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Background: Stroke-induced ischemia affects both cortex and underlying white matter. Dalfampridine extended release tablets (D-ER) enhance action potential conduction in demyelinated axons, which may positively affect post-stroke recovery. Objective: Based on promising preliminary data, we compared efficacy of D-ER administered at 7.5 mg or 10 mg with placebo on post-stroke ambulation. Primary study outcome (response) was a ≥20% increase on the 2-minute walk test (2 MinWT) at 12 weeks after first drug administration. Methods: This was a multicenter, randomized, placebo-controlled, 3-arm, parallel-group, safety and efficacy trial. After obtaining baseline measures of 2 MinWT, Walk-12, and Timed Up and Go, subjects entered a 2-week, single-blind placebo run-in period and were randomized 1:1:1 to receive 7.5 mg D-ER, 10 mg D-ER, or placebo, dosed twice-daily for 12 weeks. Follow-up evaluations occurred at weeks 14 and 16 when subjects were off study drug. Results: The study was terminated early with 377 of planned 540 patients enrolled, due to no treatment effect. At week 12, mean increase in distances walked in 2 minutes were similar among the 3 study groups (14.9±40.0 feet; 19.4±39.6 feet; and 20.4±38.3 feet for placebo, 7.5 mg D-ER, and 10 mg D-ER, respectively). The proportion of subjects who showed ≥20% improvement on 2 MinWT at week 12 was 13.5%, 14.0%, and 19.0%, for placebo, 7.5 mg D-ER, and 10 mg D-ER, respectively; these were nonsignificant changes from baseline for all groups. Conclusions: D-ER at either a 7.5-mg or 10-mg dose did not significantly increase performance on the 2 MinWT in stroke survivors with gait impairment, although this study was terminated early before full enrollment. (Clinical Trial # NCT02271217).

Supplemental digital content is available in the text., Objectives The aims of the study were to evaluate integration of musculoskeletal ultrasonography education in physical medicine and rehabilitation training programs in 2014–2015, when the American Academy of Physical Medicine & Rehabilitation and Accreditation Council for Graduate Medical Education Residency Review Committee both recognized it as a fundamental component of physiatric practice, to identify common musculoskeletal ultrasonography components of physical medicine and rehabilitation residency curricula, and to identify common barriers to integration. Design Survey of 78 Accreditation Council for Graduate Medical Education–accredited physical medicine and rehabilitation residency programs was conducted. Results The 2015 survey response rate was more than 50%, and respondents were representative of programs across the United States. Most programs (80%) reported teaching musculoskeletal ultrasonography, whereas a minority (20%) required mastery of ultrasonography skills for graduation. Ultrasonography curricula varied, although most programs agreed that the scope of resident training in physical medicine and rehabilitation should include diagnostic and interventional musculoskeletal ultrasonography, especially for key joints (shoulder, elbow, knee, wrist, hip, and ankle) and nerves (median, ulnar, fibular, tibial, radial, and sciatic). Barriers to teaching included insufficient expertise of instructors, poor access to equipment, and lack of a structured curriculum. Conclusions Musculoskeletal ultrasonography has become a required component of physical medicine and rehabilitation residency training. Based on survey responses and expert recommendations, we propose a structure for musculoskeletal ultrasonography curricular standards and milestones for trainee competency.

OBJECTIVES Our purpose was to determine whether ultrasound (US)-aided instruction and practice on musculoskeletal anatomy would improve first-year medical students' ability to locate and identify specific soft tissue structures by unaided palpation in the upper and lower extremities of healthy human models. METHODS This study was a randomized crossover design with 49 first-year medical students randomly assigned to 1 of 2 groups. Each group was provided expert instruction and hands-on practice using US to scan and study soft tissue structures. During session 1, group A learned the anatomy of the upper extremities, whereas group B learned the lower. Students were then tested on their proficiency in locating 4 soft tissue structures (2 upper and 2 lower extremities) through palpation of a human model. During session 2, group A learned lower extremities, and group B learned upper. At the end of session 2, students repeated the assessment. RESULTS After the first instructional session, neither group performed significantly better on identifying and locating the soft tissue landmarks they learned aided by US. After the second instructional session, however, scores for both groups increased approximately 20 percentage points, indicating that both groups performed significantly better on palpating and identifying both the upper and lower extremity soft tissue landmarks (Cohen d = 0.89 and 0.82, respectively). CONCLUSIONS Time and practice viewing soft tissue structures with US assistance seems to have a "palpation-with-eyes" effect that improves students' abilities to correctly locate, palpate, and identify limb-specific soft tissue structures once the US assistance is removed.

Objectives Ultrasound imaging is commonly used to teach basic anatomy to medical students. The purpose of this study was to determine whether learning musculoskeletal anatomy with ultrasound improved performance on medical students' musculoskeletal physical examination skills. Methods Twenty-seven first-year medical students were randomly assigned to 1 of 2 instructional groups: either shoulder or knee. Both groups received a lecture followed by hands-on ultrasound scanning on live human models of the assigned joint. After instruction, students were assessed on their ability to accurately palpate 4 anatomic landmarks: the acromioclavicular joint, the proximal long-head biceps tendon, and the medial and lateral joint lines of the knee. Performance scores were based on both accuracy and time. A total physical examination performance score was derived for each joint. Scores for instructional groups were compared by a 2-way analysis of variance with 1 repeated measure. Significant findings were further analyzed with post hoc tests. Results All students performed significantly better on the knee examination, irrespective of instructional group (F = 14.9; df = 1.25; P = .001). Moreover, the shoulder instruction group performed significantly better than the knee group on the overall assessment (t = –3.0; df = 25; P

Objective: Individuals with paralysis often have mobility and dexterity impairments that limit their ability to operate motor vehicle controls. Integrating brain-machine interface (BMI) neurotechnology with vehicle control systems (VCS) provides a novel solution to this problem. In this proof-of-concept study, we show that an intracortical BMI developed to restore voluntary grasp can be repurposed to decode motor intention for vehicle velocity and steering control. Methods: The BMI-VCS consists of four components: 1) implanted motor cortex microelectrode array and NeuroPort data acquisition system, 2) machine learning workstation, 3) Python interface to generate control signals, and 4) vehicle control system. Results: Direct cortical steering and velocity control were achieved through accurate decoding of movement intention (supination, pronation, hand open, hand close) from the participant’s motor cortex, translating intention into vehicle commands (turn right, turn left, accelerate, decelerate, respectively), and dynamically switching between commands to turn corners, start and stop, shift from forward to reverse, and parallel park. Conclusion: By translating BMI decoder outputs into high-level vehicle commands, a participant with tetraparesis from C5 ASIA A spinal cord injury successfully navigated CARLA driving simulator courses in real time. These decoder outputs could also be used offline for shared control of a scale model car. Significance: High-level, shared vehicle control with BMI-VCS offers an innovative way to return independent driving abilities to those with disability. BMI systems that can control multiple end-effectors may be particularly useful to those with paralysis.

Date Presented Accepted for AOTA INSPIRE 2021 but unable to be presented due to online event limitations. Both action observation and repetitive-task practice are efficacious interventions for poststroke upper limb hemiplegia individually, yet these interventions have not been combined before. A feasibility study was completed to determine preliminary evidence of the response to intervention and whether a Phase III study should be completed to test efficacy of the combined intervention. The functional impact of improving poststroke upper limb performance could benefit millions of stroke survivors. Primary Author and Speaker: Christine Griffin Contributing Authors: Marcia Bockbrader, Erinn Hade, Anne Kloos, John A. Buford

Laboratory demonstrations of brain-computer interface (BCI) systems show promise for reducing disability associated with paralysis by directly linking neural activity to the control of assistive devices. Surveys of potential users have revealed several key BCI performance criteria for clinical translation of such a system. Of these criteria, high accuracy, short response latencies, and multi-functionality are three key characteristics directly impacted by the neural decoding component of the BCI system, the algorithm that translates neural activity into control signals. Building a decoder that simultaneously addresses these three criteria is complicated because optimizing for one criterion may lead to undesirable changes in the other criteria. Unfortunately, there has been little work to date to quantify how decoder design simultaneously affects these performance characteristics. Here, we systematically explore the trade-off between accuracy, response latency, and multi-functionality for discrete movement classification using two different decoding strategies – a support vector machine (SVM) classifier which represents the current state-of-the-art for discrete movement classification in laboratory demonstrations and a proposed deep neural network (DNN) framework. We utilized historical intracortical recordings from a human tetraplegic study participant, who imagined performing several different hand and finger movements. For both decoders, we found that response time increases (i.e. slower reaction) and accuracy decreases as the number of functions increases. However, we also found that both the increase of response times and the decline in accuracy with additional functions is less for the DNN than the SVM. We also show that data preprocessing steps can affect the performance characteristics of the two decoders in drastically different ways. Finally, we evaluated the performance of our tetraplegic participant using the DNN decoder in real-time to control functional electrical stimulation (FES) of his paralyzed forearm. We compared his performance to that of able-bodied participants performing the same task, establishing a quantitative target for ideal BCI-FES performance on this task. Cumulatively, these results help quantify BCI decoder performance characteristics relevant to potential users and the complex interactions between them.

One innovation currently influencing physical medicine and rehabilitation is brain-computer interface (BCI) technology. BCI systems used for motor control record neural activity associated with thoughts, perceptions, and motor intent; decode brain signals into commands for output devices; and perform the user's intended action through an output device. BCI systems used for sensory augmentation transduce environmental stimuli into neural signals interpretable by the central nervous system. Both types of systems have potential for reducing disability by facilitating a user's interaction with the environment. Investigational BCI systems are being used in the rehabilitation setting both as neuroprostheses to replace lost function and as potential plasticity-enhancing therapy tools aimed at accelerating neurorecovery. Populations benefitting from motor and somatosensory BCI systems include those with spinal cord injury, motor neuron disease, limb amputation, and stroke. This article discusses the basic components of BCI for rehabilitation, including recording systems and locations, signal processing and translation algorithms, and external devices controlled through BCI commands. An overview of applications in motor and sensory restoration is provided, along with ethical questions and user perspectives regarding BCI technology.

Background Understanding the long-term behavior of intracortically-recorded signals is essential for improving the performance of Brain Computer Interfaces. However, few studies have systematically investigated chronic neural recordings from an implanted microelectrode array in the human brain. Methods In this study, we show the applicability of wavelet decomposition method to extract and demonstrate the utility of long-term stable features in neural signals obtained from a microelectrode array implanted in the motor cortex of a human with tetraplegia. Wavelet decomposition was applied to the raw voltage data to generate mean wavelet power (MWP) features, which were further divided into three sub-frequency bands, low-frequency MWP (lf-MWP, 0–234 Hz), mid-frequency MWP (mf-MWP, 234 Hz–3.75 kHz) and high-frequency MWP (hf-MWP, >3.75 kHz). We analyzed these features using data collected from two experiments that were repeated over the course of about 3 years and compared their signal stability and decoding performance with the more standard threshold crossings, local field potentials (LFP), multi-unit activity (MUA) features obtained from the raw voltage recordings. Results All neural features could stably track neural information for over 3 years post-implantation and were less prone to signal degradation compared to threshold crossings. Furthermore, when used as an input to support vector machine based decoding algorithms, the mf-MWP and MUA demonstrated significantly better performance, respectively, in classifying imagined motor tasks than using the lf-MWP, hf-MWP, LFP, or threshold crossings. Conclusions Our results suggest that using MWP features in the appropriate frequency bands can provide an effective neural feature for brain computer interface intended for chronic applications. Trial registration This study was approved by the U.S. Food and Drug Administration (Investigational Device Exemption) and the Ohio State University Medical Center Institutional Review Board (Columbus, Ohio). The study conformed to institutional requirements for the conduct of human subjects and was filed on ClinicalTrials.gov (Identifier NCT01997125). Electronic supplementary material The online version of this article (10.1186/s42234-018-0011-x) contains supplementary material, which is available to authorized users.

Exposure to musculoskeletal ultrasound (MSUS) is now a mandatory component of physical medicine and rehabilitation (PMR) residency training. However, reports on the extent of the implementation and efficacy of MSUS education are lacking in the literature.To determine the extent to which PMR residencies are implementing MSUS education.Cross-sectional.Institutional.Thirty-six of the 78 United States PMR residency programs accredited by the Accreditation Council for Graduate Medical Education.All 78 programs were solicited with an online survey via the residency program director and coordinator in July 2014. The 25 questions on the survey were aimed at determining program MSUS educational characteristics and their effectiveness.Description of teaching methods used for MSUS, residency demographics, characteristics of MSUS faculty expertise, and faculty-perceived competency in MSUS examinations and procedures among residents. Data were analyzed using both descriptive statistics and tests for independence to identify correlations between program characteristics and resident MSUS competency.A response was received from 36 of the 78 residency programs (46.2%). Of the 36 residency programs that responded, 97.2% provide exposure to MSUS (a figure that drops to 44.9% when nonrespondents are included); 61% had mandatory MSUS training (28.2% when including nonrespondents); and 44.4% had a formal curriculum (20.5% when including nonrespondents). The most common MSUS educational tools used were lecture (88.9%), outpatient clinic (86.1%), and hands-on workshops (86.1%). Sixty-one percent of responding programs evaluate residents with formal assessment tools. Overall, faculty at 38.8% and 44.4% of programs believed that at least 50% of residents who graduate are competent in diagnostic and interventional MSUS, respectively. These rates were significantly associated with the use of formal assessment.MSUS education is growing in PMR, but many programs still have not adopted a formal educational curriculum. Formal assessment to evaluate resident MSUS skills significantly improves faculty-perceived MSUS competency.

Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.

Millions of people worldwide suffer from diseases that lead to paralysis through disruption of signal pathways between the brain and the muscles. Neuroprosthetic devices are designed to restore lost function and could be used to form an electronic 'neural bypass' to circumvent disconnected pathways in the nervous system. It has previously been shown that intracortically recorded signals can be decoded to extract information related to motion, allowing non-human primates and paralysed humans to control computers and robotic arms through imagined movements. In non-human primates, these types of signal have also been used to drive activation of chemically paralysed arm muscles. Here we show that intracortically recorded signals can be linked in real-time to muscle activation to restore movement in a paralysed human. We used a chronically implanted intracortical microelectrode array to record multiunit activity from the motor cortex in a study participant with quadriplegia from cervical spinal cord injury. We applied machine-learning algorithms to decode the neuronal activity and control activation of the participant's forearm muscles through a custom-built high-resolution neuromuscular electrical stimulation system. The system provided isolated finger movements and the participant achieved continuous cortical control of six different wrist and hand motions. Furthermore, he was able to use the system to complete functional tasks relevant to daily living. Clinical assessment showed that, when using the system, his motor impairment improved from the fifth to the sixth cervical (C5-C6) to the seventh cervical to first thoracic (C7-T1) level unilaterally, conferring on him the critical abilities to grasp, manipulate, and release objects. This is the first demonstration to our knowledge of successful control of muscle activation using intracortically recorded signals in a paralysed human. These results have significant implications in advancing neuroprosthetic technology for people worldwide living with the effects of paralysis.

There is a need for consistent, repetitive, and reliable terminology to describe the basic manipulations of the ultrasound transducer. Previously, 5 basic transducer motions have been defined and used in education. However, even with this effort, there is still a lack of consistency and clarity in describing transducer manipulation and motion. In this technical innovation, we describe an expanded definition of transducer motions, which include movements to change the transducer's angle of insonation to the target as well as the location on the body to optimize the ultrasound image. This new terminology may allow for consistent teaching and improved communication in the process of image acquisition.

Background Interactive arts technologies, designed to augment the acute neurorehabilitation provided by expert therapists, may overcome existing barriers of access for patients with low motor and cognitive function. Objectives Develop an application prototype to present movement feedback interactively and creatively. Evaluate feasibility of use within acute neurorehabilitation. Methods Record demographics and Functional Independent Measure™ scores among inpatients who used the technology during physical, occupational or recreational therapy. Record exercises performed with the technology, longest exercise duration performed (calculated from sensor data), user feedback, and therapist responses to a validated technology assessment questionnaire. Results Inpatients (n = 21) between the ages of 19 and 86 (mean 57 ± 18; 12 male/9 female) receiving treatment for motor deficits associated with neuropathology used the application in conjunction with occupational, recreational, or physical therapy during 1 to 7 sessions. Patients classified on the Functional Independence Measure™ as requiring 75%+ assistance for cognitive and motor function were able to use the interactive application. Conclusions Customized interactive arts applications are appropriate for further study as a therapeutic modality. In addition to providing interactivity to individuals with low motor function, interactive arts applications might serve to augment activity-based medicine among inpatients with low problem-solving and memory function.

Intensity-modulated radiation therapy (IMRT) represents a powerful advance in the planning and delivery of radiation therapy owing to its ability to deliver highly conformal treatment doses while sparing normal tissues. Dosimetric studies have shown the feasibility and theoretical benefit of treating with IMRT over 3D-conformal radiation therapy in gastrointestinal malignancies. Early clinical experience with IMRT in the treatment of gastric, pancreatic, rectal and anal cancers corroborates the dosimetric analyses, with some series reporting lower normal tissue toxicities. This article reviews the radiobiological, physical, technical and clinical aspects of IMRT for gastric, pancreatic, rectal and anal cancer, and summarizes the dosimetric and outcome studies to date.

reactions. Results or Clinical Course: Records from 254 consecutive patients were reviewed; 93 patients fulfilled the inclusion criteria. Patients were 16e82 years of age (mean 46.5 years) at the start of treatment and 59.1% were male. Spasticity was mainly due to stroke (40.9%), cerebral palsy (25.8%) or multiple sclerosis (18.3%). Patients had been treated with onabotulinumtoxinA for 3e55 months (mean 16 months) before receiving incobotulinumtoxinA for 7e73 months (mean 39 months). At the last 3 onabotulinumtoxinA treatments, the mean doses administered were 143.3U, 147.2U and 143.9U, given on average 125.2, 141.5 and 194.2 days after the previous injection. At the first 3 incobotulinumtoxinA treatments after switching, patients received mean doses of 156.0U, 140.9U and 136.9U, given on average 163.8, 167.4 and 135.5 days after the previous treatment. No adverse reactions occurred with either BoNT-A formulation. Conclusion: In our spasticity outpatient clinic, switching BoNT-A formulation from onabotulinumtoxinA to incobotulinumtoxinA at a 1:1 unit dose ratio did not affect dose requirements or treatment intervals, indicating that both products were similarly efficacious. Tolerability profiles were also similar, with no adverse reactions recorded for either formulation.