A novel robotic platform to assist, train, and study head-neck movement

Moving the head-neck freely is an everyday task that a healthy person takes for granted. Such a simple movement, however, may be very challenging for individuals with neurological disorders such as amyotrophic lateral sclerosis. These individuals often do not have enough neck muscle strength to stabilize the head at the upright neutral or to move it in a controlled manner. Static braces are commonly prescribed to these patients. However, these braces often fix the head at a single configuration, which makes them uncomfortable to wear for an extended period of time. In this thesis, a robotic neck brace is developed. It accommodates three rotations and covers roughly 70% range of motion of the head-neck of a typical able-bodied adult. The hardware is lightweight (1.5 kilogram) and wearable, with a pair of pads and a soft band attached to the shoulders and the forehead, respectively. A parallel mechanism connecting the shoulder pads and the headband was designed to meet the empirical human movement data. This design choice is novel where the parasitic motion (translation of the head) was parameterized and optimized to address misalignment between the robot and the user's head. A user can control this neck brace to assist intended head-neck movement through input devices, including hand-held joysticks, keyboards, and eye-trackers. This provides a potential solution to remediate head drop. Additionally, this robotic brace is developed into a versatile platform to train and study head-neck movements. The robot was designed to be highly transparent to the user and features different force controllers. Therefore, it can be used to assess the free movement of the head-neck and mimic different interactions between a therapist and a patient. The modalities of this neck brace have been validated with different users. To the best of our knowledge, this robotic neck brace is the first in the literature to assist, train, and study head-neck movements

Computer Access Technologies for Controlling Assistive Robotic Manipulators: Potentials and Challenges

One of the most challenging barriers to a successful application of the assistive robots is how to enable users who have special needs to interact with the robot aids in an efficient and comfortable manner, since the conventional control method using a traditional joystick combined with buttons and/or knobs demands fine motor control and good dexterity resulting in cognitive and physical workload. Adopting computer access technology, which has provided an alternative means to allow people who have a wide range of special needs to independently access their computer, can be a practical solution to this issue. In this paper, we reviewed and discussed the potentials and challenges of computer access technologies as an alternative control method for controlling assistive robotic manipulators, focusing on most widely adopted interventions in the clinical settings, including alternative pointing, keyboard-only access, switch scanning interface and speech recognition

Better Medicine

https://scholarlyworks.lvhn.org/better-medicine/1022/thumbnail.jp

Robot assisted stapedotomy ex vivo with an active handheld instrument

Micron is a fully handheld active micromanipulator that helps to improve position accuracy and precision in microsurgery by cancelling hand tremor. This work describes adaptation, tuning, and testing of the Micron system for stapedotomy, a microsurgical procedure performed in the middle ear to restore hearing that requires accurate manipulation in narrow spaces. Two end-effectors, a handle, and a brace (or rest) were designed and prototyped. The control system was adapted for the new hardware. The system was tested ex vivo in stapedotomy procedure comparing manually-performed and Micron-assisted surgical tasks. Tremor amplitude was found to be reduced significantly. Further testing is needed in order to obtain statistically significant results regarding other parameters dealing with regularity of the fenestra shap

Development of a Wearable Mechatronic Elbow Brace for Postoperative Motion Rehabilitation

This thesis describes the development of a wearable mechatronic brace for upper limb rehabilitation that can be used at any stage of motion training after surgical reconstruction of brachial plexus nerves. The results of the mechanical design and the work completed towards finding the best torque transmission system are presented herein. As part of this mechatronic system, a customized control system was designed, tested and modified. The control strategy was improved by replacing a PID controller with a cascade controller. Although the experiments have shown that the proposed device can be successfully used for muscle training, further assessment of the device, with the help of data from the patients with brachial plexus injury (BPI), is required to improve the control strategy. Unique features of this device include the combination of adjustability and modularity, as well as the passive adjustment required to compensate for the carrying angle

It is all me: the effect of viewpoint on visual-vestibular recalibration

Participants performed a visual–vestibular motor recalibration task in virtual reality. The task consisted of keeping the extended arm and hand stable in space during a whole-body rotation induced by a robotic wheelchair. Performance was first quantified in a pre-test in which no visual feedback was available during the rotation. During the subsequent adaptation phase, optical flow resulting from body rotation was provided. This visual feedback was manipulated to create the illusion of a smaller rotational movement than actually occurred, hereby altering the visual–vestibular mapping. The effects of the adaptation phase on hand stabilization performance were measured during a post-test that was identical to the pre-test. Three different groups of subjects were exposed to different perspectives on the visual scene, i.e., first-person, top view, or mirror view. Sensorimotor adaptation occurred for all three viewpoint conditions, performance in the post-test session showing a marked under-compensation relative to the pre-test performance. In other words, all viewpoints gave rise to a remapping between vestibular input and the motor output required to stabilize the arm. Furthermore, the first-person and mirror view adaptation induced a significant decrease in variability of the stabilization performance. Such variability reduction was not observed for the top view adaptation. These results suggest that even if all three viewpoints can evoke substantial adaptation aftereffects, the more naturalistic first-person view and the richer mirror view should be preferred when reducing motor variability constitutes an important issue

Trunk Rehabilitation Using Cable-Driven Robotic Systems

Upper body control is required to complete many daily tasks. One needs to stabilize the head and trunk over the pelvis, as one shifts the center of mass to interact with the world. While healthy individuals can perform activities that require leaning, reaching, and grasping readily, those with neurological and musculoskeletal disorders present with control deficits. These deficits can lead to difficulty in shifting the body center of mass away from the stable midline, leading to functional limitations and a decline in the quality of activity. Often these patient groups use canes, walkers, and wheelchairs for support, leading to occasional strapping or joint locking of the body for trunk stabilization. Current rehabilitation strategies focus on isolated components of stability. This includes strengthening, isometric exercises, hand-eye coordination tasks, isolated movement, and proprioceptive training. Although all these components are evidence based and directly correlate to better stability, motor learning theories such as those by Nikolai Bernstein, suggest that task and context specific training can lead to better outcomes. In specific, based on our experimentation, we believe functional postural exploration, while encompassing aspects of strengthening, hand-eye coordination, and proprioceptive feedback can provide better results. In this work, we present two novel cable robotic platforms for seated and standing posture training. The Trunk Support Trainer (TruST) is a platform for seated posture rehabilitation that provides controlled external wrench on the human trunk in any direction in real-time. The Stand Trainer is a platform for standing posture rehabilitation that can control the trunk, pelvis, and knees, simultaneously. The system works through the use of novel force-field algorithms that are modular and user-specific. The control uses an assist-as-needed strategy to apply forces on the user during regions of postural instability. The device also allows perturbations for postural reactive training. We have conducted several studies using healthy adult populations and pilot studies on patient groups including cerebral palsy, cerebellar ataxia, and spinal cord injury. We propose new training methods that incorporate motor learning theory and objective interventions for improving posture control. We identify novel methods to characterize posture in form of the “8-point star test”. This is to assess the postural workspace. We also demonstrate novel methods for functional training of posture and balance. Our results show that training with our robotic platforms can change the trunk kinematics. Specifically, healthy adults are able to translate the trunk further and rotate the trunk more anteriorly in the seated position. In the standing position, they can alter their reach strategy to maintain the upper trunk more vertically while reaching. Similarly, Cerebral Palsy patients improve their trunk translations, reaching workspace, and maintain a more vertical posture after training, in the seated position. Our results also showed that an Ataxia patient was able to improve their reaching workspace and trunk translations in the standing position. Finally, our results show that the robotic platforms can successfully reduce trunk and pelvis sway in spinal cord injury patients. The results of the pilot studies suggest that training with our robotic platforms and methods is beneficial in improving trunk control