Classification of Activities of Daily Living Based on Grasp Dynamics Obtained from a Leap Motion Controller.

Stroke is one of the leading causes of mortality and disability worldwide. Several evaluation methods have been used to assess the effects of stroke on the performance of activities of daily living (ADL). However, these methods are qualitative. A first step toward developing a quantitative evaluation method is to classify different ADL tasks based on the hand grasp. In this paper, a dataset is presented that includes data collected by a leap motion controller on the hand grasps of healthy adults performing eight common ADL tasks. Then, a set of features with time and frequency domains is combined with two well-known classifiers, i.e., the support vector machine and convolutional neural network, to classify the tasks, and a classification accuracy of over 99% is achieved.

Force calibration for an endovascular robotic system with proximal force measurement.

Surgeons, while performing manual endovascular procedures with conventional surgical tools (catheters and guidewires), experience forces on the tool outside the patient's body that are proximal to the point of actuation. Currently, most of the robotic systems for endovascular procedures use active catheters to navigate vasculature and to measure the contact forces at the distal end (tool tip). These tools are more expensive than the conventional surgical tools used in endovascular procedures. To avoid dependence on specialized devices like active catheters, we have developed a novel endovascular robotic system (ERS) that uses conventional surgical tools. Our robot can indirectly measure proximal forces and provide haptic feedback to surgeons. This paper discusses the theory, methodology, and calibration of indirect proximal force measurement. This new calibration technique is presented as a nested optimization problem that is solved using bi-level optimization. The results of experimental validation of the new force calibration methodology are also discussed. The results show that unbiasing of the indirect force measurement by means of force calibration will allow the use of conventional tools in robotic endovascular procedures.

A new implementation for online calculation of manipulator Jacobian.

This paper describes a new implementation for calculating Jacobian and its time derivative for robot manipulators in real-time. The estimation of Jacobian is the key in the real-time implementation of kinematics and dynamics of complex planar or spatial robots with fixed as well as floating axes in which the Jacobian form changes with the structure. The proposed method is suitable for such implementations. The new method is based on matrix differential calculus. Unlike the conventional methods, which are based on screw theory, the Jacobian calculation in the proposed approach has been reduced to the inner product of two matrices. Use of the new method to derive linear and angular velocity parts of Jacobian and its time derivative is described in detail. We have demonstrated the method using a two-DOF spatial robot and a hyper-redundant spatial robot.

Rehabilitation for Children With Dystonic Cerebral Palsy Using Haptic Feedback in Virtual Reality: Protocol for a Randomized Controlled Trial.

BACKGROUND: Cerebral palsy (CP) is the most common developmental motor disorder in children. Individuals with CP demonstrate abnormal muscle tone and motor control. Within the population of children with CP, between 4% and 17% present dystonic symptoms that may manifest as large errors in movement tasks, high variability in movement trajectories, and undesired movements at rest. These symptoms of dystonia typically worsen with physical intervention exercises. OBJECTIVE: The aim of this study is to establish the effect of haptic feedback in a virtual reality (VR) game intervention on movement outcomes of children with dystonic CP. METHODS: The protocol describes a randomized controlled trial that uses a VR game-based intervention incorporating fully automated robotic haptic feedback. The study consists of face-to-face assessments of movement before, after, and 1 month following the completion of the 6-session game-based intervention. Children with dystonic CP, aged between 7 and 17 years, will be recruited for this study through posted fliers and laboratory websites along with a group of typically developing (TD) children in the same age range. We anticipate to recruit a total of 68 participants, 34 each with CP and TD. Both groups of children will be randomly allocated into an intervention or control group using a blocked randomization method. The primary outcome measure will be the smoothness index of the interaction force with the robot and of the accelerometry signals of sensors placed on the upper limb segments. Secondary outcomes include a battery of clinical tests and a quantitative measure of spasticity. Assessors administering clinical measures will be blinded. All sessions will be administered on-site by research personnel. RESULTS: The trial has not started and is pending local institutional review board approval. CONCLUSIONS: Movement outcomes will be examined for changes in muscle activation and clinical measures in children with dystonic CP and TD children. Paired t tests will be conducted on movement outcomes for both groups of children independently. Positive and negative results will be reported and addressed. TRIAL REGISTRATION: ClinicalTrials.gov NCT03744884; https://clinicaltrials.gov/ct2/show/NCT03744884 (Archived by WebCite at http://www.webcitation.org/74RSvmbZP). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/11470.

Design and Development of Surgeon Augmented Endovascular Robotic System.

OBJECTIVE: Inadequate visual and force feedback while navigating surgical tools elevate the risk of endovascular procedures. It also poses occupational hazard due to repeated exposure to X-rays. A teleoperated robotic system that augments surgeon's actions is a solution. METHOD: We have designed and developed an endovascular robotic system that augments surgeon's actions using conventional surgical tools, as well as generates feedback in order to ensure safety during the procedure. The reaction force from vasculature is estimated from motor current that drives the surgical tool. Calibration required for force estimation is based on bilevel optimization. Input shaping is used in conjunction with a cascaded controller to avoid large responses due to faster inputs and to track tool position. The design, realization, and testing of our system are presented. RESULTS: The responses of the system in comparison with the dynamics model is similar vis-à-vis the same input commands. Any error in the position tracking is reduced by the cascaded controller. Phase-portrait analysis of the system showed that the system is stable. The reaction force estimation is validated against load cell measurements. The safety mechanism in the events of excessive reaction forces while interacting with vasculature is demonstrated. CONCLUSION AND SIGNIFICANCE: Our system is a step toward intelligent robots that can assist surgeons during endovascular procedures by monitoring and alerting the surgeons regarding detrimental parameters. It arrests any unintended excursions of the surgical tools or surgeon's actions. This will also eliminate the need for surgeons to be in radiation environment.