case_images: PMC8226211_01
case_images: Anthropomorphic measurement photos. (A) Photo of the participant's non-affected (right) and affected (left) hand without the prosthetic hand. Measurements from the upper limbs were used to create a custom 3D printed prosthesis. (B) The 3D printed prosthetic hand used by the participant in this study. The prosthetic hand was modeled from the original design of the Cyborg Beast. (C) Sensitivity profile of the probe (Left and Right Hemispheres shown) used in this study. Log sensitivity index values closer to zero (red) reflect greater sensitivity for acquiring signals in that region (Aasted et al.,). Image created using AtlasViewer (v2.12.4). The location of the detectors (blue), the sources (red), and the channels (yellow lines) are shown for the subject. (D) B&B Task: Protocol of the study: 60 s of rest (red) followed by 60 s of the B&B task (blue). A total of 3 trials were conducted for the affected hand.
case_images: fnins-15-693138-g0001.jpg
case_images: PMC8226211_01_fnins-15-693138-g0001.jpg
case_images: F1
case_images: The subject evaluated was a 19-year-old female with a unilateral carpus upper limb reduction (ULD) of the left hand (Figure 1A). During the second visit (i.e., baseline), the prosthesis was fitted (Figure 1B) and baseline testing was conducted. The prosthesis was designed utilizing the measurements of the participant's affected and non-affected hand to create a symmetrically designed prosthetic hand (Figure 1B) (Zuniga et al.,). The cap was positioned on the head following the 10-20 international system (Klem et al.,) (Figure 1C). Test (Figure 1D) has been suggested as a measure of unilateral gross manual dexterity (Mathiowetz et al.,) and has been previously used to assess upper-limb prosthetic performance and motor learning (Mathiowetz et al.,; Dromerick et al.,; Young et al.,; Zuniga et al.,). The B&B task was performed during the first and last week of the home intervention.
case_images: Data analysis flow chart applied to each fNIRS channel. The data analysis utilizes two open source toolboxes: Homer3 (v1.26) and AtlasViewer (v2.12.4) Toolboxes. The Homer3 toolbox provides a user-friendly graphic user interface (GUI) that allows for the creation of easy-to-use data analysis pipelines and figures. The functions and parameters used in Homer3 are provided in the dashed black box. First, raw fNIRS signals were converted into changes in optical density data by taking the logarithm of the signal. Second, the changes in oxygenated-hemoglobin (DeltaHbO) concentrations were then obtained using the modified Beer-Lambert law with a partial pathlength factor of 1. Third, the hemodynamic response function (HRF) was then estimated by a general linear model (GLM) approach that uses iterative weighted least squares (Barker et al.,). Finally, figures were created using the AtlasViewer Toolbox, which provides an application for imaging and reconstruction of fNIRS data on atlas anatomy.
case_images: fnins-15-693138-g0002.jpg
case_images: PMC8226211_01_fnins-15-693138-g0002.jpg
case_images: F2
case_images: The data processing procedures are reported in Figure 2. The response was modeled using consecutive Gaussian temporal basis functions with a standard deviation of 0.5 s and with their means separated by 0.5 s over the regression time range of -2 to 35 s. This time period was chosen to include the full hemodynamic response to the task. beta-values were calculated during the GLM analysis and represent the weighted responses of the individual channels during the task compared to baseline levels.