abduction movement, the devices demonstrated excellent interclass reliability for the abduction humeral movement axis (Cronbach alpha=.98). The axis of abduction of the humeral showed excellent reliability for the movements of flexion (Cronbach alpha=.93) and scaption (Cronbach alpha=.98). Conclusions Compared with the InertiaCube3, the Nexus 4 smartphone is a reliable and valid tool for recording the velocity produced in the shoulder.

[1]  J. Roy,et al.  Psychometric properties of self-reported questionnaires for the evaluation of symptoms and functional limitations in individuals with rotator cuff disorders: a systematic review , 2016, Disability and rehabilitation.

[2]  Antonio I Cuesta-Vargas,et al.  The use of inertial sensors system for human motion analysis , 2010, Physical therapy reviews : PTR.

[3]  Hsiaomin Huang,et al.  Use in Patients With Rotator Cuff Disease A Systematic Review of the Psychometric Properties of Patient-Reported Outcome Instruments for , 2015 .

[4]  R. Meeusen,et al.  Scapular positioning and movement in unimpaired shoulders, shoulder impingement syndrome, and glenohumeral instability , 2011, Scandinavian journal of medicine & science in sports.

[5]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.

[6]  Kamiar Aminian,et al.  Heightened clinical utility of smartphone versus body-worn inertial system for shoulder function B-B score , 2017, PloS one.

[7]  E. Bautz-Holter,et al.  A systematic review of measures of shoulder pain and functioning using the International classification of functioning, disability and health (ICF) , 2013, BMC Musculoskeletal Disorders.

[8]  S. Peiró,et al.  [Spanish version of the DASH questionnaire. Cross-cultural adaptation, reliability, validity and responsiveness]. , 2006, Medicina clinica.

[9]  Joseph M Hart,et al.  Validation of an innovative method of shoulder range-of-motion measurement using a smartphone clinometer application. , 2014, Journal of shoulder and elbow surgery.

[10]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

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

[12]  T. Russell,et al.  Assessment and Diagnosis of Musculoskeletal Shoulder Disorders over the Internet , 2012, International journal of telemedicine and applications.

[13]  A. Roby-Brami,et al.  Kinematic patterns in normal and degenerative shoulders. Part II: Review of 3-D scapular kinematic patterns in patients with shoulder pain, and clinical implications. , 2018, Annals of physical and rehabilitation medicine.

[14]  Nicolas Vuillerme,et al.  Performance Evaluation of Smartphone Inertial Sensors Measurement for Range of Motion , 2015, Sensors.

[15]  S. Peiró,et al.  Versión española del cuestionario DASH. Adaptación transcultural, fiabilidad, validez y sensibilidad a los cambios , 2006, Medicina Clínica.

[16]  Marco Donati,et al.  Ambulatory assessment of shoulder abduction strength curve using a single wearable inertial sensor. , 2015, Journal of rehabilitation research and development.

[17]  Anton Umek,et al.  Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications , 2016, Sensors.

[18]  Betty J. Smoot,et al.  RELIABILITY AND VALIDITY OF THE HALO DIGITAL GONIOMETER FOR SHOULDER RANGE OF MOTION IN HEALTHY SUBJECTS. , 2018, International Journal of Sports Physical Therapy.

[19]  Stephanie Morton,et al.  Reliability and validity of goniometric iPhone applications for the assessment of active shoulder external rotation , 2014, Physiotherapy theory and practice.

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

[21]  A. Cuesta-Vargas,et al.  Cross-cultural adaptation, reliability and validity of the Spanish version of the upper limb functional index , 2013, Health and Quality of Life Outcomes.

[22]  Lauren Beaupre,et al.  Evaluating change in clinical status: reliability and measures of agreement for the assessment of glenohumeral range of motion. , 2010, North American journal of sports physical therapy : NAJSPT.

[23]  M. Terry Medical Apps for Smartphones. , 2010, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[24]  Ann M Cools,et al.  Measuring shoulder external and internal rotation strength and range of motion: comprehensive intra-rater and inter-rater reliability study of several testing protocols. , 2014, Journal of shoulder and elbow surgery.

[25]  T. Russell Telerehabilitation: a coming of age. , 2009, The Australian journal of physiotherapy.

[26]  Giorgio Ferriero,et al.  Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools. , 2014, PM & R : the journal of injury, function, and rehabilitation.

[27]  T. Russell,et al.  Implications of regulatory requirements for smartphones, gaming consoles and other devices. , 2011, Journal of physiotherapy.

[28]  Joo Han Oh,et al.  Within-day reliability of shoulder range of motion measurement with a smartphone. , 2012, Manual therapy.

[29]  Margaret A. Finley,et al.  Three-dimensional analysis versus goniometric measurement of total active elevation in normal subjects. , 2015, Journal of shoulder and elbow surgery.

[30]  D. Theodoros,et al.  Telerehabilitation: current perspectives. , 2008, Studies in health technology and informatics.