Threshold model with anticonformity under random sequential updating.

We study an asymmetric version of the threshold model of binary decision making with anticonformity under an asynchronous update mode that mimics continuous time. We analyze this model on a complete graph using three different approaches: the mean-field approximation, Monte Carlo simulation, and the Markov chain approach. The latter approach yields analytical results for arbitrarily small systems, in contrast to the mean-field approach, which is strictly correct only for an infinite system. We show that, for sufficiently large systems, all three approaches produce the same results, as expected. We consider two cases: (1) homogeneous, in which all agents have the same tolerance threshold, and (2) heterogeneous, in which thresholds are given by a beta distribution parametrized by two positive shape parameters α and ß. The heterogeneous case can be treated as a generalized model that reduces to a homogeneous model in special cases. We show that particularly interesting behaviors, including social hysteresis and critical mass reported in innovation diffusion, arise only for values of α and ß that yield the shape of the distribution observed in reality.

A segmentation approach to long duration surface EMG recordings.

The purpose of this study was to develop an automatic segmentation method in order to identify postural surface EMG segments in long-duration recordings. Surface EMG signals were collected from the cervical erector spinae (CES), erector spinae (ES), external oblique (EO), and tibialis anterior (TA) muscles of 11 subjects using a bipolar electrode configuration. Subjects remained seated in a car seat over the 150-min data-collection period. The modified dynamic cumulative sum (MDCS) algorithm was used to automatically segment the surface EMG signals. Signals were rejected by comparison with an exponential mathematical model of the spectrum of a surface EMG signal. The average power ratio computed between two successive retained segments was used to classify segments as postural or surface EMG. The presence of a negative slope of a regression line fitted to the median frequency values of postural surface EMG segments was taken as an indication of fatigue. Alpha level was set at 0.05. The overall classification error rate was 8%, and could be performed in 25 min for a 150-min signal using a custom-built software program written in C (Borland Software Corporation, CA, USA). This error rate could be enhanced by concentrating on the rejection method, which caused most of the misclassification (6%). Furthermore, the elimination of non-postural surface EMG segments by the use of a segmentation approach enabled muscular fatigue to be identified in signals that contained no evidence of fatigue when analysed using traditional methods.

Evaluation of driver discomfort during long-duration car driving.

The evolution of indices of fatigue, discomfort, and performance of subjects seated for long duration (150 min) in car seats were studied (n=11). Four experimental configurations were used: with and without vibration for two seats (U, uncomfortable; C, comfortable). Surface electromyography (SEMG) data were recorded bilaterally from cervical erector spinae and external oblique muscles. Discomfort increased significantly during the trial, regardless of the experimental condition (p<0.05). Performance was significantly worse for seat U with vibration (p<0.05). The median frequency of SEMG signals did not change between experimental conditions or across time. It would appear that, either the level of discomfort experienced was insufficient to change either performance or SEMG measures, or that the large parameter estimation variance of the SEMG signals might have masked any underlying spectral change. Further refinement of the SEMG signal processing methodology may be necessary to be able to detect fatigue of postural muscles.