Robotically quantifying finger and ankle proprioception: Role of range, speed, anticipatory errors, and learning.

Proprioception plays a key role in motor control and stroke recovery. Robotic devices are increasingly being used to improve proprioceptive assessments, but there is a lack of knowledge about how programmable factors such as testing range, speed, and prior exposure affect tests. From a physiological standpoint, such factors may regulate the sensitivity of limb proprioceptors, thereby influencing assessment results when not controlled for. To determine the relative influence of such factors, we studied the Crisscross proprioceptive assessment, a recently developed robotic assessment that requires participants to indicate when two joints pass by each other as they are moved passively by the robot. We implemented Crisscross with novel robots for the fingers and ankles and tested young unimpaired participants in single sessions (N = 16) and longitudinally (N = 5, across 15-30 sessions over 3-10 weeks). In single-session testing, we found that proprioceptive acuity was better for the fingers than the ankle (p < 0.01). For both limbs, acuity improved near the ends of the range of motion, which may be due to greater involvement of load and joint receptors. Acuity was poorer for slower movements due to greater anticipatory errors. These results show how the range and speed selected for a proprioceptive test affect proprioceptive acuity and highlight the heightened role of anticipatory errors at slow speeds. Improvements in proprioceptive acuity were not detectable in a single session, but acuity improved across multiple testing sessions (p < 0.01). This result shows that multiple prior exposure over at least several days can affect acuity.Clinical Relevance- Proprioceptive assessments should account for range and speed, which could be enabled by leveraging robotics technology. Proprioceptive acuity can be improved through repeated testing, an observation that is relevant to proprioceptive rehabilitation as well.

Proprioceptive Gaming: Making Finger Sensation Training Intense and Engaging with the P-Pong Game and PINKIE Robot.

Proprioceptive deficits are common after a stroke and are thought to negatively impact motor learning. Despite this, there is a lack of practical robotic devices for assessing proprioception, as well as few robotic rehabilitation techniques that intensely and engagingly target proprioception. This work first presents the design of a simple robotic device, PINKIE, developed to assess and train finger proprioception. PINKIE uses low-cost actuators and sensors and is fabricated completely from 3D printed, laser cut, and off-the-shelf components. We then describe the design and testing of a gamified proprioceptive training technique, Proprioceptive-Pong (P-Pong), implemented with PINKIE. In P-Pong, players must continuously make game decisions based on sensed index and middle finger positions, as the game robotically moves their fingers instead of screen pixels to express the motion of the ball and paddle. We also report the results of a pilot study in which we investigated the effect of a short bout of P-Pong play on proprioceptive acuity, and quantified user engagement and intrinsic motivation of game play. We randomly assigned 15 unimpaired human participants to play 15 minutes of P-Pong (proprioceptive training group) or a similar but video-only version of Pong (control group). We assessed finger proprioception acuity before and after game play using the Crisscross assessment previously developed by our laboratory, engagement using the User Engagement Scale, and motivation using the Intrinsic Motivation Inventory survey. Following game play, there was a significant improvement in proprioceptive acuity (2.2 ± 2.6 SD mm, p = 0.023) in the proprioceptive training group but not the control group (0.5 ± 0.9 SD mm, p = 0.101). Participants rated P-Pong highly on all survey subscales, and as highly as visual Pong, except in the Perceived Usability and Competence subscales, a finding we discuss. To our knowledge, this work presents the first computer gaming approach for providing intense and engaging finger proprioception training, by splitting the feedback of game elements between the visual and proprioceptive senses. The pilot experiment indicates that the human sensory motor system has the ability to at least temporarily improve proprioception acuity with such game-based training.

Development of a Robotic Unloader Brace for Investigation of Conservative Treatment of Medial Knee Osteoarthritis.

Knee osteoarthritis (KOA) is a painful and debilitating condition that is associated with mechanical loading of the knee joint. Numerous conservative treatment strategies have been developed to delay time to total joint replacement. Unloader braces are commonly prescribed for medial uni-compartmental KOA, however their evidence of efficacy is inconclusive and limited by user compliance. Typical commercial braces transfer load from the medial knee compartment to the lateral knee compartment by applying a continuous brace abduction moment (BAM). We propose that brace utilization and effectiveness could be improved with a robotic device that intelligently modulates BAM in real time over the course of a step, day, and year to better protect the knee joint, improve pain relief, and increase comfort. To this end, we developed a robotic unloader knee brace ABLE (active brace for laboratory exploration) to flexibly emulate and explore different active and passive brace behaviors that may be more efficacious than traditional braces. The system is capable of modulating BAM within each step per researcher defined unloading profiles. ABLE was realized as a lightweight orthosis driven by an off-board system containing a servo motor, drive, real-time controller, and host PC. Frequency response and intra-step trajectory tracking during level-ground walking were evaluated in a single healthy human subject test to verify system performance. The system tracked BAM vs percent gait cycle trajectories with a root mean square error of 0.18 to 0.58 Nm for conditions varying in walking speed, 85-115% nominal, and trajectory peak BAM, 2.7 to 8.1 Nm. Biomechanical and subjective outcomes will be evaluated next for KOA patients to investigate how novel robotic brace operation affects pain relief, comfort, and KOA progression.