Improving signal reliability for on-line joint angle estimation from nerve cuff recordings of muscle afferents

Closed-loop functional electrical stimulation (FES) applications depend on sensory feedback, thus, it is important to continuously investigate new methods to obtain reliable feedback signals. The objective of the present paper was to examine the feasibility of using an artificial neural network (ANN) to predict joint angle from whole nerve cuff recordings of muscle afferent activity within a physiological range of motion. Furthermore, we estimated how small changes in joint angle that can be detected from the nerve cuff recordings. Neural networks were tested with data obtained from ten acute rabbit experiments in simulated, on-line experiments. The electroneurograms (ENG) of the tibial and peroneal nerves were recorded during passive ankle joint rotation. To decrease the joint angle prediction error with new rabbit data, we attempted to pretune the nerve signals and re-trained the ANNs with the pretuned data. With these procedures we were able to compensate for interrabbit variability. On average the mean prediction errors were less than 2.0/spl deg/ (a total excursion of 20/spl deg/) and we were able to predict joint angles from muscle afferent activity with accuracy close to the best-estimated angular resolution. The angular resolution was found to depend on the initial joint angle and the actual step size taken and we found that there was a low probability of detecting joint angle changes less than 1.5/spl deg/. We thus suggest that muscle afferent activity is applicable as feedback in real-time closed-loop control, when the motion speed is restricted and when the movement is limited to a portion of the joint's physiological range.     

A comparison of models of force production during stimulated isometric ankle dorsiflexion in humans.

In this paper, we compare seven models on their ability to fit isometric muscle force. We stimulated the ankle dorsiflexors of eight subjects at seven ankle angles (85 degrees-120 degrees). Three different stimulation patterns (twitch, triangular, and random) were applied at all ankle angles. Four additional patterns (doublets, steady rates, "catch property," and walking-like) were applied at 95 degrees. Parameter values were optimized for each model at each angle. Parameters for the general linear model were calculated using a novel least-squares algorithm. A linear, second-order critically damped model gave the poorest fits (average root mean square (rms) error: 15 N). The models of Ding et al. (2002) and Bobet and Stein (1998) gave the best fits (average rms errors: 9.2 and 9.4 N). The other models (general linear second-order model, Wiener model, Zhou et al. (1995) model, general linear model) gave intermediate results. Results were similar at all ankle angles. We conclude that the Ding and Bobet-Stein models are the best overall for isometric contractions, that no linear model of any kind will give an error less than 9% of maximum force, and that the models tested are consistent across lengths.     

Shape and function from motion in medical imaging: part 2.

Much has been said about medical imaging and it is the intent of this paper to focus on the motion aspects during macroimaging. A classification is proposed that departs from the classical views by identifying motion from imaging and vice versa and involves correction of motion and evoked motion. Several aspects that introduce significant differences in camera vision deserve to be underlined. The complexity of the imaging process is a major point. This is exemplified for ultrasound imaging and medical resonance imaging as will be shown in this article. The nonstandard classification proposed in this article has attempted to show how specific features of medical imaging may affect motion extraction and tracking. If the main issues found in computer vision are also of concern in medical imaging, the importance of replacing the "black box" vision by an in-depth knowledge of object properties, the physics of the sensing device, and the interactions between them, has been emphasized. It has been pointed out that the standard assumptions in generic motion estimation methods are not verified due to the limitations in data acquisition, the complexity of tissues and organs, and the multiple factors that modify the appearances of the objects of interest. Most of the classical paradigms should benefit from prior modeling to attain a better understanding of physiological motion and to derive innovative ways for expanding its place in the diagnostic process.     

Role of afferent input in motor organization in health and disease.

In the healthy brain, there is a highly organized relationship between sensory input from one part of the body and the motor cortical output to muscles acting on that same part. This work investigates whether a change in purely sensory input have an impact on the organization of the motor cortex. In a previous study transcranial magnetic stimulation (TMS) techniques were used to probe the excitability of the motor cortex hand area. A measurement of the amplitude of the motor evoked potential (MEP) to standard single-pulse stimuli given through a focal coil was done. The excitability of two types of intracortical inhibition, SICI and LICI, was also measured using a paired-pulse TMS design. SICI is thought to be sensitive to activity in GABA/sub A/-ergic systems, whereas LICI may involve activation of GABA/sub B/-ergic systems. The work of other researchers has shown that these measures could be influenced by sensory input. Yet, all of them used electrical stimulation of peripheral nerve rather than a natural input. In order to investigate a more natural input, we delivered very low-amplitude vibration to the muscle belly of individual hand muscles through a small probe. This work explores the pattern of effects on MEPs and SICI in three different intrinsic hand muscles after vibration of each muscle in turn. In addition, the study also tested LICI with a paired-pulse TMS paradigm. In conclusion, it was seen that a period of sensory input, with or without the subject's attention, produces a specific pattern of sensory-motor reorganization in human cortex which develops quickly (after only 15 minutes) and lasts for at least 30 min. Since this produces changes in the motor cortex without requiring any active motor output, it may be a promising tool for neurorehabilitation even in patients who are unable to perform the active movements conventionally employed in therapy.     

A robot and control algorithm that can synchronously assist in naturalistic motion during body-weight-supported gait training following neurologic injury.

Locomotor training using body weight support on a treadmill and manual assistance is a promising rehabilitation technique following neurological injuries, such as spinal cord injury (SCI) and stroke. Previous robots that automate this technique impose constraints on naturalistic walking due to their kinematic structure, and are typically operated in a stiff mode, limiting the ability of the patient or human trainer to influence the stepping pattern. We developed a pneumatic gait training robot that allows for a full range of natural motion of the legs and pelvis during treadmill walking, and provides compliant assistance. However, we observed an unexpected consequence of the device's compliance: unimpaired and SCI individuals invariably began walking out-of-phase with the device. Thus, the robot perturbed rather than assisted stepping. To address this problem, we developed a novel algorithm that synchronizes the device in real-time to the actual motion of the individual by sensing the state error and adjusting the replay timing to reduce this error. This paper describes data from experiments with individuals with SCI that demonstrate the effectiveness of the synchronization algorithm, and the potential of the device for relieving the trainers of strenuous work while maintaining naturalistic stepping.     

Changes in the surface EMG signal and the biomechanics of motion during a repetitive lifting task

The analysis of surface electromyographic (EMG) data recorded from the muscles of the back during isometric constant-force contractions has been a useful tool for assessing muscle deficits in patients with lower back pain (LBP). Until recently, extending the technique to dynamic tasks, such as lifting, has not been possible due to the nonstationarity of the EMG signals. Recent developments in time-frequency analysis procedures to compute the instantaneous median frequency (IMDF) were utilized in this study to overcome these limitations. Healthy control subjects with no history of LBP (n=9; mean age 26.3/spl plusmn/6.7) were instrumented for acquisition of surface EMG data from six electrodes on the thoraco-lumbar region and whole-body kinematic data from a stereo-photogrammetric system. Data were recorded during a standardized repetitive lifting task (load=15% body mass; 12 lifts/min; 5-min duration). The task resulted in significant decreases in IMDF for six of the nine subjects, with a symmetrical pattern of fatigue among contralateral muscles and greater decrements in the lower lumbar region. For those subjects with a significant decrease in IMDF, a lower limb and/or upper limb biomechanical adaptation to fatigue was observed during the task. Increases in the peak box acceleration were documented. In two subjects, the acceleration doubled its value from the beginning to the end of the exercise, which lead to a significant increase in the torque at L4/L5. This observation suggests an association between muscle fatigue at the lumbar region and the way the subject manipulates the box during the exercise. Fatigue-related biomechanical adaptations are discussed as a possible supplement to functional capacity assessments among patients with LBP.     

Development and evaluation of a numerical simulation approach to predict metal artifacts from passive implants in MRI

Objective

This study presents the development and evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment that can be applied to improve the testing procedure for MR image artifacts in medical implants according to ASTM F2119.

Methods

The numerical approach is validated by comparing simulations and measurements of two metallic test objects made of titanium and stainless steel at three different field strengths (1.5T, 3T and 7T). The difference in artifact size and shape between the simulated and measured artifacts were evaluated. A trend analysis of the artifact sizes in relation to the field strength was performed.

Results

The numerical simulation approach shows high similarity (between 75% and 84%) of simulated and measured artifact sizes of metallic implants. Simulated and measured artifact sizes in relation to the field strength resulted in a calculation guideline to determine and predict the artifact size at one field strength (e.g., 3T or 7T) based on a measurement that was obtained at another field strength only (e.g. 1.5T).

Conclusion

This work presents a novel tool to improve the MR image artifact testing procedure of passive medical implants. With the help of this tool detailed artifact investigations can be performed, which would otherwise only be possible with substantial measurement effort on different MRI systems and field strengths.

     

Noninvasive measurement of torque development in the rat foot: measurement setup and results from stimulation of the sciatic nerve with polyimide-based cuff electrodes

In neural rehabilitation, selective activation of muscles after electrical stimulation is mandatory for control of paralyzed limbs. For an evaluation of electrode selectivity, a setup to noninvasively measure the force development after electrical stimulation in the rat foot was developed. The setup was designed in accordance to the anatomical features of the rat model to test the isometric torque development at given ankle positions in an intact leg. In this paper, the setup design and development is presented and discussed. In a first study, the selectivity of small nerve cuffs with 12 electrodes implanted around the rat sciatic nerve was investigated. Special attention was drawn to the performance of the torque measurement setup in comparison to electrophysiological data obtained from compound muscle action potential recordings. Using one cuff around the nerve, electrical stimulation on different electrode tripoles led to plantarflexion and dorsiflexion of the foot without an a priori alignment of the cuff.     

EMG and metabolite-based prediction of force in paralyzed quadriceps muscle under interrupted stimulation.

A major issue associated with functional electrical stimulation (FES) of a paralyzed limb is the decay with time of the muscle force as a result of fatigue. A possible means to reduce fatigue during FES is by using interrupted stimulation, in which fatigue and recovery occur in sequence. In this study, we present a model which enables us to evaluate the temporal force generation capacity within the electrically activated muscle during first stimulation fatigue, i.e., when the muscle is activated from unfatigued initial conditions, and during postrest stimulation, i.e., after different given rest durations. The force history of the muscle is determined by the activation as derived from actually measured electromyogram (EMG) data, and by the metabolic fatigue function expressing the temporal changes of muscle metabolites, from existing data acquired by in vivo 31P MR spectroscopy in terms of the inorganic phosphorus variables, Pi or H2PO4-, and by the intracellular pH. The model was solved for supra-maximal stimulation in isometric contractions separated by rest periods, and compared to experimentally obtained measurements. EMG data were fundamental for prediction of the ascending force during its posttetanic response. On the other hand, prediction of the decaying phase of the force was possible only by means of the metabolite-based fatigue function. The prediction capability of the model was assessed by means of the error between predicted and measured force profiles. The predicted force obtained from the model in first stimulation fatigue fits well with the experimental one. In postrest stimulation fatigue, the different metabolites provided different prediction capabilities of the force, depending on the duration of the rest period. Following rest duration of 1 min, Pi provided the best prediction of force; H2PO4- extended the prediction capacity of the model to up to 6 min and pH provided a reliable prediction for rest durations longer than 12 min. The results presented shed light on the roles of EMG and of metabolites in prediction of the force history of a paralyzed muscle under conditions where fatigue and recovery occur in sequence.     

Neural ensemble activity from multiple brain regions predicts kinematic and dynamic variables in a multiple force field reaching task.

In everyday life, we reach, grasp, and manipulate a variety of different objects all with their own dynamic properties. This degree of adaptability is essential for a brain-controlled prosthetic arm to work in the real world. In this study, rats were trained to make reaching movements while holding a torque manipulandum working against two distinct loads. Neural recordings obtained from arrays of 32 microelectrodes spanning the motor cortex were used to predict several movement related variables. In this paper, we demonstrate that a simple linear regression model can translate neural activity into endpoint position of a robotic manipulandum even while the animal controlling it works against different loads. A second regression model can predict, with 100% accuracy, which of the two loads is being manipulated by the animal. Finally, a third model predicts the work needed to move the manipulandum endpoint. This prediction is significantly better than that for position. In each case, the regression model uses a single set of weights. Thus, the neural ensemble is capable of providing the information necessary to compensate for at least two distinct load conditions.     

Segmentation of fascias, fat and muscle from magnetic resonance images in humans: the DISPIMAG software

Segmentation of human limb MR images into muscle, fat and fascias remains a cumbersome task. We have developed a new software (DISPIMAG) that allows automatic and highly reproducible segmentation of lower-limb MR images. Based on a pixel intensity analysis, this software does not need any previous mathematical or statistical assumptions. It displays a histogram with two main signals corresponding to fat and muscle, and permits an accurate quantification of their relative spatial distribution. To allow a systematic discrimination between muscle and fat in any subject, fixed boundaries were first determined manually in a group of 24 patients. Secondly, an entirely automatic process using these boundaries was tested by three operators on four patients and compared to the manual approach, showing a high concordance.     

The use of positron emission tomography and [18F]fluorodeoxyglucose for functional imaging of muscular activity during exercise with a stride assistance system.

The aim of this study was to investigate the use of [18F]fluorodeoxyglucose and positron emission tomography (FDG PET) for quantitative evaluation of glucose metabolism in skeletal muscle during walking. Ten young males underwent FDG PET twice during walks, which were done with or without an automated stride assistance system (SAS). Walk ratios were significantly increased by the SAS in seven subjects. Regional glucose metabolism in muscles between the crista iliaca and the planta was clearly visualized in all ten subjects. Glucose utilization increased significantly in the tibialis posterior and medial gastrocnemius muscles of the seven subjects in whom walk ratios were increased by the SAS. FDG PET is useful for analysis of muscle activity during exercise and rehabilitation.     

Unbalanced magnetic pull induced by arbitrary eccentric motion of cage rotor in transient operation. Part 2: Verification and numerical parameter estimation

Eccentric rotor motion of an electric motor induces an unbalanced magnetic pull. This eccentricity force can be described using a simple parametric model with physical parameters. This model allows an arbitrary rotor motion and transient operation. This paper presents an effective method to estimate the parameters from simulation results of electromagnetic fields. Further, the numerical results verify the form of the proposed parametric model in steady-state operation.     

Simulating tornado-like enhancement of heat transfer for low-velocity motion of air in a rectangular channel with cavities. Part 1: Selection and justification of calculation methods

Existing experimental data on the subject are briefly analyzed and the main objectives of calculation studies on the problem area are determined. Details of a calculation procedure are described, the choice of Menter’s shear stress transfer model is substantiated, and results are presented from testing a multiblock approach for numerically simulating hydrodynamics and heat transfer in low-velocity near-wall airflows.     

Condition assessment of 12- and 24-kV XLPE cables installed during the 80s. Results from a joint Norwegian/Swedish research project

This paper reports the results from the condition assessment of 12- and 24-kV cross-linked polyethylene (XPLE) cables using a technique based on dielectric spectroscopy initially developed at KTH in Sweden. The work aims to examine whether the method could detect water tree degradation for the second generation medium voltage (MV) cables with long, but not bridging, water trees. While the overall cable condition was better than expected for second generation XPLE cables, water trees were found in most of the selected cables. The diagnostic method based on the measurement of the dielectric response could only detect water tree degradation in the examined second generation cables when the water trees bridged the insulation wall. Condition assessment above service stress may, in some cases, be required to detect bridging water trees. The results indicate that there is a correlation between the voltage level and the breakdown voltage of the cable. This can be used as a diagnostic criterion for this group of cables.     

Morning to evening changes of intramyocellular lipid content in dependence on nutrition and physical activity during one single day: a volume selective 1H-MRS study

Object  

Intramyocellular lipids (IMCL) were shown to be metabolically highly active. In order to get insight into short-term regulation of IMCL and to reveal related problems with standardization in metabolic studies using the common signal ratio IMCL/Cr3, relative concentration changes from morning to evening in the same day were examined under four different nutritional and exercise conditions.     

Model of Inception and Growth of Damage from Microvoids in Polyethylene-based Materials for HVDC Cables. 1. Theoretical Approach

A comprehensive physical aging and life model is presented for damage inception and growth in polymeric insulation, starting at the level of microscopic cavities, that are known to be one of the most severe factors limiting design electric field and life of cable insulation. Degradation within a polyethylene-based material for HVDC cables is considered as a hot-electron induced bond-breaking process that cumulates with time into the polymer matrix at microvoid-polymer interface, fed by subsequent electron avalanches generated in microvoids. By this way, a conductive pit is formed, that may exceed eventually a critical size for the start-up of a rapid failure mechanism, thereby leading ultimately to electrical breakdown. The model, essentially based on the physical and microstructural characteristics of the insulation, is virtually free from disposable parameters. It is shown to reproduce qualitatively the dependence of insulation time to failure on applied field, temperature and cavity size and to fit quantitatively experimental times-to-failure relevant to PE-based materials in typical working conditions for HVDC cables. The first part of this paper presents the theoretical background and the derivation of model equations, as well as their discussion. The second part deals with parametric investigation and data fitting.