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The Fugl-Meyer Assessment is widely used to test motor function in stroke survivors. In the Fugl-Meyer Assessment, stroke survivors perform several movement tasks and clinicians subjectively rate the performance of each task item. The individual task items in the Fugl-Meyer Assessment are selected on the basis of clinical experience, and their physiological relevance has not yet been evaluated. In the present study, we aimed to objectively rate the performance of task items by measuring the muscle activity of 41 muscles from the upper body while stroke survivors and healthy participants performed 37 Fugl-Meyer Assessment upper extremity task items. We used muscle synergy analysis to compare muscle activity between subjects and found that 13 muscle synergies in the healthy participants (which we defined as standard synergies) were able to reconstruct all of the muscle activity in the Fugl-Meyer Assessment. Among the standard synergies, synergies involving the upper arms, forearms and fingers were activated to varying degrees during different task items. In contrast, synergies involving posterior trunk muscles were activated during all tasks, which suggests the importance of posterior trunk muscle synergies throughout all sequences. Furthermore, we noted the inactivation of posterior trunk muscle synergies in stroke survivors with severe but not mild impairments, suggesting that lower trunk stability and the underlying activity of posterior trunk muscle synergies may have a strong influence on stroke severity and recovery. By comparing the synergies of stroke survivors with standard synergies, we also revealed that some synergies in stroke survivors corresponded to merged standard synergies; the merging rate increased with the impairment of stroke survivors. Moreover, the degrees of severity-dependent changes in the merging rate (the merging rate-severity relationship) were different among different task items. This relationship was significant for 26 task items only and not for the other 11 task items. Because muscle synergy analysis evaluates coordinated muscle activities, this different dependency suggests that these 26 task items are appropriate for evaluating muscle coordination and the extent of its impairment in stroke survivors. Overall, we conclude that the Fugl-Meyer Assessment reflects physiological function and muscle coordination impairment and suggest that it could be performed using a subset of the 37 task items., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The L1-norm regularization is applied to ultrasonic reverberation characteristics imaging and vectoral Doppler measurement, of which performances are compared with those of L2-norm regularizations. The L1 regularization yields the sharper image than the L2 regularization. Alternatively, for the Doppler measurement, the L1 regularization yields less accuracy than the L2 regularization. Clinical Relevance- This study will permit us to perform quantitative ultrasonic reverberation characteristics and accurate vectoral Doppler observation.

In this paper, a novel ergodic cellular automaton model of Hes1 mRNA and Hes1 protein network is presented. Detailed analyses reveal that the presented network model can reproduce a typical nonlinear bifurcation phenomenon observed in a conventional delay differential equation model of the Hes1 mRNA and Hes1 protein network. Furthermore, the presented network model is implemented by a field programmable gate array and its operation is validated by experiments. It is shown that the presented network model consumes much fewer circuit elements and much lower power compared to the delay differential equation network model. Hence the results of this paper will provide fundamental knowledge to design an efficient hardware-based gene network simulator.

We present a highly accurate and efficient, yet simple, two-stage voting scheme for distinguishing inlier 3D correspondences by densely assessing and ranking their local and global geometric consistencies. The strength of the proposed method stems from both the novel idea of post-validated voting set, as well as single-point superimposition transforms, which are computationally cheap and avoid rotational ambiguities. Using a well-known dataset consisting of various 3D models and numerous scenes that include different occlusion rates, the proposed scheme is evaluated against state-of-the-art 3D voting schemes, in terms of both the correspondence PR (precision-recall) AUC (area under curve), and the execution time. A total of 374 experiments were conducted for each method, which involved a combination of four models, 50 scenes, and two down-samplings. The proposed scheme outperforms the state-of-the-art 3D voting schemes in terms of both accuracy and speed. Quantitatively, the proposed scheme scores 97.0% ±12.9% on the PR AUC metric, averaged over all of the experiments, while the two state-of-the-art schemes score 74.2% ±22.2% and 78.3% ±26.4%. Furthermore, the proposed scheme requires only 24.1% ±6.0% of the time consumed by the fastest state-of-the-art scheme. The proposed voting scheme also demonstrates high robustness against occlusions and scarce inliers.

Muscle functional MRI (mfMRI) is an imaging technique that assess muscles' activity, exploiting a shift in the T2-relaxation time between resting and active state on muscles. It is accompanied by the use of electromyography (EMG) to have a better understanding of the muscle electrophysiology; however, a technique merging MRI and EMG information has not been defined yet. In this paper, we present an anatomical and quantitative evaluation of the method our group introduced in to quantify its validity in terms of muscle pattern estimation for four subjects during four isometric tasks. Muscle activation pattern are estimated using a resistive network to model the morphology in the MRI. An inverse problem is solved from sEMG data to assess muscle activation. The results have been validated with a comparison with physiological information and with the fitting on the electrodes space. On average, over 90% of the input sEMG information was able to be explained with the estimated muscle patterns. There is a match with anatomical information, even if a strong subjectivity is observed among subjects. With this paper we want to proof the method's validity showing its potential in diagnostic and rehabilitation fields.

In the last years the spread of hand prosthetics has fueled the research on the field of signal processing applied on physiologic data. At the state of the art there are different algorithms that allow a precise estimation of hand movements, the majority of whom work just on the electrode space. Even though there are signal processing methods that access single muscle information, they are still premature for a real application on prosthetics. We present a novel method that exploit the information extracted from a magnetic resonance image (MRI) and a single row of high-density surface electromyography (HD-sEMG) electrodes to estimate the muscles currents in the forearm, providing a first experimental application on two simple wrist movements to assess its performance. The results show that the proposed method is able to identify the correct muscle with a single muscle-contraction task, whereas for a 2 muscle task it shows a high variance in the results. The method models the signal propagation from muscles to electrodes using a simple resistive electrical network and uses the graph theory to calculate the muscle currents. It brings a considerably simpler muscle's current estimation method, significantly decreasing the problem complexity, and therefore becoming a potential effective approach for future prosthetics' control.

In the recent years important steps forward have been made in the field of signal processing on muscle signals for hand prosthetics control. At the state of the art different algorithms and techniques allow a precise estimation of hand movements. However, they mostly work exclusively on the electrode space, not seeking for any information about the currents on the contracted muscles.In this study we propose a novel simplified method to estimate the muscles currents in the forearm, along with a first experimental application on two simple movements to assess its performance. We modeled the signal propagation from muscles to electrodes using a purely resistive electrical networks and afterwards apply the graph theory to assess the muscle currents. The proposed method considerably simplify the estimation of muscle's current, decreasing the problem complexity, and therefore potentially it can be a suitable approach for future prosthetics' control.

Local image features are invariant to in-plane rotations and robust to minor viewpoint changes. However, the current detectors and descriptors for local image features fail to accommodate out-of-plane rotations larger than 25°–30°. Invariance to such viewpoint changes is essential for numerous applications, including wide baseline matching, 6D pose estimation, and object reconstruction. In this study, we present a general embedding that wraps a detector/descriptor pair in order to increase viewpoint invariance by exploiting input depth maps. The proposed embedding locates smooth surfaces within the input RGB-D images and projects them into a viewpoint invariant representation, enabling the detection and description of more viewpoint invariant features. Our embedding can be utilized with different combinations of descriptor/detector pairs, according to the desired application. Using synthetic and real-world objects, we evaluated the viewpoint invariance of various detectors and descriptors, for both standalone and embedded approaches. While standalone local image features fail to accommodate average viewpoint changes beyond 33.3°, our proposed embedding boosted the viewpoint invariance to different levels, depending on the scene geometry. Objects with distinct surface discontinuities were on average invariant up to 52.8°, and the overall average for all evaluated datasets was 45.4°. Similarly, out of a total of 140 combinations involving 20 local image features and various objects with distinct surface discontinuities, only a single standalone local image feature exceeded the goal of 60° viewpoint difference in just two combinations, as compared with 19 different local image features succeeding in 73 combinations when wrapped in the proposed embedding. Furthermore, the proposed approach operates robustly in the presence of input depth noise, even that of low-cost commodity depth sensors, and well beyond.

Background: Dysregulation of autonomic nervous system function and impaired homogeneity of myocardial repolarization are 2 important mechanisms for the genesis of ventricular arrhythmias in nonalcoholic subjects. Our previous study suggested that acute ethanol withdrawal promoted the shift of cardiac sympathovagal balance toward sympathetic predominance and reduced the vagal tone, which were related to a higher incidence of ventricular arrhythmia and related death. However, the homogeneity of myocardial repolarization and its relation with the cardiac sympathovagal balance are unknown, especially in alcoholic subjects. The aim of the present study was to clarify these points., Methods: Male Wistar rats were treated with a continuous ethanol liquid diet for 49 days, and then subjected to 1-day withdrawal and 1-day withdrawal with 7-day carvedilol (can block the sympathetic nervous system completely via beta1, beta2, and alpha adrenergic receptors) pretreatment. The cardiac sympathovagal balance and homogeneity of myocardial repolarization were evaluated based on the heart rate variability (HRV) and QT interval dispersion (QTd: dynamic changes in QT interval duration)., Results: The increase in QTd was observed only in rats at 1-day withdrawal, but not in nonalcoholic, continuous ethanol intake, and 1-day withdrawal with 7-day carvedilol pretreatment rats. At 1-day withdrawal, the low-frequency power/high-frequency power (LF/HF) ratio in HRV was elevated and correlated with the QTd. The increased QTd and elevated LF/HF ratio were normalized by the 7-day carvedilol pretreatment in rats at 1-day ethanol withdrawal., Conclusions: In rats with an abrupt termination of the chronic continuous ethanol intake, the homogeneity of myocardial repolarization impaired and correlated with the cardiac sympathovagal balance. Carvedilol pretreatment is associated with a reduction in both the QTd and LF/HF ratio, raising the possibility that the cardiac sympathovagal balance shift may be responsible for the impaired homogeneity of myocardial repolarization, and that beta-blocker pretreatment may decrease the mortality risk during alcoholic withdrawal.

Chronic alcohol consumption activates hepatic stellate cells (HSCs) and causes fatty degeneration in the liver. However, the origin of HSCs and the mechanism of fatty changes of the liver have not been fully elucidated. Here, we examined the roles of bone marrow-derived cells (BMDCs) in a mouse model with chronic alcohol consumption. We performed bone marrow transplantation from transgenic mice expressing green fluorescence protein (GFP) to female wild-type and ROSA mice (B6.129S7-Gt 26Sor/J, transgenic mice expressing beta-galactosidase, beta-gal) and treated them with ethanol (EtOH) for 8 or 16 wk. GFP-expressing BMDCs increased in the liver with EtOH treatment in a time-dependent manner. In response to excess alcohol consumption, approximately 68% of the BMDCs became activated HSCs in that they expressed alpha-smooth muscle actin. Meanwhile, approximately 67% and approximately 66% of these BMDCs expressed Tnf-alpha and transforming growth factor (Tgf)-beta1, respectively, and the activities were further supported by the excessive mRNA expression of Tnf-alpha and Tgf-beta1 in RT-PCR, respectively. Cell fusion occurs between BMDCs and nonparenchymal cells but scarcely occurs between BMDCs and hepatocytes, demonstrated by double staining of beta-gal/GFP and further supported by the Y-chromosome staining. The EtOH withdrawal normalized most of the abnormalities produced by chronic alcohol consumption. These results indicate that excess alcohol consumption stimulates both the homing of HSCs from the bone marrow and their profibrogenic cytokine production in a mouse model of alcohol-induced fatty liver disease.

There is strong evidence that sympathovagal balance plays an important role in the progression of cardiac dysfunction in non-alcoholics. The purpose of this investigation was to determine whether a pattern of continuous ethanol intake and withdrawal modulates the cardiac sympathovagal balance and left ventricular (LV) systolic function in rats. Male Wistar rats were treated with a continuous ethanol liquid diet for 49 days, and then subjected to 1-day withdrawal and 21-day abstinence. Cardiac sympathovagal balance and LV systolic function were evaluated based on heart rate variability (HRV), Western blotting, and echocardiography. Longitudinal data obtained from the same rats showed that the 49-day continuous ethanol treatment induced LV systolic dysfunction, expressed by decreased fractional shortening and ejection fraction. At the 1-day withdrawal, LV systolic dysfunction was deteriorated, and the low-frequency power/high-frequency power (LF/HF) ratio in HRV was elevated because of the depressed HF and the increased LF. Western blot analysis showed an increased expression of myocardial tyrosine hydroxylase and a decreased expression of myocardial acetylcholine. All anomalies were recovered to baseline values with 21-day abstinence. We concluded that acute withdrawal from a 49-day continuous ethanol regimen is sufficient to promote the shift of cardiac sympathovagal balance toward sympathetic predominance and reduced vagal tone, contributing to the further deterioration of LV systolic function in rats. Those providing medical care for alcoholics should be aware of this enhanced susceptibility to LV systolic dysfunction with abrupt termination of a continuous ethanol regimen.