The feasibility of using EMG signals for spasticity assessment has been investigated by many authors. In a recent study, a linear mixed-effects model was utilized to predict MAS scores from three EMG channels (biceps brachii, flexor digitorum superficialis, and tibialis anterior) for the wrist flexors and extensors. The linear regression model was outperformed using only a one-dimensional data set . In another study, the relation between electrophysiological and kinetic responses and the MAS was investigated. The authors  used a force-sensing resistor to measure the wrist extension force. The mean values of the envelope of the EMG signal were calculated and were used to predict MAS scores. The authors reported that the success of prediction by the authors was limited because of insufficient data. The authors only considered force records from the wrist extension and did not consider any information related to the agonist and antagonist muscles.
Motor impairment is a common feature of many neurological disorders such as Parkinson's disease, stroke, and cerebral palsy . Spasticity is a common symptom that affects people with these disorders. Therefore, the ability to characterize and assess spasticity is of interest to many clinicians. A study performed to measure the SM of healthy individuals (n = 12), patients with low MAS scores (n = 12), and patients with high MAS scores (n = 12) revealed that the metrics extracted from the EMG signal discriminated between the 3 groups. In particular, the authors  utilized the EMG signals to extract kinematic information from the skin surface for spasticity assessment. As expected, the authors found that force profiles of patients with high MAS scores were more noisy than the profiles of patients with low MAS scores or healthy individuals. However, healthy individuals also did not have an uncoordinated contractions of their muscles. Instead, the authors found that patients with low MAS scores had slight contractions of their muscles. Their main findings were that the periodicity of the EMG signal was dominated by the periodic contractions of the muscles that occur in the isometric force-production task. The periodicity of the EMG signal was then used to extract metrics such as the mean frequency, dominant frequency, amplitude, and frequency bandwidth. These metrics were then used to characterize the SM of the patient and healthy individual groups .
Thus, the LSM images have revealed the crack behaviors of the Ti film on the PDMS substrates at the micro- and nanoscales. The LSM images are found to be consistent with the optical microscopy images, as shown in Figure 2g,h. From the results obtained so far, it is found that the crack formation mainly occurs during the deformation of the PDMS substrate, and that the crack behaviors are strain dependent. The crack density is larger in the undeformed areas and becomes smaller as the strain becomes larger.
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