Four State Sleep Staging From a Multilayered Algorithm Using Electrocardiographic and Actigraphic Data.

PURPOSE: Sleep studies are important to evaluate sleep and sleep-related disorders. The standard test for evaluating sleep is polysomnography, during which several physiological signals are recorded separately and simultaneously with specialized equipment that requires a technologist. Simpler recordings that can model the results of a polysomnography would provide the benefit of expanding the possibilities of sleep recordings. METHODS: Using the publicly available sleep data set from the multiethnic study of atherosclerosis and 1769 nights of sleep, we extracted a distinct data subset with engineered features of the biomarkers collected by actigraphic, oxygenation, and electrocardiographic sensors. We then applied scalable models with recurrent neural network and Extreme Gradient Boosting (XGBoost) with a layered approach to produce an algorithm that we then validated with a separate data set of 177 nights. RESULTS: The algorithm achieved an overall performance of 0.833 accuracy and 0.736 kappa in classifying into four states: wake, light sleep, deep sleep, and rapid eye movement (REM). Using feature analysis, we demonstrated that heart rate variability is the most salient feature, which is similar to prior reports. CONCLUSIONS: Our results demonstrate the potential benefit of a multilayered algorithm and achieved higher accuracy and kappa than previously described approaches for staging sleep. The results further the possibility of simple, wearable devices for sleep staging. Code is available at https://github.com/NovelaNeuro/nEureka-SleepStaging.

Reduced genioglossus muscle activity caused by fluid overload in anesthetized rats.

INTRODUCTION: Although the precise cause of obstructive sleep apnea (OSA) remains unknown, various anatomical or structural factors are thought to influence upper airway patency. Recent clinical studies show that OSA is frequently observed among patients with fluid-retaining states, such as heart/renal failure and postsurgery. It is important to note that a cause-effect relationship is not yet established, and our understanding of the effects of fluid overload is limited. The goal of this study was to investigate an animal model that can characterize the physiological changes that occur in response to fluid overload. METHOD: Acute nonsurvival experiments were conducted in 16 Sprague-Dawley rats. Rats were initially anesthetized by inhaled isoflurane, while the femoral vein was cannulated and urethane (1.2-1.5 g/Kg body weight) was gradually delivered intravenously to induce anesthesia. Additional doses of urethane were delivered as necessary to maintain a surgical plane of anesthesia. A surgical incision was made on the cervical area to catheterize carotid artery to measure blood pressure. A pair of stainless-steel wires was injected into the tongue to measure genioglossus muscle activity (GGEMG). All physiological measurements were recorded as intravenous infusion of saline was provided to the rat (infusion rate = 22 ml/kg over 30 min). RESULTS: Acute saline overloading resulted in a 33% decrease in GGEMG, when compared to baseline. There was also a gradual drop in the respiratory rate (13% decrease) that reached statistical significance at 10 min after infusion was stopped. The blood pressure exhibited a 14% increase which subsequently returned to baseline within 40 min stopping infusion. There were no significant changes in the heart rate. CONCLUSION: The results of this study indicate that systemic fluid overload can affect significant changes in different physiological systems including reduction in genioglossus muscle activity, increase in blood pressure, and change autonomic nervous system function.

Optimizing the design of bipolar nerve cuff electrodes for improved recording of peripheral nerve activity.

OBJECTIVE: Differential measurement of efferent and afferent peripheral nerve activity offers a promising means of improving the clinical utility of implantable neuroprostheses. The tripolar nerve cuff electrode has historically served as the gold standard for achieving high signal-to-noise ratios (SNRs) of the recordings. However, the symmetrical geometry of this electrode array (i.e. electrically-shorted side contacts) precludes it from measuring electrical signals that can be used to obtain directional information. In this study, we investigated the feasibility of using a bipolar nerve cuff electrode to achieve high-SNR of peripheral nerve activity. APPROACH: A finite element model was implemented to investigate the effects of electrode design parameters-electrode length, electrode edge length (EEL), and a conductive shielding layer (CSL)-on simulated single fiber action potentials (SFAP) and also artifact noise signals (ANS). MAIN RESULTS: Our model revealed that the EEL was particularly effective in increasing the peak-to-peak amplitude of the SFAP (319%) and reducing the common mode ANS (67%) of the bipolar cuff electrode. By adding a CSL to the bipolar cuff electrode, the SNR was found to be 65.2% greater than that of a conventional tripolar cuff electrode. In vivo experiments in anesthetized rats confirmed that a bipolar cuff electrode can achieve a SNR that is 38% greater than that achieved by a conventional tripolar cuff electrode (p < 0.05). SIGNIFICANCE: The current study showed that bipolar nerve cuff electrodes can be designed to achieve SNR levels that are comparable to that of tripolar configuration. Further work is needed to confirm that these bipolar design parameters can be used to record bi-directional neural activity in a physiological setting.

Characterizing the reduction of stimulation artifact noise in a tripolar nerve cuff electrode by application of a conductive shield layer.

Tripolar nerve cuff electrodes have been widely used for measuring peripheral nerve activity. However, despite the high signal-to-noise ratio levels that can be achieved with this recording configuration, the clinical use of cuff electrodes in closed-loop controlled neuroprostheses remains limited. This is largely attributed to artifact noise signals that contaminate the recorded neural activity. In this study, we investigated the use of a conductive shield layer (CSL) as a means of reducing the artifact noise recorded by nerve cuff electrodes. Using both computational simulations and in vivo experiments, we found that the CSL can result in up to an 85% decrease in the recorded artifact signal. Both the electrical conductivity and the surface area of the CSL were identified as important design criteria. Although this study shows that the CSL can significantly reduce artifact noise in tripolar nerve cuff electrodes, long-term implant studies are needed to validate our findings.

Directionally-sensitive peripheral nerve recording: bipolar nerve cuff design.

Although bipolar nerve cuff electrodes (NCEs) are used in clinical neurostimulation therapies (e.g., epilepsy, obstructive sleep apnea), the use of this electrode as part of a closed-up controlled system is very limited. The literature points to high noise content (i.e., poor signal-to-noise ratio, SNR) as the primary reason for not using bipolar NCEs to record neural activity. In fact, over the past several decades, the pseudo-tripolar NCEs, the symmetric configuration of this electrode array (i.e., electrically-shorted side contacts) makes it very difficult to obtain directional information from the recorded neural activity (efferent vs. afferent). In this study, we investigated the feasibility of using a bipolar NCE to achieve low-noise, directionally-sensitive recording of peripheral nerve activity.