The influence of crank configuration on muscle activity and torque production during arm crank ergometry

This study investigated the effect of crank configuration on muscle activity and torque production during submaximal arm crank ergometry. Thirteen non-specifically trained male participants volunteered. During the research trials they completed a warm-up at 15 W before two 3-min exercise stages were completed at 50 and 100 W; subjects used either a synchronous or asynchronous pattern of cranking. During the final 30-s of each submaximal exercise stage electromyographic and torque production data were collected. After the data had been processed each parameter was analysed using separate 2-way ANOVA tests with repeated measures. The activity of all muscles increased in line with external workload, although a shift in the temporal pattern of muscle activity was noted between crank configurations. Patterns of torque production during asynchronous and synchronous cranking were distinct. Furthermore, peak, minimum and delta (peak-minimum) torque values were different (P < 0.05) between crank configurations at both workloads. For example, at 100 W, peak torque using synchronous [19.6 (4.3) Nm] cranking was higher (P < 0.05) compared to asynchronous [16.8 (1.6) Nm] cranking. In contrast minimum torque was lower (P < 0.05) at 100 W using synchronous [4.8 (1.7) Nm] compared to asynchronous [7.3 (1.2) Nm] cranking. There was a distinct bilateral asymmetry in torque production during asynchronous cranking with the dominant transmitting significantly more force to the crank arm. Taken together, these preliminary data demonstrate the complex nature of muscle activity during arm crank ergometry performed with an asynchronous or synchronous crank set-up. Further work is required to determine how muscle activity (EMG activity) and associated patterns of torque production influence physiological responses and functional capacity during arm crank ergometry.

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.