BackgroundSwallowing is a continuous process with substantive interdependencies among different muscles, and it plays a significant role in our daily life. The aim of this study was to propose a novel technique based on high-density surface electromyography (HD sEMG) for the evaluation of normal swallowing functions.MethodsA total of 96 electrodes were placed on the front neck to acquire myoelectric signals from 12 healthy subjects while they were performing different swallowing tasks. HD sEMG energy maps were constructed based on the root mean square values to visualize muscular activities during swallowing. The effects of different volumes, viscosities, and head postures on the normal swallowing process were systemically investigated by using the energy maps.ResultsThe results showed that the HD sEMG energy maps could provide detailed spatial and temporal properties of the muscle electrical activity, and visualize the muscle contractions that closely related to the swallowing function. The energy maps also showed that the swallowing time and effort was also explicitly affected by the volume and viscosity of the bolus. The concentration of the muscular activities shifted to the opposite side when the subjects turned their head to either side.ConclusionsThe proposed method could provide an alternative method to physiologically evaluate the dynamic characteristics of normal swallowing and had the advantage of providing a full picture of how different muscle activities cooperate in time and location. The findings from this study suggested that the HD sEMG technique might be a useful tool for fast screening and objective assessment of swallowing disorders or dysphagia.
Question Is there, at the macro‐habitat scale, a relationship between the fraction of evergreen forests and the presence probability of epiphyllous liverworts? Can these two parameters be estimated and mapped using an NDVI‐based indicator that is derived from time‐series of SPOT‐VGT imagery? Location Southern China. Methods Applying the ISODATA algorithm, we classified SPOT‐VGT NDVI time‐series imagery and produced an NDVI map at 1‐km2 resolution containing 128 NDVI classes. That map and the National Land Cover Map of China (2000) were used to prepare a scheme for field sampling. For 537 1‐km2 areas, located in 19 blocks of 100 km × 100 km, field data were collected. They represented 51 preselected NDVI classes that were assumed to contain evergreen forests. Data on the fractions of forest and evergreen forest, the fraction of evergreen forest in forest present and presence probability of epiphyllous liverworts were regressed against different NDVI class‐specific indicators by means of weighted least‐squares regression (WLSR). Results The SPOT‐VGT NDVI for March was found to best explain the variation between 1‐km2 areas in the presence probability of epiphyllous liverworts (R2 = 0.64; linear relationship; RMSE = 0.38) as the area fraction (%) of evergreen forest (R2 = 0.90; exponential relationship; RMSE = 6.1%). Epiphyllous liverworts were only found within 1‐km2 areas when the SPOT‐VGT NDVI value for March was more than 0.50 (model estimate: 0.43 ± 0.20) and the fraction of evergreen forest in 1 km2 was above 14% (model estimate: 5 ± 35%). The estimation errors (with 95% confidence interval) of these two relationships were calculated using a bootstrap resampling method with 1000 replications; they were, respectively, 0.49–0.76 and 0.85–0.94 for R2, and 0.11–0.23 and 5.2–11.9% for RMSE. Other positive relationships were found between the presence probability of epiphyllous liverworts and the fraction of evergreen forest (R2 = 0.64, linear relationship; RMSE = 0.38) and between the fraction of evergreen forest and forest within 1‐km2 areas (R2 = 0.80, linear relationship; RMSE = 29%). Conclusion We show that for southern China, the fraction of evergreen forest and the presence probability of epiphyllous liverworts can directly be inferred by making use of SPOT‐VGT NDVI imagery. The findings are fully consistent with earlier reported hotspots for epiphyllous liverworts. At the macro‐habitat scale, the presence probability of epiphyllous liverworts proved quantitatively related to the fraction of evergreen forest. This suggests causal relationships with patch size and/or rainfall patterns. We believe that the derived maps may serve as a foundation for a range of further studies.
Biopotential signals are mainly characterized by low amplitude and thus often distorted by extraneous interferences, such as power line interference in the recording environment and movement artifacts during the acquisition process. With the presence of such large-amplitude interferences, subsequent processing and analysis of the acquired signals becomes quite a challenging task that has been reported by many previous studies. A number of software-based filtering techniques have been proposed, with most of them being able to minimize the interferences but at the expense of distorting the useful components of the target signal. Therefore, this study proposes a hardware-based method that utilizes a shielded drive circuit to eliminate extraneous interferences on biopotential signal recordings, while also preserving all useful components of the target signal. The performance of the proposed method was evaluated by comparing the results with conventional hardware and software filtering methods in three different biopotential signal recording experiments (electrocardiogram (ECG), electro-oculogram (EOG), and electromyography (EMG)) on an ADS1299EEG-FE platform. The results showed that the proposed method could effectively suppress power line interference as well as its harmonic components, and it could also significantly eliminate the influence of unwanted electrode lead jitter interference. Findings from this study suggest that the proposed method may provide potential insight into high quality acquisition of different biopotential signals to greatly ease subsequent processing in various biomedical applications.
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