Mon, June 1, 1:00 PM
Speaker: Lorenzo Masia, PhD
Title: Robot Aided Rehabilitation for Proprioception and Design of an Assistive Upper Limb Exosuit
Abstract: Human Machine Interaction (HMI) has advanced the range of possibilities in manipulation tasks, providing additional empowering instruments for a wide spectrum of novel applications from Ergonomics (remotely operated systems or minimally invasive surgery MIS) to Clinical Rehabilitation (Robot Aided Rehabilitation).
After a short introduction on broadly used control schemes in HMI, I will briefly discuss the robotic solutions designed and developed in my previous experiences: driving through experiments for characterization of residual motor functions in stroke patients to better address rehabilitation strategies by using opportunely designed haptic devices. A special emphasis will be dedicated to proprioceptive impairment: loss of proprioception is likely to affect in a significant manner the capacity of stroke patients to recover functionality of the upper limb; clinical assessment methods currently in use are rather crude, with a low level of reliability and a limited capacity to discriminate the relevant features of the deficits. I will illustrate a new technique based on robotic technology, with the goal of providing a reliable, accurate, and quantitative evaluation of kinesthetic acuity which can be integrated in rehabilitation protocols.
The second part of the presentation will be on a new concept for actuation that combines an elastically compliant composite structure with conventional electromechanical elements. The proposed design is analogous to that used in Series Elastic Actuators, but with a distinctive feature in the compliant transmission which can provide different stable configurations. In other words, its elastic potential presents points of local minima that correspond to robust stable positions (multistability). This potential is known a priori as a function of the structural geometry, thus providing tremendous benefits in terms of control implementation. Such knowledge enables to overcome the complexities arising from the additional degrees of freedom associated with link deformations and uncovers challenges that go beyond those posed by standard rigid-link robot dynamics. It is thought that integrating a multistable elastic element in a robotic transmission can open new scenarios in the field of assistive robotics, as the system may help a subject to stand or carry a load without the need for an active control effort by the actuators: this new approach has the potential to provide tremendous benefits in terms of control implementation, enabling to overcome the complexities arising from the additional degrees of freedom associated with link deformations and uncovering challenges that go beyond those posed by standard rigid-link robot dynamics in assistive technology.
Hosts: Drs. Patton and Mussa-Ivaldi
Fri, May 29
Speaker: Kathryn Nightingale, PhD
Title: Ultrasonic Elasticity Imaging with Acoustic Radiation Force
Abstract: Acoustic radiation force based ultrasonic elasticity imaging methods have become widely available in the clinical market over the past five years. To date, these methods have found success clinically in the context of hepatic fibrosis staging and breast lesion characterization, with many additional applications under investigation. Implementations are available that provide high resolution images of relative differences in tissue stiffness, as well as shearwave based approaches that provide quantitative estimates of the tissue stiffness. The quantitative methods assume that the tissues are linear, isotropic, elastic, homogeneous, and incompressible in order to reconstruct the underlying material stiffness. Our recent work in shear wave imaging focuses on understanding the sources of error in these systems, and developing methods that address some of the underlying assumptions, i.e. using 3D volumetric imaging to analyze material anisotropy and dispersion analyses to assess material viscoelasticity. In this talk, I will review the underlying physics of these tools and discuss the promise and limitations of these methods, and present examples of clinical applications.
Host: Dr. Rymer
Tue May 19, 12:30 PM
Speaker: Ravneet S Vohra, PT, PhD
Abstract: With a number of potential therapeutic interventions for Duchenne muscular dystrophy (DMD) under development, and some already in clinical trials, there is a need for non-invasive biomarkers. Recently, there has been increasing interest in non-invasive imaging modalities, particularly MRI, for diagnosis and assessment of disease progression for a number of neuromuscular diseases, including DMD. Indeed several MR investigations of dystrophic muscle have shown promise in monitoring disease progression in skeletal and cardiac muscle. In this talk, I will provide an overview of different MR imaging techniques to monitor the disease progression in skeletal muscles of human and animal models of DMD.
Host: Dr. Jayaraman
Fri May 15
Speaker: Claire Chambers
Title: Context effects in the perception of frequency shift
Abstract: A new experimental paradigm is presented for studying how recent sensory history (the context) affects a basic aspect of auditory perception, the comparison of successive frequency components. Stimuli were devised to include ambiguous transitions between frequency components, as it was hypothesized that such an ambiguity would make the task especially prone to reveal context effects. Using pairs of Shepard tones (Shepard, J. Acoust. Soc. Am., 1964), we show that frequency shifts are preferentially reported when they encompass a frequency regions that was stimulated during the context. This context effect is rapidly introduced, as a single tone as short as 20ms can produce a reliable bias. Yet it also has an enduring effect on perception, persisting over more than 30s. Using random chords pairs designed to include ambiguous frequency shifts, it then shown that the context effect is not specific to Shepard tones but rather reflects a generic process acting on the tonotopic representation of sounds. In a final experiment, we show that the context effect is modulated by both low-level (ear-of-entry) and high-level (selective attention) manipulations, suggesting an interplay between several processing stages in the underlying neural mechanism. Finally, we use a probabilistic perceptual model based on the notion of auditory grouping to account for our psychophysical results. Our findings show that one of the most ubiquitous and basic tasks of the auditory system, comparing successive frequency components, is not a fixed function of the physical stimulus. Rather, it is highly malleable and depends on the ongoing context.
Host: Dr. Kording
Speaker: Meena AbdelMaseeh
Title: New Approaches for the Analysis of Electromyographic Signals for Characterizing Neuromuscular Disorders and Myoelectric Control
Abstract: The focus of the first part of the talk is the use of intramuscular electromyographic (EMG) signals for assessing the neurophysiologic characteristics of neuromuscular disorders. The evaluation of patients with suspected neuromuscular disorders is typically based on qualitative visual and auditory assessment of needle electrode detected EMG signals; the resulting muscle characterization is subjective and highly dependent on the skill and experience of the examiner. Quantitative EMG techniques have been developed to identify motor unit potential trains (MUPTs) in EMG signals, and extract quantitative features capturing motor unit potential (MUP) morphology, morphological instability across MUPs of the same MUPT, and motor unit activation levels.
Following a brief introduction to the basic concepts of the decomposition-based quantitative EMG techniques, I will present new clinically useful representations and quantitative features that can be interpreted from an anatomical, physiological and pathological basis. I will then introduce a muscle categorization algorithm capable of estimating the likelihood of a muscle being affected with a specific disorder and inducing transparency rules integratable in the clinical assessment. The direct implication of these improvements is to increase the diagnostic power of quantitative EMG techniques. The availability of representations, quantitative features, and muscle categorizations that can be automatically obtained will motivate further utilization of quantitative EMG techniques for neuromuscular disorders assessment and other specialties such as senior care, rehabilitation, sport medicine, and pain management.
In the second part of the talk, I will describe a system for hand movement recognition using multi-channel EMG signals obtained from the forearm surface. In particular, methods for the extraction of activation trajectories underlying hand movements, and classifying the extracted trajectories using a metric based on multi-dimensional dynamic time warping will be discussed.
Host: Dr. Hargrove
Fri May 8
Speaker: Gerald E. Loeb, M.D
Title: Biomimetic Machine Touch for Dexterous Robotic and Prosthetic Hands
Abstract: Machine vision has been applied successfully to industrial robots. Commercially available CCD video cameras capture images of objects being manipulated and computer algorithms extract information to make decisions about their handling. Is this a model for haptically enabled robots? No. Haptics is essentially collision management. No matter what tactile sensing modality is employed, the events that will be sensed depend on the mechanical properties of the appendage that contains the sensors and on the active movement that causes the collisions with an object. Humanlike dexterity is often seen as a desirable and challenging goal for haptic robots, so it seems reasonable to understand and perhaps to imitate those properties and movements. Key mechanical properties of glabrous fingertips include highly elastic and compliant skin that is deformed by mechanical interactions with objects. A flat region on the underlying bone called an apical tuft provides the equivalent of a vernier amplifier for tiny tilt angles. Fingerprint ridges convert simple sliding movements into coherent amplification of induced vibrations. Heating the fingertip above ambient results in thermal gradients indicative of the material properties of objects. All other surfaces of human limbs are covered by hairy skin, which provides highly sensitive contact detection to trigger evasive action and a tough surface that can absorb kinetic energy until such action takes effect. Dexterity also depends as much on speedy responses as on sophisticated signal processing, so humans rely first on simple, short-latency reflexes mediated by spinal cord rather than conscious perception by the distant brain. Conscious perception in the brain requires an iterative series of decisions about what exploratory movement will most likely resolve whatever uncertainty the human operator has about an object, based on prior experience and unfolding events. We have built robotic machines with tactile sensors, reflexive feedback and exploratory algorithms that mimic most of these human strategies and thereby achieve at least a modicum of humanlike haptic function. Much remains to be done but at least we are finally on the right track.
Host: Dr. Mussa-Ivaldi
Fri May 1
Speaker: Dominique Duncan, PhD
Title: Nonlinear Factor Analysis in Neurological Applications
Abstract: A novel approach to describe the variability of the statistics of intracranial EEG (icEEG) data is proposed that is an adaptation of the diffusion map framework. Diffusion maps, which extend principal components analysis and provide a nonlinear approach, provide dimensionality reduction of the data as well as pattern recognition that can be used to distinguish different states of a patient, for example, interictal and preseizure states. A new algorithm, which is an extension of diffusion maps, is developed to construct coordinates that generate efficient geometric representations of the complex structures in the icEEG data. Numerical results show that the proposed approach provides a distinction between interictal and preseizure states.
Furthermore, the algorithm is also applied to classify magnetic resonance images (MRI) of brains of patients with Alzheimer's Disease and those without Alzheimer's Disease. The method is adapted to the MRI and accounts for the variability in calibration of the MRI of different patients.
Additionally, the icEEG data of the epilepsy patients are used to test the existence of a relationship between distant parts of the default mode network (DMN), a resting state network defined by fMRI studies. Magnitude squared coherence, mutual information, cross-approximate entropy, and the coherence of the gamma power time-series were estimated, for one hour icEEG recordings of background activity from 9 patients, to evaluate the relationship between two test areas. These two test areas were within the DMN (anterior cingulate and orbital frontal, denoted as T1 and posterior cingulate and mesial parietal, denoted as T2), and one control area (denoted as C) was outside the DMN. The goal was to test if the relationship between T1 and T2 was stronger than the relationship between each of these areas and C. A low level of relationship was observed among the 3 areas tested. The relationships among T1, T2, and C did not demonstrate support for the DMN. The results obtained underscore the considerable difference between electrophysiological and hemodynamic measurements of brain activity and possibly suggest a lack of neuronal involvement in the DMN.
Host: Dr. Körding
Fri April 17
Speaker: Todd Kuiken, MD, PhD
Title: New Concepts for Attaching Prostheses to People
Abstract: The most challenging and important part of any prosthesis is how you attract the device to the person. The residual limbs of people with amputations have a nice rigid long bone, that is covered with multiple layers of compliant tissue. At the CBM we have been working on improving this human machine interface in many ways. Dr Kuiken will show preliminary work and early concepts on 4 different approaches to improving this interface.
Fri April 10
Speaker: Diane L. Damiano, PhD PT
Title: Activity-based neurorehabilitation for cerebral palsy: How well are we doing?
Abstract: This presentation will discuss the effectiveness of current activity-based neurorehabilitation strategies primarily aimed at improving mobility in children withcerebral palsy. It is now well-recognized that motor activity (or lack thereof) drives both muscle and brain plasticity. Intense motor training paradigms utilizing various types of devices have become increasingly common in CP rehabilitation with outcomes not always as anticipated. Emerging principles on the types, amounts and timing of activity that may best promote these processes will be discussed with respect to existing and novel strategies. Developmental and individual genetic factors and how these may affect responsiveness to motor training in CP will also be considered.
Host: Drs. Gaebler & Zhang
Fri April 3
Speaker: Alex Leow, PhD
Title: Multi-modal Connectomics of the Human Brain
Abstract: In this talk, I will provide an overview of multi-modal brain connectomics as a rapidly evolving field in computational neuroimaging. Using structural brain connectome as an example, we will first look at diffusion-weighted MR imaging developed in order to better understand the micro-architecture of white matter. Next, we will examine related techniques including diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI) and diffusion spectrum imaging (DSI). These techniques naturally lead to white matter tractography, based on which structural brain networks or “connectomes” can be built. This paves the way for the application of graph theory to probe the organizational properties of the human brain modelled as a graph. Most recent developments by our own group to investigate and further explore the translational implications of connectomics will be discussed. Case study topics may include the digital clock drawing test and virtual-reality connectome visualization.
Host: Dr. Patton
Tue March 31
Speaker: Michelle Ferrill
Title: Sentence Processing in Aphasia: Contributions of Word Level Deficits
Abstract: Although listeners rarely have difficulty understanding spoken language, the intricate complexity of language comprehension becomes all too obvious after an individual suffers neural trauma that results in aphasia. Individuals with one type of aphasia in particular, agrammatic Broca’s aphasia, have generally spared comprehension of sentences that follow the most common (canonical) word order in a language, but comprehension becomes impaired when sentences deviate from that order (e.g., Caramazza & Zurif, 1976; Grodzinsky, 2000; and many others). Revealing the underlying basis for this comprehension disorder would shed light on brain-language relations and would also allow for more effective treatment approaches. One hypothesis that has been supported by recent research implicates delayed lexical access during sentence comprehension (Love, Swinney, Walenski, & Shapiro, 2008; Ferrill, Love, Walenski, & Shapiro, 2012; see also Thompson & Choy, 2009). Our work suggests that this lexical access delay affects syntactic processes and thus contributes to the sentence comprehension deficits observe in this population. This talk will present findings from three studies: (1) a study which evaluated the time-course of lexical access during sentence processing in Broca’s aphasia via a method that measures real-time processing, that is, processing that is occurring as the sentence is ongoing; (2) a study that examined the relationship between these real-time lexical access patterns and patterns of brain damage in areas of the brain that have been linked to language; as well as (3) a study that attempted to exploit anticipatory processing cues to mitigate the lexical processing delay. Finally, a treatment study will be proposed that attempts to capitalize on sensitivity to certain types of processing cues in the listeners with Broca’s aphasia who have a comprehension disorder.
Host: Dr. Cherney
Fri March 20
Speaker: William S. Evans, MS, CCC-SLP
Title: Cognitive Control and Task Effects in Aphasia
Abstract: Executive control, attention, and language impairments often co-occur following stroke, and this observation has led to an increasing interest in the role of control processes in aphasia. This talk will present parts of my doctoral work, which explores relationships between cognitive control, task goals, and automatic linguistic processes in the post-stoke aphasia population. Results will be interpreted using the Ratcliff Diffusion Model, a classic forced-choice decision model that incorporates both accuracy and reaction time data to derive underlying parameters claimed to drive the decision process. Potential implications for aphasia rehabilitation will be discussed.
Host: Dr. Cherney
Fri March 13
Speaker: Luca Lonini, PhD
Title: Wearable sensors and machine learning: using novel outcome tools in rehabilitation
Abstract: The use of wearable sensors as a tool for continuous health monitoring is gaining interest due to their low cost and increasing memory storage and computing power. Machine learning algorithms are often used in this context to infer relevant information from the sensors data and inform clinicians on patients’ outcomes.
In this talk I will present two applications exploiting the synergy of these fields in physical rehabilitation: the first consists of measuring walking quality in spinal cord injury patients’ who are trained to use a robotic exoskeleton to walk; the second case is a comparative study of the effect of a computerized leg brace (C-brace) vs. a traditional stance-control orthoisis (SCO) on patients’ everyday activities.
Fri March 6
Speakers: Jessica Crujeiras, Nathalia Headley and Andy Kondrat
Title: Informed Consent in Research at RIC: Policy, Compliance, and Ethics
Fri Feb 27
Speaker: Katharine Polasek, PhD
Title: Referred Sensation from Surface Electrical Stimulation as a Potential Treatment for Phantom Limb Pain
Abstract: Phantom limb pain adversely affects a majority of amputees and most treatment options are unsatisfactory. The long term goal of this research is to develop a non-invasive therapy to treat phantom limb pain in individuals with amputations. This therapy will be based on the theory that a major contributor to phantom limb pain is lack of input from the missing limb. Our hypothesis is that sensation from the missing limb paired with appropriate visual feedback will lead to an overall decrease in painful sensations. Prior to testing in amputees, we needed to show that we could reliably evoke distal referred sensation through proximal stimulation. I will first talk about our testing on individuals with intact-limbs where we have been able to reliably evoke a tapping sensation in the hand or foot though surface electrical stimulation at the elbow or knee. At times we have evoked sensations in different hand locations but this has been more difficult to reproduce. To investigate what we are actually activating and see if we can determine a method to reliably produce sensations in different location we developed a computer model of surface electrical stimulation. This model will be used to predict the effect of electrode location, size and configuration on which part of the nerve is activated and help design an electrode configuration that can be adjusted to activate distinct distal locations. Future work will include using the rubber hand illusion to quantify the reality of the evoked sensations and experiments with individuals with amputations to evaluate the decrease in phantom limb pain due to periodic restoration of sensation.
Host: Carrie Peterson
Fri Feb 13
Speaker: Jinsung Wang, PhD
Title: Generalization of sensorimotor adaptation across different motor effectors
Abstract: Motor learning can generalize across different motor effectors. However, the extent of generalization across different effectors is typically smaller than the extent of generalization observed across different movement conditions within the same effector. While generalization of motor learning has been studied extensively, it remains unclear why generalization across different effectors is limited. Findings from our recent studies suggest that motor learning may involve two types of learning mechanisms: algorithmic learning, which is analogous to model-based learning, and instance-reliant learning, which is analogous to model-free learning. Based on the idea of instance-reliant learning, we attempt to explain why generalization of motor learning across motor effectors is limited, and also to demonstrate that providing effector-specific instances can increase the extent of interlimb generalization substantially.
Host: Dr. Patton
Fri Feb 6
Speaker: Lois Shepherd, JD
Title: Recent research ethics controversies and what they mean for comparative effectiveness (“outcomes”) research
Abstract: If a parent is asked to enroll her pre-mature infant in a study comparing different amounts of supplemental oxygen, what should she be told? In the controversial SUPPORT Trial, conducted from 2005-2009, investigators sought to determine the best oxygen saturation levels for infants in terms of reducing risks for eye disease, neurological injury, and death. The parents were told there was no predictable increase in risk from participation in the study because both oxygen levels targeted in the study were within the “standard of care.” Was this disclosure adequate? Was it accurate? These questions have split the bioethics community to an unprecedented degree. This session will discuss the SUPPORT Trial, basic principles of research ethics, and where research regulation is headed in relation to comparative effectiveness research.
Host: Max Shepherd
Tue Feb 3
Speaker: Amy Orsborn, PhD
Title: Designing neuroprostheses in closed-loop
Abstract: The ultimate goal for motor neuroprostheses is to provide high performance that can be maintained for long-term use in the varied activities of daily life. Leveraging the closed-loop, co-adaptive nature of neuroprostheses may be particularly beneficial for meeting these challenges. Neuroprostheses create artificial, closed-loop control systems where the subject can actively contribute to performance via learning. In this talk, I will discuss design strategies and research motivated by this closed-loop perspective. My work focuses on non-human primate models, where subjects control virtual objects using neural activity recorded from arrays implanted in motor cortex. I will first discuss closed-loop decoder adaptation (CLDA), which adapts the decoding algorithm as the user controls the prosthetic to improve performance. I will then show that CLDA can be combined with neural adaptation, and that incorporating both forms of adaptation may be useful for producing long-lasting flexible devices. I will also discuss new work exploring the potential importance of signal selection for neuroprosthetic performance. I will present a new method to simultaneously record neural activity across multiple spatial scales (electrocorticography, local field potentials, and action potentials). This method, combined with peripheral recordings like electromyography, will allow us to optimize signal selection for high-performance neuroprostheses.
Host: Dr. Miller
Fri. Jan 30
Speakers: Reva Johnson and Lauren Smith
Title 1: Sensorimotor Adaptation with Powered Upper-Limb Prosthesis Control
Abstract: Powered upper limb prostheses offer hope in restoring the abilities lost to amputation; however, the current lack of kinesthetic feedback requires users to devote constant visual attention. Providing additional sensory feedback is an intuitive solution, and many groups are working towards clinical implementation. However, we do not understand how amputees rely on sensory feedback during movements with a prosthesis, and how this use of feedback differs from movements with intact limbs. To help answer these questions, we studied how amputees and able-bodied subjects relied on feedback during trial-by-trial adaptation using different control signals: joint angle, joint torque, and EMG. Our results suggest that adaptation was not significantly affected by control signal or limb used, but depended primarily on mean error. Thus we can apply models of sensorimotor adaptation to powered prosthesis control and use them to clarify the most effective sensory feedback information.
Title 2: Intramuscular EMG for the Simultaneous Control of Multiple Degrees of Freedom in Upper-Limb Myoelectric Prostheses
Abstract: Clinically available myoelectric prostheses use surface EMG signals to control prosthetic joint movement, and have limited ability to provide simultaneous control of multiple degrees of freedom (DOFs). Instead, most patients are required to operate each DOF sequentially, unlike the coordinated multi-joint movements produced by intact limbs. Recent advances in implantable EMG recording devices have the potential to provide intramuscular EMG signals for clinical applications, which may allow for the use of simultaneous control approaches that have not been successfully implemented using surface EMG. Using fine wire EMG recordings from the forearm, we investigated the potential for using intramuscular EMG for the simultaneous control of a three-DOF wrist/hand system. We evaluated different methods for predicting intended wrist/hand movement from intramuscular EMG, how subjects used the simultaneous myoelectric control in a virtual task, and the potential for providing improved controllability compared to sequential control methods.
Fri Jan 23
Speaker: Tommaso Lenzi, PhD
Title: User-Adaptive Control of Powered Transfemoral Prostheses: Leveraging Robotics to Meet the Clinical Needs of the Amputee Population
Abstract: Robotic leg prostheses can actively regulate joint torque to emulate the full biomechanical functionality of the healthy limb, possibly restoring physiological gait efficiency and stability. However, proper emulation of the healthy limb depends on how well the prosthesis controller synchronizes the movement of the leg with the movement of the user. To this end, available control strategies rely on experimental, user-specific tuning that optimizes the leg behavior for the user’s preferred speed and cadence. Outside the tuned speed and cadence the prosthesis does not properly synchronize with the movement of the user, thus impairing walking ability. In addition, the tuning process is time consuming and requires expertise in robotics, which considerably limits the clinical viability of powered robotic legs. We have developed a new controller that automatically adapts to the user’s speed and cadence, providing physiological gait symmetry and joint energetics without need for tuning. The talk will describe the design, implementation, and preliminary validation of the new controller on transfemoral amputee patients.
Tue Jan 6
Speaker: Mingbo Cai
Title: Time perception - impact of expectation and duration cue combination
Abstract: Our perception of duration can be biased by many factors, including both stimulus history and stimulus properties. In this talk, I am going to present results from psychophysical experiments and modeling work to answer two questions: (1) is the influence of stimulus history on perceived duration due to the expectation of a stimulus or purely because of stimulus repetition? (2) How does the brain form a representation of duration when simultaneously presented stimuli provide conflicting cues of duration?
Host: Dr. Kording