Thirty healthy young adults (20 males, 10 females, 22-35 years old), with no claim of medical history nor impairment in the upper limbs participated in this study. This study was approved by the institutional review board of our institution (2021-387). Estimated sample size was calculated by PASS software (version 15.0) using equivalence test for the difference between two means. With a type one error (a) of 0.05, power (1-b) of 0.95, equivalence limit of 10 degree, and standard deviation of 10, that a minimum of 27 samples would be required. All subjects were given full explanations about the motion tasks. After that, written consent was obtained for the use of their images for research purposes.
The measurement environment is shown in Supplementary Figure1A. Three commercial digital cameras (HIKIVISION DS-2CD3T56FWDV2-I3) were positioned around the field (one in the front and two in the sides). The height of the cameras was 1.5m and the distance between the camera and subjects was 3m. To ensure the consistency of the participant placement, feet markers were placed 3m away from the cameras.
Motion tasks and parameters extracting
We designed a 6-task procedure including shoulder abduction, shoulder elevation, elbow flexion, elbow extension, wrist flexion and extension (Shown in Supplementary Figure1B). To control the impact introduced by rotation, all the interest angles in our design were fully presented in either sagittal or coronal view. Participants were asked to stand in the field and perform the motion tasks one after another. To ensure their performances were the same as we recommended, we set a screen in front of participants with word and video instructions. Moreover, their motion videos were real-time displayed on that screen as well. All photographs were taken from the anterior side, except the elbow flexion was taken from the lateral side (one for each side).
The landmarks of each joint were estimated by the Openpose Human Pose Estimation library (version 1.5.0)(16). The coordinates for landmarks of joints were further extracted, and skeleton models were rebuilding accordingly. Then, the joint angle was calculated by corresponding coordinates.
Digital photography-based measurement
After the automatic measurement, the photography-based measurements were conducted by using the same images. The angle of joints was measured by two hand surgeons individually, applying a screen goniometer software to the images displayed on the computer screen (The main reason of screen-goniometry was to make sure the posture present to measurement system and human researchers were identical. The validity of this method have been previously confirmed(20, 21)). To minimize the uncertainty of manual assessment, these images were reassessed by the same researchers at an interval of one week. The landmarks included the center of the shoulder, elbow and wrist, axis along the center of the upper arm and forearm, and central axis along the metacarpals. During the measurement, observers were free to locate the landmarks after reading the instruction. During this procedure, observers were not allowed to see the results of automatic measurement or another observer's report.
Data processing and statistical analysis
The mean values of the four measurements (2 researchers * 2 round) were considered as the standard results for comparison. All measurements are presented as mean±standard deviation (means ± sd). The deviation between the automatic assessment and standard results and the 95% confidence interval (CI) were calculated to assess the accuracy. The intra-class correlation coefficient (ICC) was also performed between the standard and the proposed measurement for assessing the agreement. Next, the results were analyzed using Bland and Altman analysis(22). The upper limits of agreement (LOA) were considered reference values to judge if the proposed measurement could be a reliable method for upper limb ROM. Since it has been confirmed that the results were in complete agreement when using Openpose to analyze the same image twice, the repeatability of the automatic methods was not assessed. In comparison, the repeatability of manual measurement was evaluated by comparing the test-retest results. In addition, to confirm the validity, linear regression analyses were conducted to compare the manual and system measurement data. R-square was calculated to evaluate the correlation between different methods.
Statistical analysis was performed by SPSS 22.0 (Armonk, NY: IBM Corp) and R software 4.0.3 (R Foundation for Statistical Computing, Vienna, Austria). Results with p<0.05 were considered statistically significant. Interpretation of ICC value was as follows: <0.20: unacceptable, 0.20-0.40: questionable, 0.41-0.60: good, 0.61-0.80 very good, 0.81-1.00: excellent. The correlation coefficient, 1 indicates a total positive linear correlation, 0 means no linear correlation, and -1 shows a total negative linear correlation.