Shoulder Range of Motion: Validation of an Innovative Measurement Method Using a Smartphone

OBJECTIVES: An accurate and consistent measurement of shoulder range of motion (ROM) is of vital importance in the examination and functional evaluation of the shoulder. Classically, shoulder ROM is measured using a goniometer for research purposes, although clinically, visual estimation is typically utilized given its efficiency and providers’ lack of access to a goniometer.While visual estimation is likely sufficient for a single provider to follow a patient over time, it has been demonstrated to have very low interobserver reliability, especially for patients with pain or shoulder pathology. Current medical practice has led most orthopaedic surgeons to rely heavily on residents and physician assistants, especially in the clinic setting. Despite the importance of accurate and consistent measurement of shoulder ROM, a reliable and reproducible method of measurement for all levels of care providers does not exist. A widely-available and low-cost alternative for measurement of shoulder ROM is the Clinometer application (Plaincode Software Solutions) available inexpensively to all iPhone and smartphone users. Such a readily-available and accurate device could provide practicioners with a much simpler method for measuring shoulder ROM, as well as allowing physician extenders, primary care physicians and other non-orthopaedic trained physicians to easily obtain reproducible shoulder ROM measurements. The goal of this study is to establish the validity and reliability of shoulder ROM measurements amongst varying types of healthcare providers using the Clinometer application in healthy adult patients and compare these results to goniometry. METHODS: Examiners: One sports fellowship-trained orthopaedic surgeon, one current orthopaedic sports fellow, one orthopaedic resident physician, one orthopaedic physician assistant and one medical student. Subjects: Bilateral shoulders of twenty three healthy adult volunteer subjects, yielding 46 shoulders. Procedures: Each examiner first measured each subject using the iPhone clinometer, and then later repeated measurements using a standard goniometer. Abduction and forward flexion were measured with the patient standing. External rotation with the arm at the patient’s side, external rotation with the arm abducted at 90 degrees and internal rotation with the arm abducted at 90 degrees were measured with the patient supine. (Fig 1A-1E) Analysis: ICC(3,1) comparing iPhone measurements with goniometer measurements were calculated for each examiner. ICC(3,1) were also calculated comparing iPhone measurements with goniometer measurements across examiners for each measurement. RESULTS: ICC results are reported in Table IA-B. On average, examiners demonstrated good correlation (average ICC = 0.650) between their goniometer and iPhone measurements. Even better correlation was noted between examiners for each individual measure (average ICC = 0.721). CONCLUSION: Smartphones have good correlation with the “gold standard” goniometer for measuring shoulder range of motion. Additionally, there is good correlation amongst different levels of providers with measurements obtained using the smartphone. Given their wide availability and the low cost of measurement applications, smartphones are a good resource for shoulder range of motion measurement. Additional studies are underway to validate their use in post-operative and symptomatic patients.