Feasibility of carotid artery stenting with double cerebral embolic protection in high-risk patients.

BACKGROUND: Previous trials comparing carotid artery stenting (CAS) with carotid endarterectomy have shown that the former can increase the stroke rate. However, in the last years, because of the improvements either of the technique or the improvement of the stents and embolic protection devices (EPD), CAS has become a very competitive procedure. In this study, we tried to assess the feasibility and the safety of using double EPD (proximal and distal) in high-risk patients. METHODS: We collected data about all consecutive patients with carotid artery stenosis who underwent CAS and compared clinical and procedural characteristics as well as immediate and 30-day outcomes between the use of double vs. single EPD. RESULTS: Between November 2007 and August 2014, 294 patients underwent CAS. In 35 of them (11.9%) double EPD was used. In comparison with the patients treated with single EPD, those with double EPD presented more with acute carotid syndrome (recurrent TIAs < 48 hr, minor stroke < 14 days) and with complex plaque (79.4 vs. 33.6%, P < 0.0001). There was no difference between the 2 groups in primary success (100 vs. 99.6%, P = 0.16) and in 30-days major complications: death (0 vs. 0.8%, P = 0.6), major stroke (0 vs. 0.8%, P = 0.42), and minor stroke (0 vs 1.1%, P = 0.66). CONCLUSIONS: In our experience, in high-risk patients with high-risk lesions, the use of double EPD (proximal and distal) is safe and effective in minimizing the risk of cerebral embolization, but, to validate such a technique in wide range of patients, further studies are warranted.

Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion.

This work presents an electrophysiologically and dynamically consistent musculoskeletal model to predict stiffness in the human ankle and knee joints as derived from the joints constituent biological tissues (i.e., the spanning musculotendon units). The modeling method we propose uses electromyography (EMG) recordings from 13 muscle groups to drive forward dynamic simulations of the human leg in five healthy subjects during overground walking and running. The EMG-driven musculoskeletal model estimates musculotendon and resulting joint stiffness that is consistent with experimental EMG data as well as with the experimental joint moments. This provides a framework that allows for the first time observing 1) the elastic interplay between the knee and ankle joints, 2) the individual muscle contribution to joint stiffness, and 3) the underlying co-contraction strategies. It provides a theoretical description of how stiffness modulates as a function of muscle activation, fiber contraction, and interacting tendon dynamics. Furthermore, it describes how this differs from currently available stiffness definitions, including quasi-stiffness and short-range stiffness. This work offers a theoretical and computational basis for describing and investigating the neuromuscular mechanisms underlying human locomotion.

Validity and reliability of the Barthel index administered by telephone.

BACKGROUND AND PURPOSE: We aimed to evaluate validity and reliability of the Barthel Index administered telephonically compared with face-to-face assessment in clinically stable patients with stroke. METHODS: One hundred thirty-one patients were interviewed twice by 2 registered nurses with identical training. Half of the patients were randomized to receive the telephone interview followed by the face-to-face interview and half the contrary. The sequence of interviewers was randomized. RESULTS: The median value of the Barthel Index score was 30 (first to third interquartile range, 15 to 80) by telephone and 35 (15 to 75) by face-to-face (P=0.29). The weighted κ was 0.90 (95% CI, 0.85 to 0.94); κ values ranged from 0.70 (0.58 to 0.82) for bowel control to 0.91 (0.83 to 0.99) for bathing. CONCLUSIONS: Telephone assessment of stroke disability with the Barthel Index is reliable in comparison to direct face-to-face assessment.

BOPS: a Matlab toolbox to batch musculoskeletal data processing for OpenSim.

This paper presents Batch OpenSim Processing Scripts (BOPS), a Matlab toolbox for batch processing common OpenSim procedures: Inverse Kinematics, Inverse Dynamics, Muscle Analysis, Static Optimization, and Joint Reaction Analysis. BOPS is an easy-to-use and highly configurable tool that aims to reduce the time required to process large datasets, thus fostering the adoption of musculoskeletal modeling and simulations in daily practice. Its graphical user interface includes pre-defined setup files and has been designed to fulfill the needs of different research projects by simplifying the customization of the procedures, facilitating the analysis, and boosting research group collaborations. BOPS is released under Apache License 2.0, and its source code is freely available on SimTK and GitHub.

Myeloneuropathy due to copper deficiency: clinical and MRI findings after copper supplementation.

Acquired copper deficiency constitutes an under-recognised cause of myelopathy. Aim of the study was to describe the clinical and imaging features at admission and after copper supplementation of a patient with acquired copper deficiency myeloneuropathy. A 73-year-old woman presented with anaemia and signs of posterior column dysfunction. Somatosensory evoked potentials showed impaired central pathway conduction. Serum copper and caeruloplasmin levels were low. Nerve conduction assessment revealed axonal polyneuropathy. Spinal magnetic resonance imaging (MRI) showed posterior column hyperintensity. Diffusion tensor imaging disclosed decreased fractional anisotropy (FA) corresponding to the hyperintensity. Copper supplementation normalised the haematological picture, whereas vibratory sensitivity was only slightly improved. Control MRI revealed a slight hyperintensity at C1-C2 level; FA values normalised. In conclusion, in acquired copper-deficiency-associated myelopathy, correction of blood and MRI alterations precedes that of neurological manifestations, which may remain suboptimal.

Comparison of six electromyography acquisition setups on hand movement classification tasks.

Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements. The acquisition setups are based on four different sEMG electrodes (including Otto Bock, Delsys Trigno, Cometa Wave + Dormo ECG and two Thalmic Myo armbands) and they were used to record more than 50 hand movements from intact subjects with a standardized acquisition protocol. The relative performance of the six sEMG acquisition setups is compared on 41 identical hand movements with a standardized feature extraction and data analysis pipeline aimed at performing hand movement classification. Comparable classification results are obtained with three acquisition setups including the Delsys Trigno, the Cometa Wave and the affordable setup composed of two Myo armbands. The results suggest that practical sEMG tests can be performed even when costs are relevant (e.g. in small laboratories, developing countries or use by children). All the presented datasets can be used for offline tests and their quality can easily be compared as the data sets are publicly available.

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces.

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.

Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.

A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par.

Estimating EMG signals to drive neuromusculoskeletal models in cyclic rehabilitation movements.

A main challenge in the development of robotic rehabilitation devices is how to understand patient's intentions and adapt to his/her current neuro-physiological capabilities. A promising approach is the use of electromyographic (EMG) signals which reflect the actual activation of the muscles during the movement and, thus, are a direct representation of user's movement intention. However, EMGs acquisition is a complex procedure, requiring trained therapists and, therefore, solutions based on EMG signals are not easily integrable in devices for home-rehabilitation. This work investigates the effectiveness of a subject- and task-specific EMG model in estimating EMG signals in cyclic plantar-dorsiflexion movements. Then, the outputs of this model are used to drive CEINMS toolbox, a state-of-the-art EMG-driven neuromusculoskeletal model able to predict joint torques and muscle forces. Preliminary results show that the proposed methodology preserves the accuracy of the estimates values.

MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation.

BACKGROUND: Neuromusculoskeletal modeling and simulation enable investigation of the neuromusculoskeletal system and its role in human movement dynamics. These methods are progressively introduced into daily clinical practice. However, a major factor limiting this translation is the lack of robust tools for the pre-processing of experimental movement data for their use in neuromusculoskeletal modeling software. RESULTS: This paper presents MOtoNMS (matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal applications), a toolbox freely available to the community, that aims to fill this lack. MOtoNMS processes experimental data from different motion analysis devices and generates input data for neuromusculoskeletal modeling and simulation software, such as OpenSim and CEINMS (Calibrated EMG-Informed NMS Modelling Toolbox). MOtoNMS implements commonly required processing steps and its generic architecture simplifies the integration of new user-defined processing components. MOtoNMS allows users to setup their laboratory configurations and processing procedures through user-friendly graphical interfaces, without requiring advanced computer skills. Finally, configuration choices can be stored enabling the full reproduction of the processing steps. MOtoNMS is released under GNU General Public License and it is available at the SimTK website and from the GitHub repository. Motion data collected at four institutions demonstrate that, despite differences in laboratory instrumentation and procedures, MOtoNMS succeeds in processing data and producing consistent inputs for OpenSim and CEINMS. CONCLUSIONS: MOtoNMS fills the gap between motion analysis and neuromusculoskeletal modeling and simulation. Its support to several devices, a complete implementation of the pre-processing procedures, its simple extensibility, the available user interfaces, and its free availability can boost the translation of neuromusculoskeletal methods in daily and clinical practice.

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction.

Reliability of the modified Rankin Scale applied by telephone.

We aimed to evaluate the reliability of the modified Rankin Scale applied telephonically compared with face-to-face assessment in clinically stable hospitalized patients with acute stroke. One hundred and thirty-one patients were interviewed twice by 2 certified nurses (unstructured interview). Half of the patients were randomized to be interviewed by telephone followed by the face-to-face assessment, and half in the reverse order. The median value of the modified Rankin Scale score was 4 (first to third interquartile range 3-5) by telephone as well as by face-to-face assessment (P=0.8). The weighted kappa between the two methods was 0.82 (95% confidence interval: 0.77-0.88). Sensitivity of the telephone assessment was lower for scores 2 and 3 (17% and 46%, respectively) than for the other scores (range 67-90%). Telephone assessment of stroke disability with the modified Rankin Scale is reliable in comparison to direct face-to-face assessment.

EMG-driven forward-dynamic estimation of muscle force and joint moment about multiple degrees of freedom in the human lower extremity.

This work examined if currently available electromyography (EMG) driven models, that are calibrated to satisfy joint moments about one single degree of freedom (DOF), could provide the same musculotendon unit (MTU) force solution, when driven by the same input data, but calibrated about a different DOF. We then developed a novel and comprehensive EMG-driven model of the human lower extremity that used EMG signals from 16 muscle groups to drive 34 MTUs and satisfy the resulting joint moments simultaneously produced about four DOFs during different motor tasks. This also led to the development of a calibration procedure that allowed identifying a set of subject-specific parameters that ensured physiological behavior for the 34 MTUs. Results showed that currently available single-DOF models did not provide the same unique MTU force solution for the same input data. On the other hand, the MTU force solution predicted by our proposed multi-DOF model satisfied joint moments about multiple DOFs without loss of accuracy compared to single-DOF models corresponding to each of the four DOFs. The predicted MTU force solution was (1) a function of experimentally measured EMGs, (2) the result of physiological MTU excitation, (3) reflected different MTU contraction strategies associated to different motor tasks, (4) coordinated a greater number of MTUs with respect to currently available single-DOF models, and (5) was not specific to an individual DOF dynamics. Therefore, our proposed methodology has the potential of producing a more dynamically consistent and generalizable MTU force solution than was possible using single-DOF EMG-driven models. This will help better address the important scientific questions previously approached using single-DOF EMG-driven modeling. Furthermore, it might have applications in the development of human-machine interfaces for assistive devices.

Modeling the human knee for assistive technologies.

In this paper, we use motion capture technology together with an EMG-driven musculoskeletal model of the knee joint to predict muscle behavior during human dynamic movements. We propose a muscle model based on infinitely stiff tendons and show this allows speeding up 250 times the computation of muscle force and the resulting joint moment calculation with no loss of accuracy with respect to the previously developed elastic-tendon model. We then integrate our previously developed method for the estimation of 3-D musculotendon kinematics in the proposed EMG-driven model. This new code enabled the creation of a standalone EMG-driven model that was implemented and run on an embedded system for applications in assistive technologies such as myoelectrically controlled prostheses and orthoses.

Fibrinolytic activity and platelet function in subjects with obstructive sleep apnoea and a patent foramen ovale: is there an option for prevention of ischaemic stroke?

Obstructive sleep apnoea (OSA) carries an increased risk of ischaemic stroke, but the underlying mechanism is not clear. As right-to-left shunting can occur through a patent foramen ovale (PFO) during periods of apnoea, we investigated nocturnal changes in fibrinolytic activity and platelet function in subjects who had OSA with or without PFO and in controls. We determined plasminogen activator inhibitor 1 (PAI-1) activity and antigen and platelet activation parameters. The severity of OSA was verified by polygraphy and PFO was detected by ear oximetry. We found a higher PAI-1 activity and antigen and a lower ratio of 2,3-dinor-PGF(1α) to 2,3-dinor-TXB(2) in the subjects with OSA than in the controls. Linear regression analysis showed the apnoea-hypopnoea index (ß-coefficient, 0.499; P = 0.032) and PFO (ß-coefficient, 0.594; P = 0.015) to be associated independently with PAI-1 activity in the morning, while the increment in PAI-1:Ag from evening to morning was significantly associated with the presence of PFO (r(s) = 0.563, P = 0.002). Both OSA and PFO reduce fibrinolytic activity during nocturnal sleep. We hypothesize that subjects having both OSA and PFO may develop a more severe prothrombotic state during sleep than those having either OSA or PFO alone.

Estimation of musculotendon kinematics in large musculoskeletal models using multidimensional B-splines.

We present a robust and computationally inexpensive method to estimate the lengths and three-dimensional moment arms for a large number of musculotendon actuators of the human lower limb. Using a musculoskeletal model of the lower extremity, a set of values was established for the length of each musculotendon actuator for different lower limb generalized coordinates (joint angles). A multidimensional spline function was then used to fit these data. Muscle moment arms were obtained by differentiating the musculotendon length spline function with respect to the generalized coordinate of interest. This new method was then compared to a previously used polynomial regression method. Compared to the polynomial regression method, the multidimensional spline method produced lower errors for estimating musculotendon lengths and moment arms throughout the whole generalized coordinate workspace. The fitting accuracy was also less affected by the number of dependent degrees of freedom and by the amount of experimental data available. The spline method only required information on musculotendon lengths to estimate both musculotendon lengths and moment arms, thus relaxing data input requirements, whereas the polynomial regression requires different equations to be used for both musculotendon lengths and moment arms. Finally, we used the spline method in conjunction with an electromyography driven musculoskeletal model to estimate muscle forces under different contractile conditions, which showed that the method is suitable for the integration into large scale neuromusculoskeletal models.

A neuromusculoskeletal model of the human lower limb: towards EMG-driven actuation of multiple joints in powered orthoses.

This paper presents a novel neuromusculoskeletal (NMS) model of the human lower limb that uses the electromyo-graphic (EMG) signals from 16 muscles to estimate forces generated by 34 musculotendon actuators and the resulting joint moments at the hip, knee and ankle joints during varied contractile conditions. Our proposed methodology allows overcoming limitations on force computation shown by currently available NMS models, which constrain the operation of muscles to satisfy joint moments about one single degree of freedom (DOF) only (i.e. knee flexion-extension). The design of advanced human machine interfaces can benefit from the application of our proposed multi-DOF NMS model. The better estimates of the human internal state it provides with respect to single-DOF NMS models, will allow designing more intuitive human-machine interfaces for the simultaneous EMG-driven actuation of multiple joints in lower limb powered orthoses.