Biomedical subjects

James McNames

Publications and source records attributed to James McNames.

15 recordsLinked to original sources

PubMed2006

Reliability and accuracy of heart rate variability metrics versus ECG segment duration.

Despite the exponential growth in heart rate variability (HRV) research, the reproducibility and reliability of HRV metrics continues to be debated. We estimated the reliability of 11 metrics calculated from 5 min records. We also compared the accuracy of the HRV metrics calculated from ECG records spanning 10 s to 10 min as compared with the metrics calculated from 5 min records. The mean heart rate was more reproducible and could be more accurately estimated from very short segments (<1 min) than any of the other HRV metrics. HRV metrics that effectively highpass filter the R-R interval series were more reliable than the other metrics and could be more accurately estimated from very short segments. This indicates that most of the HRV is caused by drift and nonstationary effects. Metrics that are sensitive to low frequency components of HRV have poor repeatability and cannot be estimated accurately from short segments (<10 min).

Adult↗

PubMed2006

Automatic microelectrode recording analysis and visualization of the globus pallidus interna and stereotactic trajectory.

Locating deep brain neuronal structures is required to accurately place deep brain stimulation (DBS) electrodes during stereotactic surgery in patients with Parkinson's disease and other movement disorders. This study investigates the efficacy of automatic microelectrode visualization and analysis methods to help neurosurgeons locate target structures more objectively, consistently, and easily during surgery. Ten patients (4 males and 6 females) who underwent bilateral implantation of DBS electrodes in the globus pallidus interna (Gpi), from 2001 to 2003, at the Oregon Health and Science University and the Portland Veterans Administration Medical Center were included. We compared the efficacy of the microelectrode recording signal energy, power spectral density (PSD), marginal probability density (mPDF), autocorrelation function (ACF), and partial ACF. mPDF and PSD estimates most accurately indicated the borders of the GPi target structure.

Aged↗

PubMed2006

Automatic analysis and visualization of microelectrode recording trajectories to the subthalamic nucleus: preliminary results.

Although microelectrode recordings (MER) are commonly used to confirm stereotactic targets during surgery for movement disorders, there is no consensus on whether the additional risks and cost of MER are worth the benefits. This may be due, in part, to the inconsistency and inefficiency of subjective interpretation of MER data that is currently used in practice. We describe several fully automatic visualization methods for MER that efficiently and clearly indicate segments of the microelectrode trajectories with homogeneous neural activity that correspond to expected deep brain nuclei. Specifically we demonstrate that these visualization methods can help identify the subthalamic nucleus in Parkinson's disease patients. These methods have the potential to significantly improve patient outcome by helping neurosurgeons objectively identify target structures more quickly and accurately.

Aged↗

PubMed2006

Complex analysis of intracranial hypertension using approximate entropy.

OBJECTIVE: To determine whether decomplexification of intracranial pressure dynamics occurs during periods of severe intracranial hypertension (intracranial pressure >25 mm Hg for >5 mins in the absence of external noxious stimuli) in pediatric patients with intracranial hypertension. DESIGN: Retrospective analysis of clinical case series over a 30-month period from April 2000 through January 2003. SETTING: Multidisciplinary 16-bed pediatric intensive care unit. PATIENTS: Eleven episodes of intracranial hypertension from seven patients requiring ventriculostomy catheter for intracranial pressure monitoring and/or cerebral spinal fluid drainage. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We measured changes in the intracranial pressure complexity, estimated by the approximate entropy (ApEn), as patients progressed from a state of normal intracranial pressure (<25 mm Hg) to intracranial hypertension. We found the ApEn mean to be lower during the intracranial hypertension period than during the stable and recovering periods in all the 11 episodes (0.5158 +/- 0.0089, 0.3887 +/- 0.077, and 0.5096 +/- 0.0158, respectively, p < .01). Both the mean reduction in ApEn from the state of normal intracranial pressure (stable region) to intracranial hypertension (-0.1271) and the increase in ApEn from the ICH region to the recovering region (0.1209) were determined to be statistically significant (p < .01). CONCLUSIONS: Our results indicate that decreased complexity of intracranial pressure coincides with periods of intracranial hypertension in brain injury. This suggests that the complex regulatory mechanisms that govern intracranial pressure may be disrupted during acute periods of intracranial hypertension. This phenomenon of decomplexification of physiologic dynamics may have important clinical implications for intracranial pressure management.

Acute Disease↗

PubMed2006

The individual RDH index: a novel vector index for statistical assessment of antihypertensive treatment reduction, duration, and homogeneity.

We propose a new vector index for the statistical assessment of antihypertensive treatment duration and homogeneity from ambulatory blood pressure monitoring. We termed this approach for evaluating and comparing blood pressure coverage offered by antihypertensive drugs over 24 h as the reduction-duration-homogeneity index. The reduction-duration-homogeneity index is a three-component vector index that incorporates information about the reduction, duration, and homogeneity of antihypertensive treatment, as well as their statistical significance. The advantages of the reduction-duration-homogeneity index are demonstrated by several comparative examples.

Adult↗

PubMed2006

Tracking tremor frequency in spike trains using the extended Kalman smoother.

Tremor is one of the most disabling symptoms in patients with many movement disorders including Parkinson's disease (PD) and essential tremor (ET). Neural tremor manifests itself as a quasi-periodic fluctuation of the firing rate. We describe a frequency tracking method based on the extended Kalman smoother (EKS) to estimate the instantaneous tremor frequency (ITF) exhibited in binary spike trains detected from neural recordings. Simulation results demonstrate that the EKS frequency tracker can estimate the ITF accurately, even though the signal of interest is not sinusoidal and the noise is not Gaussian. The EKS frequency tracker can obtain a normalized mean squared error (NMSE) as low as 0.1 and performs much better than the conventional approach based on the Hilbert transform.

Action Potentials↗

PubMed2005

Adaptive modeling and spectral estimation of nonstationary biomedical signals based on Kalman filtering.

We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is robust to model mismatches. We demonstrate its usefulness by a sample application involving PSD estimation of intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI).

Computer Simulation↗

PubMed2005

Interpretation of approximate entropy: analysis of intracranial pressure approximate entropy during acute intracranial hypertension.

We studied changes in intracranial pressure (ICP) complexity, estimated by the approximate entropy (ApEn) of the ICP signal, as subjects progressed from a state of normal ICP (< 20-25 mmHg) to acutely elevated ICP (an ICP "spike" defined as ICP > 25 mmHg for < or = 5 min). We hypothesized that the measures of intracranial pressure (ICP) complexity and irregularity would decrease during acute elevations in ICP. To test this hypothesis we studied ICP spikes in pediatric subjects with severe traumatic brain injury (TBI). We conclude that decreased complexity of ICP coincides with episodes of intracranial hypertension (ICH) in TBI. This suggests that the complex regulatory mechanisms that govern intracranial pressure are disrupted during acute rises in ICP. Furthermore, we carried out a series of experiments where ApEn was used to analyze synthetic signals of different characteristics with the objective of gaining a better understanding of ApEn itself, especially its interpretation in biomedical signal analysis.

Adolescent↗

PubMed2005

An automatic beat detection algorithm for pressure signals.

Beat detection algorithms have many clinical applications including pulse oximetry, cardiac arrhythmia detection, and cardiac output monitoring. Most of these algorithms have been developed by medical device companies and are proprietary. Thus, researchers who wish to investigate pulse contour analysis must rely on manual annotations or develop their own algorithms. We designed an automatic detection algorithm for pressure signals that locates the first peak following each heart beat. This is called the percussion peak in intracranial pressure (ICP) signals and the systolic peak in arterial blood pressure (ABP) and pulse oximetry (SpO2) signals. The algorithm incorporates a filter bank with variable cutoff frequencies, spectral estimates of the heart rate, rank-order nonlinear filters, and decision logic. We prospectively measured the performance of the algorithm compared to expert annotations of ICP, ABP, and SpO2 signals acquired from pediatric intensive care unit patients. The algorithm achieved a sensitivity of 99.36% and positive predictivity of 98.43% on a dataset consisting of 42,539 beats.

Algorithms↗

PubMed2004

Reliability of the Prognos electrodermal device for measurements of electrical skin resistance at acupuncture points.

OBJECTIVES: (1) To characterize and calibrate an electrodermal screening device, Prognos. (2) To replicate a previous test-retest reliability study of this device with measurements of electrical skin resistance (ESR) at 24 Jing-well acupuncture points (APs). (3) To determine measurement precision in three successively more exacting trial protocols on the same set of subjects. SETTINGS: Oregon College of Oriental Medicine and Portland State University, Portland, OR. INSTRUMENTS: The Prognos device was electrically characterized by a team of research engineers at the Biomedical Signal Processing Laboratory of Portland State University. They determined that Prognos measures the average direct-current (DC) resistance between a metallic wrist strap and an electrode probe tip. The probe tip is connected to a linear spring set to trigger with an optically generated signal at a deflection of 2.62 mm, which corresponds to an average applied force of 2.68 +/- 0.04 N (mean +/- standard deviation [SD], n = 6). They also determined that the device quantifies resistance by applying a 1.1 microA current for an average of 223 +/- 3 ms (n = 7). When calibrated against a series of known resistors, Prognos measures accurately in the range of 150 kOmega to 14.3 MOmega with an error of less than 0.4%. SUBJECTS: Thirty-one (31) healthy volunteers, 17 females and 14 males, 23-63 years of age. RESULTS OF RELIABILITY TEST-RETEST: The mean reliability of a single measurement was; 0.758 for a standard measurement protocol of four sequential sweeps of 24 Jing-well (Ting) APs; 0.851 for four sequential sweeps after ink-marking the APs; and 0.961 for four rapid repeat measurements at each inked AP. Mean absolute values of ESR decreased between the standard and marked protocols, but not between the marked and rapid repeat protocols. CONCLUSIONS: Prognos performs accurately, against known resistors over the reported range of ESR. The reliability in the standard protocol (r = 0.758) is comparable to the reliability of 0.721 demonstrated under similar conditions by other investigators. Marking APs, and performing measurements in a rapid sequence, increases reliability of ESR measurements. Increased reliability in the second and third protocols is associated with decreased mean ESR values which may be related to increased accuracy of Prognos probe placement and/or inking the APs.

Acupuncture Points↗

PubMed2004

Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes.

Currently, no reliable method exists to predict the onset of paroxysmal atrial fibrillation (PAF). We propose a predictor that includes an analysis of the R-R time series. The predictor uses three criteria: the number of premature atrial complexes (PAC) not followed by a regular R-R interval, runs of atrial bigeminy and trigeminy, and the length of any short run of paroxysmal atrial tachycardia. An increase in activity detected by any of these three criteria is an indication of an imminent episode of PAF. Using the Physionet database of the Computers in Cardiology 2001 Challenge, the predictor achieved a sensitivity of 89% and a specificity of 91%.

Algorithms↗

PubMed2004

A novel algorithm to estimate the pulse pressure variation index deltaPP.

We designed a new methodology to estimate the pulse pressure variation index (deltaPP) in arterial blood pressure (ABP). The method uses automatic detection algorithms, kernel smoothing, and rank-order filters to continuously estimate deltaPP. The technique can be used to estimate deltaPP from ABP alone, eliminating the need for simultaneously acquiring airway pressure.

Algorithms↗

PubMed2003

Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit.

OBJECTIVE: To describe a real-time, continuous physiologic data acquisition system for the study of disease dynamics in the intensive care unit. DESIGN: Descriptive report. SETTING: A 16-bed pediatric intensive care unit in a tertiary care children's hospital. PATIENTS: A total of 170 critically ill or injured pediatric patients. INTERVENTIONS: None. MAIN OUTCOME MEASURES: None. RESULTS: We describe a computerized data acquisition and analysis system for the study of critical illness and injury from the perspective of complex dynamic systems. Both parametric (1 Hz) and waveform (125-500 Hz) signals are recorded and analyzed. Waveform data include electrocardiogram, respiration, systemic arterial pressure (invasive and noninvasive), central venous pressure, pulmonary arterial pressure, left and right atrial pressures, intracranial pressure, body temperature, and oxygen saturation. Details of the system components are explained and examples are given from the resultant physiologic database of signal processing algorithms and signal analyses using linear and nonlinear metrics. CONCLUSIONS: We have successfully developed a real-time, continuous physiologic data acquisition system that can capture, store, and archive data from pediatric intensive care unit patients for subsequent time series analysis of dynamic changes in physiologic state. The physiologic signal database generated from this system is available for analysis of dynamic changes caused by critical illness and injury.

Algorithms↗

PubMed2002

Update on intensive care ECG and cardiac event monitoring.

This brief review is aimed primarily as a resource for the clinician and summarizes recent advancements in electrocardiographic monitoring in the intensive care unit. Emphasis is placed on recent advances in ICU ECG and cardiac event monitoring with particular attention to arrhythmia detection in patients following myocardial infarction. Specific topics addressed include: clinical indicators of impending arrhythmic events and sudden death, signal averaged ECG, QT dispersion, ST segment fluctuation, T-wave alternans, QT interval beat-to-beat variability, heart rate variability, and advances in automated arrhythmia detection.

Arrhythmias, Cardiac↗

PubMedDate not supplied

Developments in understanding neuronal spike trains and functional specializations in brain regions.

Understanding information processing at the neuronal level would provide valuable insights to computational intelligence research and computational neuroscience. In particular, understanding constraints on neuronal spike trains would provide indication about the type of syntactic rules used by neurons when processing information. A recent discovery, reported here, was made through analyzing microelectrode recordings (MER) made during surgical procedure in humans. Analysis of MERs of extracellular neuronal activity has gained increasing interest due to potential improvements to surgical techniques involving ablation or placement of deep brain stimulators, done in the treatment of advanced Parkinson's disease. Important to these procedures is the identification of different brain structures such as the globus pallidus internus from the spike train being recorded from the intracranial probe tip during surgery. Spike train data gathered during surgical procedure from multiple patients were processed using a novel feature extraction method reported here. Distinct structures within the spike trains were identified and used to build an effective brain region classifier. The extracted features upon analysis provide some insight into the 'syntactic' constraint on spike trains.

Action Potentials↗