## 4 Discussion
### Markers and Marker Size  
In this study we chose to use specific markers with a defined shape rather than a marker-less strategy using body edges for position determination. While there have been advances in marker-less motion capture technology, with evidence of viability for use in human movement biomechanics, marker-based motion capture has long been considered the gold standard for tracking human movement [28; 29]. The logic here was that markers \begin{table}
\begin{tabular}{l l l} \hline \hline
**Body Element** & **Flexibility** & **Specific Medical Use** \\ \hline \multirow{4}{*}{**Whole Body**} & Toe Touch & \\  & Sit and Reach & \\  & Schooler Test & Adams Forward Bend Test (Scoliosis) \\  & Side Bending Test & Lateral Bend Test \\  & Trunk Rotation Test & \\ \hline \multirow{4}{*}{**Large Body**} & \multirow{4}{*}{Back Scratch Test} & Hawkins-Kennedy Test (Shoulder) \\  & & Anterior Drawer Test (Knee-ACL) \\  & Shoulder-Neck Mobility & Apley’s Test (Knee-Meniscus) \\  & Back Scratch Test & Lachman’s Test (Knee-ACL) \\  & Straight Leg Raise & McMurray’s Test (Knee-Meniscus) \\  & Modified Thomas Test & Craig’s Test (Hip) \\  & & Thomas Test (Hip Flexion) \\  & Calf Muscle Flexibility Test & Trendelenburg Test (Hip Abduction) \\  & & Ober’s Test (IT Band) \\ \hline \multirow{4}{*}{**Regional Element/Digits**} & \multirow{4}{*}{Wrist Extension/Flexion} & Finger Abduction/Adduction \\  & & Temporomandibular Joint Movement \\ \cline{1-1}  & & Metacarpophalangeal Joint \\ \cline{1-1}  & & Ankle Extension/Flexion \\ \cline{1-1}  & Finger Extension/Flexion & Iterphaphalegal Joint Flexion/Extension \\ \cline{1-1}  & & Toe Extension/Flexion & Claw Test \\ \cline{1-1}  & & Finger Lift \\ \cline{1-1}  & & Thumb Movement \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Representative Application of MO\({}^{2}\)CA Based on Body Elements Measured. allow for uniform, reproducible target identification, as opposed to great variability that may be encountered with body contours and edges. This also simplified the computational algorithms needed for detection, with uniform marker-accurate identification being less complex and more reliable than body and body component detection. For example, as limits and complicates facial recognition software and marker-less software [27, 38]. In addition, a limitation of marker-based motion capture is generally cost, which we have been able to mitigate with the use of home products for marker construction and personal cell phones [28, 29]. Our choice of marker shape related to the ease of detection of edges, with simple shapes being more readily and accurately identifiable versus complex shapes [39, 40, 41]. Marker size was also selected based on camera resolution relative to the distance from the camera, as well as for inter-marker discrimination. We observed a clear relationship between the marker size and the effective system operating range, with a 10 mm marker affording a 300% increase in the operating distance of target to camera, compared to a 2 mm marker. A practical consideration of marker size relates to the simplicity of affixing a marker to a given body location as well as to the discrimination between markers. Our choice of 2 mm to 10 mm was arrived at by balancing accuracy, operating range, and practicality. To address the resolution and discrimination between markers we conducted the marker pair study, aimed at examining the translational utility of identifying differences in the extent of motion for closely situated digits, extremities, or body structures. As such, we tested a range of separation of 2 to 10 mm based on the anticipated use. For example, in the evaluation of range of motion of adjacent finger digits, smaller 2 mm markers are adequate without the marker obscuring movement or creating artifacts for visual detection. The finding that 2 mm marker pairs separated from 2 to 10 mm is accurately detected and discriminated, effectively up to 7.7 ft, reveals great opportunity for using this system in assessing finger and hand motion.