Automatic sleep stage classification with cardiorespiratory signals has attracted increasing attention. In contrast to the traditional manual scoring based on polysomnography, these signals can be measured using advanced unobtrusive techniques that are currently available, promising the application for personal and continuous home sleep monitoring. This paper describes a methodology for classifying wake, rapid-eye-movement (REM) sleep, and non-REM (NREM) light and deep sleep on a 30 s epoch basis. A total of 142 features were extracted from electrocardiogram and thoracic respiratory effort measured with respiratory inductance plethysmography. To improve the quality of these features, subject-specific Z-score normalization and spline smoothing were used to reduce between-subject and within-subject variability. A modified sequential forward selection feature selector procedure was applied, yielding 80 features while preventing the introduction of bias in the estimation of cross-validation performance. PSG data from 48 healthy adults were used to validate our methods. Using a linear discriminant classifier and a ten-fold cross-validation, we achieved a Cohen's kappa coefficient of 0.49 and an accuracy of 69% in the classification of wake, REM, light, and deep sleep. These values increased to kappa = 0.56 and accuracy = 80% when the classification problem was reduced to three classes, wake, REM sleep, and NREM sleep.

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The LIMPACT is an exoskeleton developed to be used in identifying the reflex properties of the arm in stroke survivors. Information on joint reflexes helps in designing optimal patient specific therapy programs. The LIMPACT is dynamically transparent by combining a lightweight skeleton with high power to weight ratio actuators. The LIMPACT is supported by a passive weight balancing mechanism to compensate for the weight of the exoskeleton and the human arm. Various self-aligning mechanisms allow the human joint axes to align with the axes of the exoskeleton which ensure safety and short don/doff times. The torque controlled motors have a maximum torque bandwidth of 97 Hz which is required for fast torque perturbations and smooth zero impedance control. The LIMPACT's weight is reduced five times as gravitational forces are lowered using a model-based gravity compensation algorithm. The impedance controller ensures tracking of a cycloidal joint angle reference. A cycloid with an amplitude of 1.3 rad and a maximum velocity of 6.5 rad/s has a maximum tracking error of only 7%. The LIMPACT fulfills the requirements to be used in future diagnostics measurements for stroke patients.