Eric Wade

Virtual reality and robotics for stroke rehabilitation: where do we go from here?

Abstract Promoting functional recovery after stroke requires collaborative and innovative approaches to neurorehabilitation research. Task-oriented training (TOT) approaches that include challenging, adaptable, and meaningful activities have led to successful outcomes in several large-scale multisite definitive trials. This, along with recent technological advances of virtual reality and robotics, provides a fertile environment for furthering clinical research in neurorehabilitation. Both virtual reality and robotics make use of multimodal sensory interfaces to affect human behavior. In the therapeutic setting, these systems can be used to quantitatively monitor, manipulate, and augment the users’ interaction with their environment, with the goal of promoting functional recovery. This article describes recent advances in virtual reality and robotics and the synergy with best clinical practice. Additionally, we describe the promise shown for automated assessments and in-home activity-based interventions. Finally, we propose a broader approach to ensuring that technology-based assessment and intervention complement evidence-based practice and maintain a patient-centered perspective.

Motor function assessment using wearable inertial sensors

We present an approach to wearable sensor-based assessment of motor function in individuals post stroke. We make use of one on-body inertial measurement unit (IMU) to automate the functional ability (FA) scoring of the Wolf Motor Function Test (WMFT). WMFT is an assessment instrument used to determine the functional motor capabilities of individuals post stroke. It is comprised of 17 tasks, 15 of which are rated according to performance time and quality of motion. We present signal processing and machine learning tools to estimate the WMFT FA scores of the 15 tasks using IMU data. We treat this as a classification problem in multidimensional feature space and use a supervised learning approach.

An architecture for rehabilitation task practice in socially assistive human-robot interaction

New approaches to rehabilitation and health care have developed due to advances in technology and human robot interaction (HRI). Socially assistive robotics (SAR) is a subcategory of HRI that focuses on providing assistance through hands-off interactions. We have developed a SAR architecture that facilitates multiple task-oriented interactions between a user and a robot agent. The architecture accommodates a variety of inputs, tasks, and interaction modalities that are used to provide relevant, real-time feedback to the participant. We have implemented the architecture and validated its technological feasibility in a small pilot study in which a SAR agent led three post-stroke individuals through an exercise scenario. In the following, we present our architecture design, and the results of the feasibility study.

Automated administration of the Wolf Motor Function Test for post-stroke assessment

The advent of new health sensing technologies has presented us with the opportunity to gain richer data from patients undergoing clinical interventions. Such technologies are particularly suited for applications requiring temporal accuracy. The Wolf Motor Function Test (WMFT) is one such application. This assessment is an instrument used to determine functional ability of the paretic and non-paretic limbs in individuals post-stroke. It consists of 17 tasks, 15 of which are scored according to both time and a functional ability scale. We propose a technique that uses wearable sensors and performance sensors to estimate the timing of seven of these tasks. We have developed a sensing framework and an algorithm to automatically detect total movement time. We have validated the systems accuracy on the seven selected WMFT tasks. We also suggest how this framework can be adapted to the remaining tasks.

Reduced-cable smart motors using DC power line communication

A servomotor design that is powered and controlled through only one wire is presented. A traditional servomotor needs both a power cable and a control cable connecting the motor to a control amplifier. Cables are bulky, heavy, and expensive and, more importantly, difficult to install and maintain in many applications. Particularly for multi-axis applications, like robots and machine tools, cable harnesses become thick and long, and are difficult to run through a stack of many axes, this is a major burden and bottleneck in electromechanical drives. The objective of this research is to eliminate such bulky cables by integrating and consolidating power cables and signal cables into a single wire, and transmitting control signals through the signal wire. Signals are coded by using a CDMA protocol and are superimposed on the single wire that supplies a DC voltage to each motor. In the paper first the principle of reduced-cable smart motors is described, followed by the architecture of the signal transmission system using direct sequence spread spectrum. A prototype system is designed, and the signal transmission line is simulated to verify the principle.

Using socially assistive robotics to augment motor task performance in individuals post-stroke

This paper presents an application of a socially assistive robotics (SAR) system to hands-off post-stroke rehabilitation. We validate the technical feasibility and efficacy of our system in guiding, motivating, and administering an upper extremity rehabilitation task. The robot, which consists of a humanoid torso on a mobile base, monitors user performance on a wire puzzle task through a wearable inertial measurement unit and signals from the puzzle. Smoothness of stroke-affected limb movement is used as the evaluation metric. Five adults of mild to moderate functional ability in the chronic phase of stroke recovery interacted with our SAR system over three separate days. The inertial data from the five participants were analyzed using frequency domain techniques. Subsequently, the amount of power in frequency bands corresponding to voluntary (0.1 to 2Hz) and involuntary motion/jerk (4 to 8Hz) was evaluated. We found that, in adults of mild severity (Upper Extremity Fugl-Meyer Assessment scores greater than 40), the motion becomes smoother (the amount of jerk is reduced) over 3 days of task practice. In adults of moderate motor severity (scores below 40), the motion became less smooth. This may indicate that the combination of our task and SAR system is better suited for individuals with higher functional ability, and needs augmentation in order to aid those of lower functional ability levels.

Socially Assistive Robotics for Guiding Motor Task Practice

Due to their quantitative nature, robotic systems are useful tools for systematically augmenting human behavior and performance in dynamic environments, such as therapeutic rehabilitation settings. The efficacy of human-robot interaction (HRI) in these settings will depend on the robot’s coaching style. Our goal was to investigate the influence of robot coaching styles designed to enhance motivation and encouragement on post-stroke individuals during motor task practice. We hypothesized that coaching styles incorporating user performance and preference would be preferred in a therapeutic HRI setting. We designed an evaluation study with seven individuals post stroke. A socially assistive robotics (SAR) system using three different coaching styles guided participants during performance of an upper extremity practice task. User preference was not significantly affected by the different robot coaching styles in our participant sample (H(2) = 2.638, p = 0.267). However, trends indicated differences in preference for the coaching styles. Our results provide insights into the design and use of SAR systems in therapeutic interactions aiming to influence user behavior.

Design of a Broadcasting Modem for a DC PLC Scheme

A new type of power line carrier communication (PLC) technique is developed to reduce cable requirements for robotic and vehicular systems. An electrical line connecting a dc power supply to motor drives and sensor units is used for transmitting data as well as for delivering the dc power. Unlike conventional ac power line communication, the dc power bus has predictable noise and impedance characteristics that allow for large fanout and high bandwidth. First, the basic architecture of the dc power line communication is presented. Then, a design of a high-fanout modem that uses a Guanella-type transmission line transformer (TLT) is presented. The serial windings and special resonance characteristics of the TLT coupled with a capacitor are exploited to minimize attenuation in high-fanout systems. The modem characteristics including high-frequency parasitic dynamics are analyzed, and the end-to-end line impedance and signal gain are evaluated as the number of nodes goes to infinity. A prototype dc power line communication system is then built, tested, and applied to a design for modular reconfigurable robots

Design and testing of lightweight inexpensive motion-capture devices with application to clinical gait analysis

The advent of more portable and affordable sensing devices has facilitated the study of rehabilitation robotics. Critical to the further development of therapies and interventions are low-cost, easy-to-use devices that can be applied in clinical and home care settings. In this paper, we present a low-cost motion capture system that relies on the opensource Player/Stage software development environment, and can be used in conjunction with a socially assistive robotic agent (or a computer interface) for various types of motor task rehabilitation training. We describe the hardware and software development for the device, and the activity recognition algorithm we developed to capture the relevant motion data. We present the overall framework in which this system can be adapted to other motor task-based rehabilitation regimens. Finally, we present initial experimental data in the domain of gait rehabilitation, in which we use the system to estimate cadence, walking speed, and stride length.

DC powerline communication network for a wearable health monitoring system

Wearable health monitoring networks are useful for many populations. We propose a network that relies on DC powerline communication for power and data transmission between nodes. By using powerline communication, we need only two conductors. We use a garment composed of conductive fabrics as the transmission medium. In this work, we evaluate the basic electronic transmission characteristics of such a garment. We model the 2D transmission that dominates the garment behavior, and present initial experimental results to verify our model.