Stroke is the main cause of adult disability; 8 out of 10 survivors sustain motor deficits that interfere with activities of daily living. There exists no proven therapeutic strategy for motor recovery of the upper extremity following stroke. While this limitation could be a fundamental deficiency of the stroke-impaired brain, it is at least in part the result of neglecting the sensory impairments that frequently accompany motor deficits. Sensory impairments, specifically those affecting proprioception—the sense one has of his or her body in space—are known to exacerbate motor deficits and prevent motor recovery following stroke. As many as 63% of stroke survivors face deficits in proprioception. To improve potential for recovery, it is important to better understand the brain's proprioceptive estimation system, this system's role in motor control, and how the systems both can "break" following stroke.
To assess sensorimotor ability in the upper limb, we designed a low-cost robotic arm support. We call this the chARM, a nod to Allison Okamura's CHARM Lab at Stanford University. The robot is easily back-drivable and capable of tracking and controlling movement in both joint space and hand space. A mirror display calibrated to the chARM robot shows 3D graphics in the plane of the arm while simultaneously blocking the arm from view. CAD files and software will soon be made available online via GitHub.
Using the chARM, we have quantified proprioception in the upper limb of both non-disabled controls and a selection of stroke survivors. Experiments are broken into sub-tests that attempt to shed light on the inner workings of the brain's estimation system, especially the contribution of the predictive internal model. Check out a Stanford article about my research here. Publications include the following, the first of which was awarded Best Student Presentation:
S. M. Sketch, A. J. Bastian and A. M. Okamura (2018) Comparing Proprioceptive Acuity in the Arm between Joint Space and Task Space. In IEEE Haptics Symposium, pages 125-132. [paper] [slides]
S. M. Sketch, C. S. Simpson, A. J. Bastian and A. M. Okamura (2018) Measurements of Proprioception: Active, Passive, Joint Space, Task Space. TBD, [in preparation].
In addition to research towards my graduate thesis, I have worked on a number of projects both in and out of the lab.
While many of the sensorimotor deficits encountered by disabled stroke survivors are treatable, the benefits of applying a treatment cannot be foreseen due to the unknown causal relationship between sensorimotor deficits and movement impairment. A subject-specific simulation has the potential to predict the effects of specific medical interventions so that only the most effective treatments are implemented on a patient. We modeled neural control of reaching with the human upper limb as a near-optimally feedback-controlled two-degree-of-freedom system with biologically based parameters. We added sensorimotor impairments commonly associated with post-stroke hemiparesis—abnormal joint coupling, increased noise on internal model, and muscle weakness—and examined the impact on reaching performance. MATLAB scripts will soon be made available online via GitHub.
S. M. Sketch, C. S. Simpson, F. Crevecoeur and A. M. Okamura (2017) Simulating the impact of sensorimotor deficits on reaching performance. In IEEE International Conference on Rehabilitation Robotics, pages 31-37. [paper] [poster]
C. S. Simpson, S. M. Sketch, F. Crevecoeur and A. M. Okamura (2017) Modeling sensitivity of reaching behavior to sensorimotor deficits. In 27th Annual Meeting of the Society for the Neural Control of Movement.
improving running efficiency
Spring-like tissues attached to the swinging legs of animals are thought to improve running economy by simply reducing the effort of leg swing. We showed that show that a spring, or 'exotendon,' connecting the legs of a human runner improves economy instead through a more complex mechanism that produces savings during both swing and stance. The spring increases the energy optimal stride frequency; when runners adopt this new gait pattern, savings occur in both phases of gait. Remarkably, the simple device improves running economy by 6.4 ± 2.8%, comparable to savings achieved by motorized assistive robotics that directly target the costlier stance phase of gait. Our results highlight the importance of considering both the dynamics of the body and the adaptive strategies of the user when designing systems that couple human and machine.
C. S. Simpson, C. G. Welker, S. D. Uhlrich, S. M. Sketch, R. W. Jackson, S. L. Delp, S. H. Collins, J. C. Selinger and E. W. Hawkes (2018) Connecting the legs with a spring improves human running economy. BioRxiv, 474650. [paper]
Brain-computer interfaces (BCIs) have the potential to restore a degree of independence for individuals with severe mobility and dexterity impairments. However, the neural control that such individuals are able to exert over BCI-controlled devices is limited due to insufficient sensory feedback through the human-robot interface. Haptic feedback can provide BCI users with information about their brain activity without taxing the auditory and visual systems on which they rely to monitor the environment. We designed a BCI-driven skin-stretch device, assessed several control paradigms for this device, and evaluated its effectiveness in a small user study.
S. M. Sketch, D. R. Deo, J. P. Menon and A. M. Okamura (2015) Design and Experimental Evaluation of a Skin- Stretch Haptic Device for Improved Control of Brain-Computer Interfaces. In IEEE International Conference on Robotics and Automation, pages 272-277. [paper] [slides]
Impedance-type kinesthetic haptic displays aim to render arbitrary desired dynamics to a human operator using force feedback. To effectively render realistic virtual environments, the difference between desired and rendered dynamics must be small. We analyzed the closed-loop dynamics of haptic displays for three common virtual environments: a spring, a damper, and a spring-damper, including the effects of time delay and low-pass filtering. Using a linear model, we identified important parameters for accuracy in terms of "effective impedances," a conceptual tool that decomposes the haptic display’s closed-loop impedance into components with physical analogs, such as stiffness, damping, and mass.
N. Colonnese, S. M. Sketch and A. M. Okamura (2014) Closed-loop Stiffness and Damping Accuracy of Impedance-type Haptic Displays. In IEEE Haptics Symposium, pages 97-102. [paper]
Telerobotics has the potential to facilitate the repair of satellites by allowing human operators to interact naturally with remote objects. Time delays on the order of seconds—due to signal transmission and encryption—make it difficult to provide immersive feedback to the operator, motivating the use of predictive visual and haptic displays of the robot and environment. In collaboration with DARPA, we developed a teleoperation framework that invokes a two-part environment model that predicts motion of objects in the environment, both in free space and during contact with the robot.
R. C. Winck, S. M. Sketch, E. W. Hawkes, D. L. Christensen, H. Jiang, M. R. Cutkosky and A. M. Okamura (2014) Time-delayed teleoperation for interaction with moving objects in space. In IEEE International Conference on Robotics and Automation, pages 5952-5958. [paper]
Being perhaps the most intimate form of communication, I am passionate about teaching. In addition to serving as Course Assistant for Stanford undergraduate and graduate courses, I have lectured in both Mechanical Engineering and the medical school:
ENGR 105: Feedback Control Design
ME 328: Medical Robotics
ME 161/261: Dynamic Systems
MED 289: Introduction to Bioengineering Research
I also redesigned the Teaching Assistant training course within Mechanical Engineering [ME 492] and instructed more than 100 CAs over the course of 2 years. Within the CHARM Lab, I have given tutorials on statistics and figure-making.