## 2 Materials and Methods
### Hand Posture Data Acquisition and Processing  
CT scans of the participants' right hands in ten postures were captured by a radiologist at Pohang Stroke and Spine Hospital. The ten postures (postures 1 to 10; Figure 2) were selected from a natural hand motion starting from a fully extended posture (posture 1) and ending at a fist posture (posture 10) with a difference of approximately 10 degrees in flexion of the PIP joint of the index finger between two adjacent postures visually estimated by an experimenter. The difference of the PIP joint angles was not measured during the CT scan to avoid unnatural motions of the hand. The ten postures were sequentially scanned by a 256-slice CT scanner (Brilliance iCT; Philips Healthcare, Cleveland, OH, USA) while the participants were holding each of the postures. The participants were covered by a lead-free radiation shielding apron (FC001; Longkou Sanyi Medical Device Co., Ltd., Longkou, China) to protect them from radiation. For each posture, 576 to 670 CT slices, depending on the participants' hand sizes, were collected with a resolution of 512 \(\times\) 512 pixels and a thickness of 0.44 mm for each CT slice. A 3D hand skeleton was reconstructed using CT scans of each hand posture. First, the hand skin was excluded from a CT scan using a masking program developed by the Visualization Toolkit (VTK) [19], as shown in Figure 3a. Second, the hand skeleton was semi-automatically extracted from the masked CT scan by a threshold-based segmentation method provided in the Medical Imaging Interaction Toolkit (MITK) [20], as shown in Figure 3b. Lastly, the bones connected were separated from each other for the hand skeleton of posture 1 using a subtraction function in MITK, as shown in Figure 3c. After the separation of the bones, the hand skeleton of posture 1 consisted of 29 bones, including radius, ulna, eight carpal bones (hamate, pisiform, triquetral, lunate, scaphoid, capitate, trapezium, and trapezoid), five metacarpals, five proximal phalanges, four middle phalanges, and five distal phalanges. Each bone separated in the hand skeleton of posture 1 was exported as a file with the polygon (PLY) format by RapidForm 2006 (Inus Technology, Inc., Republic of Korea). Figure 2: Postures selected from a natural hand motion starting from a fully extended posture (posture 1) to a fist posture (posture 10) for the estimation of finite finger joint centers of rotation. To ensure all the hand skeletons at different postures have the same bone surfaces, the 29 bones in the hand skeleton of posture 1 (template posture) were registered to those in the hand skeletons of the other nine postures (target postures), as shown in Figure 4. First, each bone in the template posture was roughly registered to that in a target posture by aligning three points selected at a similar position, each from the template bone surface and the target bone surface (Figure 5a,b). Then, a fine registration (Figure 5c) was performed to precisely register the template bone to the target bone using the ICP algorithm [18]. The registration of the template bone to the target bone was conducted in RapidForm 2006. Table 1 shows the mean registration accuracy of the bones from posture 1 to each of the other nine postures measured by root mean square error (RMSE) of Hausdorff distance [21]. The registered hand skeletons of the other nine postures and the hand skeleton of posture 1 having the same bone surfaces were then used to find finite finger joint CoRs.