The Clinical Utilisation of Respiratory Elastance Software (CURE Soft): a bedside software for real-time respiratory mechanics monitoring and mechanical ventilation management.

BACKGROUND: Real-time patient respiratory mechanics estimation can be used to guide mechanical ventilation settings, particularly, positive end-expiratory pressure (PEEP). This work presents a software, Clinical Utilisation of Respiratory Elastance (CURE Soft), using a time-varying respiratory elastance model to offer this ability to aid in mechanical ventilation treatment. IMPLEMENTATION: CURE Soft is a desktop application developed in JAVA. It has two modes of operation, 1) Online real-time monitoring decision support and, 2) Offline for user education purposes, auditing, or reviewing patient care. The CURE Soft has been tested in mechanically ventilated patients with respiratory failure. The clinical protocol, software testing and use of the data were approved by the New Zealand Southern Regional Ethics Committee. RESULTS AND DISCUSSION: Using CURE Soft, patient's respiratory mechanics response to treatment and clinical protocol were monitored. Results showed that the patient's respiratory elastance (Stiffness) changed with the use of muscle relaxants, and responded differently to ventilator settings. This information can be used to guide mechanical ventilation therapy and titrate optimal ventilator PEEP. CONCLUSION: CURE Soft enables real-time calculation of model-based respiratory mechanics for mechanically ventilated patients. Results showed that the system is able to provide detailed, previously unavailable information on patient-specific respiratory mechanics and response to therapy in real-time. The additional insight available to clinicians provides the potential for improved decision-making, and thus improved patient care and outcomes.

Evaluation of model-based methods in estimating respiratory mechanics in the presence of variable patient effort.

Monitoring of respiratory mechanics is required for guiding patient-specific mechanical ventilation settings in critical care. Many models of respiratory mechanics perform poorly in the presence of variable patient effort. Typical modelling approaches either attempt to mitigate the effect of the patient effort on the airway pressure waveforms, or attempt to capture the size and shape of the patient effort. This work analyses a range of methods to identify respiratory mechanics in volume controlled ventilation modes when there is patient effort. The models are compared using 4 Datasets, each with a sample of 30 breaths before, and 2-3 minutes after sedation has been administered. The sedation will reduce patient efforts, but the underlying pulmonary mechanical properties are unlikely to change during this short time. Model identified parameters from breathing cycles with patient effort are compared to breathing cycles that do not have patient effort. All models have advantages and disadvantages, so model selection may be specific to the respiratory mechanics application. However, in general, the combined method of iterative interpolative pressure reconstruction, and stacking multiple consecutive breaths together has the best performance over the Dataset. The variability of identified elastance when there is patient effort is the lowest with this method, and there is little systematic offset in identified mechanics when sedation is administered.

Lung injury and respiratory mechanics in rugby union.

BACKGROUND: Rugby is a highly popular team contact sport associated with high injury rates. Specifically, there is a chance of inducing internal lung injuries as a result of the physical nature of the game. Such injuries are only identified with the use of specific invasive protocols or equipment. This study presents a model-based method to assess respiratory mechanics of N=11 rugby players that underwent a low intensity experimental Mechanical Ventilation (MV) Test before and after a rugby game. METHODS: Participants were connected to a ventilator via a facemask and their respiratory mechanics estimated using a time-varying elastance model. RESULTS: All participants had a respiratory elastance <10 cmH2O/L with no significant difference observed between pre and postgame respiratory mechanics (P>0.05). Model-based respiratory mechanics estimation has been used widely in the treatment of the critically ill in intensive care. However, the application of a ventilator to assess the respiratory mechanics of healthy human beings is limited. CONCLUSIONS: This method adapted from ICU mechanical ventilation can be used to provide insight to respiratory mechanics of healthy participants that can be used as a more precise measure of lung inflammation/injury that avoids invasive procedures. This is the first study to conceptualize the assessment of respiratory mechanics in healthy athletes as a means to monitor postexercise stress and therefore manage recovery.

Human biovibrations: assessment of human life signs, motor activity, and cognitive performance using wrist-mounted actigraphy.

The application of miniature motion sensors (accelerometers) to study the macro- (gross) and micro- (barely discernible) activities associated with human motion has been termed actigraphy. In countless human sleep studies, actigraphy has mostly been applied to distinguish between when a person is asleep or awake. Use of sleep/wake information has been applied to the development of mathematical models that aim to predict aspects of cognitive performance. However, wrist-mounted actigraphy potentially has many more applications to cognitive and physical assessment beyond sleep/wake discrimination. For example, studies reveal that micro-miniature accelerometric sensors can discriminate heart rate, breathing, and life cessation (death) via actigraphically measured biovibration signals. This paper briefly reviews the development of wrist-mounted actigraphy; presents the data showing wrist-monitored ballistocardioimpulses, respirations, and life-signs signals; discusses the application of sophisticated signal processing for new clinical, operational, and cognitive-assessment-related applications; and concludes with recommendations for further research for demodulating the complex actigram signal.

High-frequency EEG as measure of cognitive function capacity: a preliminary report.

BACKGROUND: High-frequency EEG (HFE) as a potential predictor of alertness/drowsiness was first proposed by Kaplan and Loparo. Sampling EEG at 950 Hz, they established an HFE bandwidth of interest ranging from 100-475 Hz. We extend their work by applying discrete Fourier transform (DFT) of HFE signals sampled at 1000 Hz and partitioned into spectral bands along specific frequency ranges for the assessment of sleep-wake state transition, sleep, and active cognitive engagement. METHODS: There were 13 volunteers (6 men, 7 women, 30 +/- 3 yr) who participated in a 40-h sleep-deprivation study, during which time they performed multiple cognitive tasks. EEG, in synchrony with other physiological signals, was collected at a sampling rate of 1000 Hz. EEG and task performance results from two volunteers are discussed in this preliminary analysis of the C3-C4 region data. Spectral components obtained from DFT are delineated into five main frequency bands: low, (LFB, 1-15 Hz); intermediate (IFB, 16-50 Hz); and 3 high frequency bands: HFB1 (51-100 Hz); HFB2 (101-200 Hz); and HFB3 (201-500 Hz) for analysis purposes. RESULTS: LFB in the 1-15 Hz range at 0.40 spectrum proportion indicated declining alertness; LFB above 0.50 signals transition to sleep; and LFB at 0.70 indicates Stage 2/3 sleep. HFB3 in the 201-500 Hz range at 0.25 and above was a marker of cognitive function and/or capacity. CONCLUSIONS: HFE may provide a quantitative measure of cognitive function capacity. LFB may provide a measure for awake, asleep, or awake-sleep transition, and HFB3 an estimate of cognitive task engagement. HFE may be applied for electroencephalographic monitoring of cognitive performance.

Visual perception, psychomotor performance, and complex motor performance during an overnight air refueling simulated flight.

INTRODUCTION: Visual perception task, complex motor flight task, and psychomotor vigilance task performances were evaluated in U.S. Air Force pilots navigating a high-fidelity fixed wing jet simulator over 26.5 h of continuous wakefulness. METHODS: Eight military pilots on flight status performed the primary task of flying a simulated 12.5-h overnight mission in an Air Refueling Part Task Trainer (ARPTT): Response omission to presentation of single- and double-light stimuli displayed in random sequence across the cockpit instrument panel was the metric used to assess choice visual perception task (CVPT) performance. Deviation from an established azimuth heading in the ARPTT during the CVPT was the flight metric used to assess complex motor performance. Speed, lapse, false start, and anticipation were the metrics used to assess psychomotor vigilance task (PVT) performance during crew rest periods. RESULTS: Significant visual perceptual, complex motor, and psychomotor vigilance (speed and lapse) impairments occurred at 19 h awake in the eight-subject group. CVPT response omissions significantly correlated with ARPTT azimuth deviations at r = 0.97, and with PVT speed at r = -0.92 and lapses at r = 0.90. ARPTT azimuth deviations significantly correlated with PVT speed at r = -0.92 and lapses at r = 0.91. CONCLUSIONS: Acute sleep deprivation degrades visual perceptual, complex motor, and simple motor performance. Complex motor impairments strongly correlate with visual perceptual impairments. This research provides support for the use of visual perceptual measures as surrogates of complex motor performance in operational situations where the primary cognitive inputs are through the visual system.

Oculomotor responses during partial and total sleep deprivation.

INTRODUCTION: Oculomotor responses related to the pupil light reflex (PLR) and saccadic velocity may be sensitive to the effects of sleepiness and therefore could be used to evaluate an individual's fitness for duty. METHODS: There were 12 normal subjects who completed an 8-d study. They were allowed 8 h in bed on the first three nights, 4 h in bed on the fourth night, and then were sleep deprived for the following 64 h. Approximately every 3 h, subjects performed a battery of tests which included a 45-s automated oculomotor test and a 40-min PC-based driving simulator task. Sleepiness was evaluated with a self-assessment instrument. Subjects were allowed 10 h of recovery sleep following sleep deprivation. RESULTS: Oculomotor results for nine subjects showed a significant increase in latency to pupil constriction and a significant decrease in saccadic velocity with total, but not partial, sleep deprivation. The most robust changes during sleep deprivation occurred for saccadic velocity. A night of recovery sleep reversed the effects of total sleep deprivation on latency to pupil constriction and saccadic velocity. Subjective sleepiness and off-road accidents were found to significantly increase over the sleep deprivation period. A significant positive correlation between increasing latency to pupil constriction and increasing sleepiness and driving accidents, and a significant negative correlation between decreasing saccadic velocity and increasing sleepiness and driving accidents during sleep deprivation were found. CONCLUSION: These findings suggest that oculomotor functions, particularly saccadic velocity, are feasible for assessing neurophysiological changes associated with and predictive of sleep deprivation-induced operational performance degradation.

A polynomial model of patient-specific breathing effort during controlled mechanical ventilation.

Patient breathing efforts occurring during controlled ventilation causes perturbations in pressure data, which cause erroneous parameter estimation in conventional models of respiratory mechanics. A polynomial model of patient effort can be used to capture breath-specific effort and underlying lung condition. An iterative multiple linear regression is used to identify the model in clinical volume controlled data. The polynomial model has lower fitting error and more stable estimates of respiratory elastance and resistance in the presence of patient effort than the conventional single compartment model. However, the polynomial model can converge to poor parameter estimation when patient efforts occur very early in the breath, or for long duration. The model of patient effort can provide clinical benefits by providing accurate respiratory mechanics estimation and monitoring of breath-to-breath patient effort, which can be used by clinicians to guide treatment.

Automated logging of inspiratory and expiratory non-synchronized breathing (ALIEN) for mechanical ventilation.

Asynchronous Events (AEs) during mechanical ventilation (MV) result in increased work of breathing and potential poor patient outcomes. Thus, it is important to automate AE detection. In this study, an AE detection method, Automated Logging of Inspiratory and Expiratory Non-synchronized breathing (ALIEN) was developed and compared between standard manual detection in 11 MV patients. A total of 5701 breaths were analyzed (median [IQR]: 500 [469-573] per patient). The Asynchrony Index (AI) was 51% [28-78]%. The AE detection yielded sensitivity of 90.3% and specificity of 88.3%. Automated AE detection methods can potentially provide clinicians with real-time information on patient-ventilator interaction.

Visual neglect: occurrence and patterns in pilots in a simulated overnight flight.

INTRODUCTION: Visual neglect is the unconscious inability to recognize or acknowledge some visual information in the presence of a structurally intact visual system, and was hypothesized to occur with less than 24 h of continuous wakefulness. Visual perception was evaluated in military pilots during a simulated overnight flight to explore for the possible occurrence of visual neglect. METHODS: There were eight military pilots (male, 31-52 yr of age, mean 37 yr) on flight status who were recruited to perform the primary task of flying a simulated 12.5 h overnight mission after a day of continuous wakefulness and the secondary task of responding to repeated 20 min presentations of single- and double-light stimuli displayed in random sequence at 15 degrees intervals across the cockpit instrument panel. In addition to the visual performance task, simulator shutdowns occurring when the tolerances of the simulator were exceeded were measured and simple reaction time on the psychomotor vigilance task was assessed. Total continuous wakefulness was 26.5 h. RESULTS: Combined performance on the visual perception task showed response omissions increasing at 19 h of continuous wakefulness. Patterns included omissions at all stimulus locations, of primarily peripherally located stimuli, and of one of two simultaneously presented stimuli. Simulator shutdowns began at 21.5 h of continuous wakefulness. Correlation of visual task response omissions with simulator shutdowns was r = 0.95, p < 0.0001. CONCLUSIONS: Significant neglect of visual stimuli occurred in pilots beginning at 19 h of continuous wakefulness in a simulated overnight fixed wing aircraft flight, preceded simulator shutdowns, and correlated at 0.95 with simulator shutdowns.

Modulating the homeostatic process to predict performance during chronic sleep restriction.

BACKGROUND: In most current sleep/performance models, the homeostatic process is generally conceived as a simple reservoir in which performance capacity increases exponentially during sleep and decays either linearly or exponentially during wakefulness. Models that include this notional homeostatic process have been successful for describing sleep-performance data under conditions of irregular sleep schedules, jet lag, and short periods of total sleep loss. However, recently described data from sleep restriction studies indicate that recovery following chronically restricted sleep is considerably slower than would be predicted by these models. These findings suggest that chronic sleep restriction induces relatively long-term, slow-recovering changes in brain physiology that affect alertness and performance. METHODS: This paper describes, both conceptually and mathematically, a generic modification to sleep/performance models that facilitates the ability to predict the rate at which alertness and performance restoration occurs during recovery sleep following chronic sleep restriction. Weighted nonlinear least-squares methods were used to compare the proposed modulated homeostatic model with recent sleep/performance observations during chronic sleep restriction and recovery. RESULTS: When compared with the classical Walter Reed homeostatic model, this proposed model was found to provide a better description of sleep restriction and recovery observations. The proposed model was also found to be consistent with the data from a recent University of Pennsylvania study. CONCLUSIONS: These two models make significantly different predictions of performance during both the recovery phase and the chronic sleep restriction phase.

Fatigue models for applied research in warfighting.

The U.S. Department of Defense (DOD) has long pursued applied research concerning fatigue in sustained and continuous military operations. In 1996, Hursh developed a simple homeostatic fatigue model and programmed the model into an actigraph to give a continuous indication of performance. Based on this initial work, the Army conducted a study of 1 wk of restricted sleep in 66 subjects with multiple measures of performance, termed the Sleep Dose-Response Study (SDR). This study provided numerical estimation of parameters for the Walter Reed Army Institute of Research Sleep Performance Model (SPM) and elucidated the relationships among several sleep-related performance measures. Concurrently, Hursh extended the original actigraph modeling structure and software expressions for use in other practical applications. The model became known as the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) Model, and Hursh has applied it in the construction of a Fatigue Avoidance Scheduling Tool. This software is designed to help optimize the operational management of aviation ground and flight crews, but is not limited to that application. This paper describes the working fatigue model as it is being developed by the DOD laboratories, using the conceptual framework, vernacular, and notation of the SAFTE Model. At specific points where the SPM may differ from SAFTE, this is discussed. Extensions of the SAFTE Model to incorporate dynamic phase adjustment for both transmeridian relocation and shift work are described. The unexpected persistence of performance effects following chronic sleep restriction found in the SDR study necessitated some revisions of the SAFTE Model that are also described. The paper concludes with a discussion of several important modeling issues that remain to be addressed.

The Walter Reed palm-held psychomotor vigilance test.

This field-portable reaction time test and analysis software run on devices using the Palm operating system. It is designed to emulate a test and commercial device widely used in sleep deprivation, shift work, fatigue, and stimulant drug research but provides additional capabilities. Experimental comparisons with the standard commercial device in a 40-hour total sleep deprivation study show it to be comparably sensitive to selected experimental variables. A Pocket PC-compatible version is under developement.

Comparative utility of instruments for monitoring sleepiness-related performance decrements in the operational environment.

As both military and commercial operations increasingly become continuous, 24-h-per-day enterprises, the likelihood of operator errors or inefficiencies caused by sleep loss and/or circadian desynchrony also increases. Avoidance of such incidents requires the timely application of appropriate interventions--which, in turn, depend on the ability to measure and monitor the performance capacity of individuals in the operational environment. Several factors determine the potential suitability of candidate measures, including their relative sensitivity, reliability, content validity, intrusiveness and cumbersomeness/fieldability. In the present study, the relative sensitivity (defined as the ratio of effect size to 95% confidence interval) of several measures to the effects of sleep loss was compared in a sleep restriction experiment, in which groups were allowed 3, 5, 7, or 9 h time in bed (TIB) across seven consecutive nights. Of the measures compared, the Psychomotor Vigilance Test was among the most sensitive to sleep restriction, was among the most reliable with no evidence of learning over repeated administrations, and possesses characteristics that make it among the most practical for use in the operational environment.

Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study.

Daytime performance changes were examined during chronic sleep restriction or augmentation and following subsequent recovery sleep. Sixty-six normal volunteers spent either 3 (n = 18), 5 (n= 16), 7 (n = 16), or 9 h (n = 16) daily time in bed (TIB) for 7 days (restriction/augmentation) followed by 3 days with 8 h daily TIB (recovery). In the 3-h group, speed (mean and fastest 10% of responses) on the psychomotor vigilance task (PVT) declined, and PVT lapses (reaction times greater than 500 ms) increased steadily across the 7 days of sleep restriction. In the 7- and 5-h groups speed initially declined, then appeared to stabilize at a reduced level; lapses were increased only in the 5-h group. In the 9-h group, speed and lapses remained at baseline levels. During recovery, PVT speed in the 7- and 5-h groups (and lapses in the 5-h group) remained at the stable, but reduced levels seen during the last days of the experimental phase, with no evidence of recovery. Speed and lapses in the 3-h group recovered rapidly following the first night of recovery sleep; however, recovery was incomplete with speed and lapses stabilizing at a level comparable with the 7- and 5-h groups. Performance in the 9-h group remained at baseline levels during the recovery phase. These results suggest that the brain adapts to chronic sleep restriction. In mild to moderate sleep restriction this adaptation is sufficient to stabilize performance, although at a reduced level. These adaptive changes are hypothesized to restrict brain operational capacity and to persist for several days after normal sleep duration is restored, delaying recovery.