Contribuição do biodiesel ao superávit comercial do Brasil.

Foi calculada a contribuição do Programa do Biodiesel para o superávit brasileiro, descontando da importação evitada de petrodiesel a parcela de óleo de soja que seria exportada sem o programa. Dependendo da metodologia de cálculo, a contribuição variou entre R$4,7 e R$6,5 bilhões de reais, sendo o valor mais provável de R$4,72 bilhões, equivalendo a 2,05% do superávit comercial do período

Design and Characterization of a Textile Electrode System for the Detection of High-Density sEMG

Muscle activity monitoring in dynamic conditions is a crucial need in different scenarios, ranging from sport to rehabilitation science and applied physiology. The acquisition of surface electromyographic (sEMG) signals by means of grids of electrodes (High-Density sEMG, HD-sEMG) allows obtaining relevant information on muscle function and recruitment strategies. During dynamic conditions, this possibility demands both a wearable and miniaturized acquisition system and a system of electrodes easy to wear, assuring a stable electrode-skin interface. While recent advancements have been made on the former issue, detection systems specifically designed for dynamic conditions are at best incipient. The aim of this work is to design, characterize, and test a wearable, HD-sEMG detection system based on textile technology. A 32-electrodes, 15 mm inter-electrode distance textile grid was designed and prototyped. The electrical properties of the material constituting the detection system and of the electrode-skin interface were characterized. The quality of sEMG signals was assessed in both static and dynamic contractions. The performance of the textile detection system was comparable to that of conventional systems in terms of stability of the traces, properties of the electrode-skin interface and quality of the collected sEMG signals during quasi-isometric and highly dynamic tasks

Does the Brazilian soybean production increase pose a threat on the Amazon rainforest?

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Quantifying Forearm Muscle Activity during Wrist and Finger Movements by Means of Multi-Channel Electromyography.

The study of hand and finger movement is an important topic with applications in prosthetics, rehabilitation, and ergonomics. Surface electromyography (sEMG) is the gold standard for the analysis of muscle activation. Previous studies investigated the optimal electrode number and positioning on the forearm to obtain information representative of muscle activation and robust to movements. However, the sEMG spatial distribution on the forearm during hand and finger movements and its changes due to different hand positions has never been quantified. The aim of this work is to quantify 1) the spatial localization of surface EMG activity of distinct forearm muscles during dynamic free movements of wrist and single fingers and 2) the effect of hand position on sEMG activity distribution. The subjects performed cyclic dynamic tasks involving the wrist and the fingers. The wrist tasks and the hand opening/closing task were performed with the hand in prone and neutral positions. A sensorized glove was used for kinematics recording. sEMG signals were acquired from the forearm muscles using a grid of 112 electrodes integrated into a stretchable textile sleeve. The areas of sEMG activity have been identified by a segmentation technique after a data dimensionality reduction step based on Non Negative Matrix Factorization applied to the EMG envelopes. The results show that 1) it is possible to identify distinct areas of sEMG activity on the forearm for different fingers; 2) hand position influences sEMG activity level and spatial distribution. This work gives new quantitative information about sEMG activity distribution on the forearm in healthy subjects and provides a basis for future works on the identification of optimal electrode configuration for sEMG based control of prostheses, exoskeletons, or orthoses. An example of use of this information for the optimization of the detection system for the estimation of joint kinematics from sEMG is reported

Timing and modulation of activity in the lower limb muscles during indoor rowing: What are the key muscles to target in FES-rowing protocols?

The transcutaneous stimulation of lower limb muscles during indoor rowing (FES Rowing) has led to a new sport and recreation and significantly increased health benefits in paraplegia. Stimulation is often delivered to quadriceps and hamstrings; this muscle selection seems based on intuition and not biomechanics and is likely suboptimal. Here, we sample surface EMGs from 20 elite rowers to assess which, when, and how muscles are activated during indoor rowing. From EMG amplitude we specifically quantified the onset of activation and silencing, the duration of activity and how similarly soleus, gastrocnemius medialis, tibialis anterior, rectus femoris, vastus lateralis and medialis, semitendinosus, and biceps femoris muscles were activated between limbs. Current results revealed that the eight muscles tested were recruited during rowing, at different instants and for different durations. Rectus and biceps femoris were respectively active for the longest and briefest periods. Tibialis anterior was the only muscle recruited within the recovery phase. No side differences in the timing of muscle activity were observed. Regression analysis further revealed similar, bilateral modulation of activity. The relevance of these results in determining which muscles to target during FES Rowing is discussed. Here, we suggest a new strategy based on the stimulation of vasti and soleus during drive and of tibialis anterior during recovery

Contraction level, but not force direction or wrist position, affects the spatial distribution of motor unit recruitment in the biceps brachii muscle

Purpose: Different motor units (MUs) in the biceps brachii (BB) muscle have been shown to be preferentially recruited during either elbow flexion or supination. Whether these different units reside within different regions is an open issue. In this study, we tested wheter MUs recruited during submaximal isometric tasks of elbow flexion and supination for two contraction levels and with the wrist fixed at two different angles are spatially localized in different BB portions. Methods: The MUs’ firing instants were extracted by decomposing high-density surface electromyograms (EMG), detected from the BB muscle of 12 subjects with a grid of electrodes (4 rows along the BB longitudinal axis, 16 columns medio-laterally). The firing instants were then used to trigger and average single-differential EMGs. The average rectified value was computed separately for each signal and the maximal value along each column in the grid was retained. The center of mass, defined as the weighted mean of the maximal, average rectified value across columns, was then consdiered to assess the medio-lateral changes in the MU surface representation between conditions. Results: Contraction level, but neither wrist position nor force direction (flexion vs. supination), affected the spatial distribution of BB MUs. In particular, higher forces were associated with the recruitment of BB MUs whose action potentials were represented more medially. Conclusion: Although the action potentials of BB MUs were represented locally across the muscle medio-lateral region, dicrimination between elbow flexion or supination seems unlikely from the surface representation of MUs action potentials

Design and validation of a wireless Body Sensor Network for integrated EEG and HD-sEMG acquisitions

Sensorimotor integration is the process through which the human brain plans the motor program execution according to external sources. Within this context, corticomuscular and corticokinematic coherence analyses are common methods to investigate the mechanism underlying the central control of muscle activation. This requires the synchronous acquisition of several physiological signals, including EEG and sEMG. Nevertheless, physical constraints of the current, mostly wired, technologies limit their application in dynamic and naturalistic contexts. In fact, although many efforts were made in the development of biomedical instrumentation for EEG and HD-sEMG signal acquisition, the need for an integrated wireless system is emerging. We hereby describe the design and validation of a new fully wireless body sensor network for the integrated acquisition of EEG and HD-sEMG signals. This Body Sensor Network is composed of wireless bio-signal acquisition modules, named sensor units, and a set of synchronization modules used as a general-purpose system for time-locked recordings. The system was characterized in terms of accuracy of the synchronization and quality of the collected signals. An in-depth characterization of the entire system and an end-to-end comparison of the wireless EEG sensor unit with a wired benchmark EEG device were performed. The proposed device represents an advancement of the State-of-the-Art technology allowing the integrated acquisition of EEG and HD-sEMG signals for the study of sensorimotor integration

Quantification of cortical proprioceptive processing through a wireless and miniaturized EEG amplifier

Corticokinematic coherence (CKC) is computed between limb kinematics and cortical activity (e.g. MEG, EEG), and it can be used to detect, quantify and localize the cortical processing of proprioceptive afference arising from the body. EEG-based studies on CKC have been limited to lab environments due to bulky, non-portable instrumentations. We recently proposed a wireless and miniaturized EEG acquisition system aimed at enabling EEG studies outside the laboratory. The purpose of this work is to compare the EEG-based CKC values obtained with this device with a conventional wired-EEG acquisition system to validate its use in the quantification of cortical proprioceptive processing. Eleven healthy right-handed participants were recruited (six males, four females, age range: 24-40 yr). A pneumatic-movement actuator was used to evoke right index-finger flexion-extension movement at 3 Hz for 4 min. The task was repeated both with the wireless-EEG and wired-EEG devices using the same 30-channel EEG cap preparation. CKC was computed between the EEG and finger acceleration. CKC peaked at the movement frequency and its harmonics, being statistically significant (p < 0.05) in 8-10 out of 11 participants. No statistically significant differences (p < 0.05) were found in CKC strength between wireless-EEG (range 0.03-0.22) and wired-EEG (0.02-0.33) systems, that showed a good agreement between the recording systems (3 Hz: r = 0.57, p = 0.071, 6 Hz: r = 0.82, p = 0.003). As expected, CKC peaked in sensors above the left primary sensorimotor cortex contralateral to the moved right index finger. As the wired-EEG device, the tested wireless-EEG system has proven feasible to quantify CKC, and thus can be used as a tool to study proprioception in the human neocortex. Thanks to its portability, the wireless-EEG used in this study has the potential to enable the examination of cortical proprioception in more naturalistic conditions outside the laboratory environment. Clinical Relevance - Our study will contribute to provide innovative technological foundations for future unobtrusive EEG recordings in naturalistic conditions to examine human sensorimotor system