Joint goniometry is a common mode of clinical assessment used in many disciplines, in particular rehabilitation [1-3]. One way to perform joint goniometry is through the use of computer-aided joint measurements from digital photographs [4-8]. This method entails a complex procedure to obtain the range of motion (ROM) value, which consists of the picture being manipulated upon by dedicated software once it has been downloaded from the camera to a computer. Recently, a new iPhone (Apple Inc, Cupertino, CA)-based application (app) functioning as a virtual goniometer, DrGoniometer (DrG; C.D.M. srl, Milano, Italy), has been developed to provide a simpler, faster measurement of limb joint mobility (Figure 1). Measurements with the DrG app are obtained by positioning a virtual goniometer, visible on the smartphone screen, on a picture previously taken by the mobile camera. The software creates an easily retrievable patient database. After selecting the patient, the clinician chooses the desired joint from a list and the respective motion to measure (eg, flexion, extension), then simply takes a photo of the limb, saves it, measures the joint angle, and observes the value. For research purposes, it is possible to blind the rater to the angular value. Notes can be added to each picture. The measurements and pictures are stored in the smartphone database for further analysis, if required. All data can be easily downloaded to a computer to obtain direct written reports. We assessed the reliability (intraand interrater correlation and agreements analysis) of DrG in comparison with a small plastic universal goniometer (UG) [1] for elbow ROM measurement [9]. Twenty-eight pictures of elbows of healthy subjects, measured by UG at different angles, were assessed with DrG by 7 raters, selected as expert clinicians and working in 2 different facilities. Measurements were repeated after 1 week. Each picture was judged adequate, that is, without evident perspective error. Raters were blinded to all joint angles values. The 392 measurements were used to assess: the intraclass correlation coefficient (ICC) for intrarater and interrater reliability [9]; and the agreement between the DrG and UG, considering 10° as the acceptable interval (width) within which 95% of differences between measurements by the DrG and UG are expected to lie (limits of agreement, LoA –5°, 5°) [10,11]. The results showed high intraand interrater correlation (ICC 0.998, 95% confidence interval 0.998-0.999, and ICC 0.998, 95% confidence interval 0.9960.999, respectively). The width of 95% LoA between DrG and UG was equal to 10.26° (LoA 4.51°, 5.75°). In a 1985 report, Fish and Wingate [2] assessed the accuracy of elbow goniometry by omparing a manual goniometer with (conventional) photographic measurements. They ound that the accuracy of elbow angle measurement via photography was greater than via he standard goniometer. The authors explained the difference by stating that the precision f the photographic method was dependent on the use of landmarks. However, the use of andmarks in everyday practice is uncommon, which is why we preferred not to place any abel on the limb to be measured [12]. More recently, Hoffmann et al [13] compared the UG measurement of an upper limb with that obtained by dedicated software that analyzed the still pictures of video images of the patients. Results showed that the investigators’ remote measurement method also had a high level of intraand interrater reliability for elbow goniometry (ICC 0.97) and a width of 95% LoA within 9.2°. DrG has shown a similar reliability to these photographic-based
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