Clinician perceptions of a novel wearable robotic hand orthosis for post-stroke hemiparesis.

PURPOSE: Wearable robotic devices are currently being developed to improve upper limb function for individuals with hemiparesis after stroke. Incorporating the views of clinicians during the development of new technologies can help ensure that end products meet clinical needs and can be adopted for patient care. METHODS: In this cross-sectional mixed-methods study, an anonymous online survey was used to gather clinicians' perceptions of a wearable robotic hand orthosis for post-stroke hemiparesis. Participants were asked about their clinical experience and provided feedback on the prototype device after viewing a video. RESULTS: 154 participants completed the survey. Only 18.8% had previous experience with robotic technology. The majority of participants (64.9%) reported that they would use the device for both rehabilitative and assistive purposes. Participants perceived that the device could be used in supervised clinical settings with all phases of stroke. Participants also indicated a need for insurance coverage and quick setup time. CONCLUSIONS: Engaging clinicians early in the design process can help guide the development of wearable robotic devices. Both rehabilitative and assistive functions are valued by clinicians and should be considered during device development. Future research is needed to understand a broader set of stakeholders' perspectives on utility and design.

Clinicians valued both assistive and rehabilitative uses of a wearable robotic hand orthosis designed for individuals with hemiparesis after stroke.Wearable robotic hand devices should have the capacity to engage in functional, real-world activities for both assistive and rehabilitative purposes.Pragmatic factors, such as set-up and training time, must be balanced with device complexity to enable implementation in clinical settings.Stakeholders, such as clinicians, play an important role in identifying design priorities for wearable robotic devices to ensure these devices can meet the needs of end-users.

Design of Spiral-Cable Forearm Exoskeleton to Assist Supination for Hemiparetic Stroke Subjects.

We present the development of a cable-based passive forearm exoskeleton that is designed to assist supination for hemiparetic stroke survivors. Our device uniquely provides torque sufficient for counteracting spasticity within a below-elbow apparatus. The mechanism consists of a spiral single-tendon routing embedded in a rigid forearm brace and terminated at the hand and upper-forearm. A spool with an internal releasable-ratchet mechanism allows the user to manually retract the tendon and rotate the hand to counteract involuntary pronation synergies due to stroke. We characterize the mechanism with benchtop testing and five healthy subjects, and perform a preliminary assessment of the exoskeleton with a single chronic stroke subject having minimal supination ability. The mechanism can be integrated into an existing active hand-opening orthosis to enable supination support during grasping tasks, and also allows for a future actuated supination strategy.

Thumb Stabilization and Assistance in a Robotic Hand Orthosis for Post-Stroke Hemiparesis.

We propose a dual-cable method of stabilizing the thumb in the context of a hand orthosis designed for individuals with upper extremity hemiparesis after stroke. This cable network adds opposition/reposition capabilities to the thumb, and increases the likelihood of forming a hand pose that can successfully manipulate objects. In addition to a passive-thumb version (where both cables are of fixed length), our approach also allows for a single-actuator active-thumb version (where the extension cable is actuated while the abductor remains passive), which allows a range of motion intended to facilitate creating and maintaining grasps. We performed experiments with five chronic stroke survivors consisting of unimanual resistive-pull tasks and bimanual twisting tasks with simulated real-world objects; these explored the effects of thumb assistance on grasp stability and functional range of motion. Our results show that both active- and passive-thumb versions achieved similar performance in terms of improving grasp force generation over a no-device baseline, but active thumb stabilization enabled users to maintain grasps for longer durations.

Adaptive Semi-Supervised Intent Inferral to Control a Powered Hand Orthosis for Stroke.

In order to provide therapy in a functional context, controls for wearable robotic orthoses need to be robust and intuitive. We have previously introduced an intuitive, user-driven, EMG-based method to operate a robotic hand orthosis, but the process of training a control that is robust to concept drift (changes in the input signal) places a substantial burden on the user. In this paper, we explore semi-supervised learning as a paradigm for controlling a powered hand orthosis for stroke subjects. To the best of our knowledge, this is the first use of semi-supervised learning for an orthotic application. Specifically, we propose a disagreement-based semi-supervision algorithm for handling intrasession concept drift based on multimodal ipsilateral sensing. We evaluate the performance of our algorithm on data collected from five stroke subjects. Our results show that the proposed algorithm helps the device adapt to intrasession drift using unlabeled data and reduces the training burden placed on the user. We also validate the feasibility of our proposed algorithm with a functional task; in these experiments, two subjects successfully completed multiple instances of a pick-and-handover task.

Rapid mid-jump production of high-performance silk by jumping spiders.

Jumping spiders (Salticidae) do not rely on webs to capture their prey, but they do spin a silk dragline behind them as they move through their habitat. They also spin this dragline during jumps, continuously connecting them with the surface they leapt from. Because spiders cannot spin silk in advance, this silk must be spun at the same speed as the spider jumps - in effect, requiring spin speeds over ten times faster than typical. And while many spiders can move rapidly, for example when running or rappelling, previous research on silk has found that silk spinning rates in excess of walking and web-building speeds (∼2-20 mm/s) result in lower quality silk and even dragline failure1. Here we report that, despite being spun at high speeds (∼500-700 mm/s; 100-140 body lengths/s), jump-spun salticid silk shows consistent, uniform structure as well as the high-performance qualities characteristic of silk spun by other spiders, including orb-weaving species, at low speeds2. The toughness of this jump-spun silk (mean = 281.9 MJ/m3) even surpasses reported values for all but the toughest orb-web draglines2. These results show that salticids are capable of spinning high-performance silk and are able to do so extremely rapidly under natural conditions.

A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins.

We created a computational method to identify allosteric sites using a machine learning method trained and tested on protein structures containing bound ligand molecules. The Random Forest machine learning approach was adopted to build our three-way predictive model. Based on descriptors collated for each ligand and binding site, the classification model allows us to assign protein cavities as allosteric, regular or orthosteric, and hence to identify allosteric sites. 43 structural descriptors per complex were derived and were used to characterize individual protein-ligand binding sites belonging to the three classes, allosteric, regular and orthosteric. We carried out a separate validation on a further unseen set of protein structures containing the ligand 2-(N-cyclohexylamino) ethane sulfonic acid (CHES).