# A Low-Cost Soft Robotic Hand Exoskeleton for Use in Therapy of Limited Hand-Motor Function
## 3 Results  
Tests of the soft robotic exoskeleton were conducted to verify that the range of motion of the digits and the forces exerted at the fingertip coincide with those of a healthy human hand. The tests were conducted by first establishing a baseline for a healthy individual's natural range of motion shown in blue in the Figures 9-11 below and using the square symbol in the Figure 12 block and whiskers plot. The data was gathered from a Qualisys Miqus camera setup used for visual metrology and motion capture. The system consists of four high-resolution, high frame rate cameras and an array of visual markers placed on the DIP, PIP and MCP joints. Our experimental setup provides tracking information in real time at latencies close to 3 ms. Each test was performed for a duration of one second each,  
Figure 8: Control algorithm flow chart. Figure 7: Motor velocity control loop. where each finger would first curl and then uncurl. The duration of the test was selected to show the time needed to fully flex and relax each digit. The range of motion from the baseline data was then used as a control signal for the actuation of the soft robotic hand exoskeleton. The three figures below show the joint angles observed in the distal interphalangeal (DIP), proximal interphalangeal (PIP) and metacarpophalangeal (MCP) joints of a typical baseline healthy individual's index finger range of motion. As the controls of each digit and subsequent motor are fundamentally the same within our control algorithm, the following test results extend to all digits of the soft robotic hand exoskeleton, except for the thumb which only has a DIP and an MCP joint. Figure 10: Motion analysis data for the proximal interphalangeal (PIP) joint. Figure 9: Motion analysis data for the distal interphalangeal (DIP) joint. From Figure 9; Figure 10, it can be seen that the DIP and PIP joints track very closely to the control with a negligible relative error as compared to natural range of motion. This result is expected as our soft robotic exoskeleton is tendon-driven and the force exerted on the tendon, which is anchored at the top of the DIP joint, will move the DIP joint first, which is why the actuated DIP data follows the unactuated data immediately and closely. Figure 10 shows the tracking of the PIP joint and consequently from our previous argument, it was expected and observed that the while the tracking between the unactuated and actuated data is close, it follows with an initial delay of about 200 ms, while the movement of the DIP triggers movement in the PIP. Figure 11 shows the motion analysis data for the MCP joint, where the blue line represents the baseline range of motion of a healthy individual's hand and the red line shows the joint angle for the motor-manipulated finger and resulting joint angle in degrees for its MCP portion. As can be seen from the figure, the MCP joint did not track the control signal as closely as the PIP and DIP did. The error in tracking was at a maximum of six degrees and this again is a result of the soft tendon actuation affecting the MCP joint last. Figure 11: Motion analysis data for the metacarpophalangeal (MCP) joint. Figure 12: Finger force measured normal to fingertip. In addition to verifying the kinematic functionality of the design, the force exerted by the fingertips was measured for both an unactuated and fully actuated hand in order to determine if the design could be useful in helping patients to complete daily tasks. This data was collected using a test setup designed to keep the wrist and finger straight as the motors were actuated. A standard load cell was placed horizontally, while each fingertip of the hand was placed on top of it with the hand was fully extended. The force was then measured using the load cell placed parallel to the fingertip, measuring the normal force.