Improved synchronization performance in DSSS systems

This paper deals with the synchronization properties of a family of spreading codes, called concatenated codes. New synchronization algorithms are introduced, and the performance of these algorithms is discussed both analytically and by simulation. It turns out that with a minimum of extra hardware, the mean phase acquisition time can be considerably reduced, while maintaining the reliability of the synchronization process at low power consumption

Trapezius muscle EMG as predictor of mental stress

Stress is a growing problem in society and can cause musculoskeletal complaints. It would be useful to measure stress for prevention of stress-related health problems. An experiment is described in which EMG signals of the upper trapezius muscle were measured with a wireless system during three different stressful conditions: a calculation task (the Norinder test), a logical puzzle task and a memory task. The latter two tests were newly designed and aimed at creating circumstances that are similar to work stress. Amplitudes of the EMG signals were significantly higher during stress compared to rest (+2.6% of reference contraction level) and relative time with EMG gaps was lower during stress (−14.3% of time). Also, mean and median frequencies were significantly lower during stress than during rest (−8.6 and −8.8 Hz, respectively). EMG amplitude increased not only from rest to stress conditions, but also during stressful conditions and decreased during relaxation periods. EMG features correlated with subjectively indicated stress levels (correlations of 0.32 with RMS and −0.32 with relative gaptime). The results indicate that EMG is a useful parameter to detect stress. Together with other physiological sensors, EMG sensors can be included in a wireless system for ambulatory monitoring of stress levels

Towards continuous mental stress level estimation from physiological signals

It is well known that chronic mental stress can cause health problems. Early stress detection can help prevent these problems. We propose and compare two approaches to estimate stress level from physiology. We have measured physiological signals in three different artificial stressful conditions involving problem solving under time pressure and memorizing exercises. Rest periods were included in the protocol to avoid crossover effects over the stress conditions. The recorded signals were: electrocardiogram (ECG), respiration, skin conductance and electromyogram (EMG) of the upper trapezius muscles. About 40 minutes of data were recorded from 30 healthy subjects. Subjective stress levels were measured using questionnaires. We followed a feature selection process to choose 5 physiological features to be used in the analysis. A 2-minute sliding window was used to extract the features by 1-second steps. The feature values were normalized to eliminate baseline and reactivity differences among subjects. The dataset was divided five times randomly in an 80% training set and a 20% test set. The different stress estimation approaches were evaluated and compared using three metrics. First, the classification accuracy in distinguishing between stress and rest conditions was calculated. Second and third, the root mean square error (RMSE) and the correlation were calculated against the subjective stress levels that the subjects indicated during the protocol. Logistic regression and linear regression were applied to obtain an estimation of the stress level. The logistic regression model provided a probability between 0 and 1of a data point belonging to a stress condition. Three concepts were tested to extend the outcome towards a continuous stress level estimation. In the first method, the probability values were interpreted directly as stress le-vels ranging from 0 to 1. In the second method, the relative amount of time that the measure-ments were classified as stress condition in the past 2 minutes was calculated. In the third me-thod, the average of the probability values of the past 2-minutes was calculated. Linear regression was performed against subjective stress levels measured by questionnaires. For classification we chose the optimal threshold that resulted in the highest classification accuracy to classify the es-timated stress levels into the known rest and stress conditions. Results are shown in Table 1. The values in the table correspond to the average numbers over the five different training and test sets. Examples of continuous stress level estimations using me-thods 1 and 4 are shown in Figure 1. Method 4 (linear regression) resulted in the highest classification rate and the lowest RMSE. Me-thod 1 showed the highest correlation with the subjective stress levels. Overall, we conclude that both linear and logistic regression are possible candidates to provide a continuous estimation of stress level. Logistic regression has the advantage that it does not need a subjective reference like questionnaires. The approach of interpreting the probability of the logistic regression model as an estimate of the stress level has, to our knowledge, not been reported before. Our results suggest that it may provide a good estimate, but this needs to be validated in further investigations

Motion artifact reduction in EEG recordings using multi-channel contact impedance measurements

Dry-contact electrodes have paved the way for easy-to-use electroencephalography (EEG) systems with minimal setup time, which are of particular interest in ambulatory as well as real-life environments. However, the presence of motion artifacts forms a major obstacle for such systems. In previous studies, it has been shown that continuous electrode-tissue impedance monitoring can be used to handle motion artifacts. In this paper, we demonstrate that the in-phase and quadrature components of the contact impedance provide complementary information that can be used to improve the prediction of motion artifacts. Furthermore, we demonstrate that the prediction of motion artifacts at one electrode can be further improved by also incorporating the impedance measurements at other electrodes. With this, we propose a motion artifact reduction algorithm based on a multi-channel linear prediction (MLP) filter. Although the MLP filter is not able to completely remove motion artifacts, a substantial reduction can indeed be achieved. © 2013 IEEE.status: publishe

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined these patterns in colonies on land of two sympatric seal species: the harbour seal and grey seal. Results show that the density of grey seals on land is twice as high as that of harbour seals. Furthermore, the nearest neighbour distance (NND) of harbour seals (median = 1.06 m) is significantly larger than that of grey seals (median = 0.53 m). Avoidance at small distances (i.e. social distancing) was supported by spatial simulation: when the observed seal locations were shuffled slightly, the frequency of the smallest NNDs (0–25 cm) increased, while the most frequently observed NNDs decreased. As harbour seals are more prone to infectious diseases, we hypothesize that the larger NNDs might be a behavioural response to reduce pathogen transmission. The approach presented here can potentially be used as a practical tool to differentiate between harbour and grey seals in remote sensing applications, particularly in low to medium resolution imagery (e.g. satellite imagery), where morphological characteristics alone are insufficient to differentiate between species

Compact Wireless EEG System with Active Electrodes for Daily Healthcare Monitoring

Development of Wireless EEG system is described. Realtime impedance monitoring and active electrodes are introduced in order to reduce noise from impedance changes caused due to body motion, and to prevent noise from power line interference, respectively. EEG ASICs are developed for the system. The complete system has a low noise (60nV/√Hz) and is packaged in a compact enclosure (38mm × 38mm × 16mm). The system is evaluated against different types of artefacts and possible applications with the system are discussed

Comb-shaped Polymer-based Dry Electrodes for EEG/ECG Measurements with High User Comfort

Soft, comfortable polymer-based dry electrodes are fabricated. Impedance and biopotential measurements are carried out to compare the performance of conventional gel electrodes with our dry electrodes. The impedance of our dry electrodes is reduced by adding more conductive additives to the polymer material. To further lower the impedance, two skin pretreatment techniques are evaluated regarding their influence on skin impedance. However, these techniques are found to have only temporary beneficial effects. Finally biopotential measurements (both ECG and EEG) are performed using our soft polymer electrodes. The ECG signal acquired with both gel and our polymer electrodes demonstrates high degree of similarity. Therefore, heart beat detection is straightforward. To enable monitoring of EEG signals with smaller amplitudes, our dry electrodes need to be combined with pre-amplifiers. Initial EEG tests show that the alpha waves are clearly identifiable with the dry electrodes when subjects close their eyes. Based on the results, combining with sophisticated signal acquisition electronics, the dry electrodes provide a high user comfort solution for high quality biopotential measurements, even on very hairy skin

Wireless EEG System with Real Time Impedance Monitoring and Active Electrodes

In this paper, we present a miniaturized (<;6cm3) and low noise (60nV/√Hz) wireless EEG sensor node with active electrodes and simultaneous electrode tissue impedance (ETI) monitoring. The added benefit of the active electrodes and continuous ETI monitoring is quantified in terms of susceptibility against power line interference and cable motion artefacts. The sensor node is benchmarked against a reference system for similarity measures in EEG frequency response in the relevant bandwidth. Applications of this prototype are foreseen in the clinical, lifestyle and entertainment domains