IEEE transactions on bio-medical engineering
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A 3-D application-specific microelectrode array has been developed for physiological studies in guinea pig cochlear nucleus (CN). The batch-fabricated silicon probes contain integrated parylene cables and use a boron etch-stop to define 15μm-thick shanks and limit tissue displacement. ⋯ Through these experiments, it has demonstrated the efficacy of bimodal silicon arrays to better understand the central nervous system at the circuit level. The 160 electrode sites also provide a high-density neural interface, which is an essential aspect of auditory prosthesis prototypes.
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IEEE Trans Biomed Eng · Jan 2011
Advancements in noncontact, multiparameter physiological measurements using a webcam.
We present a simple, low-cost method for measuring multiple physiological parameters using a basic webcam. By applying independent component analysis on the color channels in video recordings, we extracted the blood volume pulse from the facial regions. ⋯ High degrees of agreement were achieved between the measurements across all physiological parameters. This technology has significant potential for advancing personal health care and telemedicine.
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IEEE Trans Biomed Eng · Jan 2011
Closed-loop anesthetic drug concentration estimation using clinical-effect feedback.
This letter presents a novel closed-loop approach to anesthetic drug concentration estimation using clinical-effect measurement feedback. Compared with the open-loop prediction used in current target-controlled infusion systems, closed-loop estimation exploits the discrepancy between the measured and predicted clinical effects to make corrections to the drug-concentration estimate, achieving improved robustness against variability in the patient pharmacokinetics and pharmacodynamics. ⋯ Initial proof of principle of the closed-loop estimation is demonstrated using the Monte Carlo simulation of surgical procedures with a wide range of patient models. Closed-loop estimation results in statistically significant reductions in median percentage, median absolute percentage, and maximum absolute percentage drug-concentration errors compared to open-loop prediction.
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IEEE Trans Biomed Eng · Dec 2010
Adaptation in P300 brain-computer interfaces: a two-classifier cotraining approach.
A cotraining-based approach is introduced for constructing high-performance classifiers for P300-based brain-computer interfaces (BCIs), which were trained from very little data. It uses two classifiers: Fisher's linear discriminant analysis and Bayesian linear discriminant analysis progressively teaching each other to build a final classifier, which is robust and able to learn effectively from unlabeled data. ⋯ This performance improvement is shown to be even more significant in cases where the training data as well as the number of trials that are averaged for detection of a character is low, both of which are desired operational characteristics of a practical BCI system. Moreover, the proposed method outperforms the self-training-based approaches where the confident predictions of a classifier is used to retrain itself.
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IEEE Trans Biomed Eng · Oct 2010
An improved detrended moving-average method for monitoring the depth of anesthesia.
The detrended moving-average (DMA) method is a new approach to quantify correlation properties in nonstationary signals with underlying trends. This paper monitored the depth of anesthesia (DoA) using modified DMA (MDMA) method. MDMA provides a power-law relation between the fluctuation function F(MDMA)(s) and the scale s: F(MDMA)(s)αs(α), where α is the slope of F(MDMA)(s) in the logarithm scale. ⋯ The minimum time delay between the BIS and F(min) trends was 12 s and the maximum was 178 s. Furthermore, in the case of poor signal quality, our results agreed with clinical observation, which indicates that our method can accurately estimate a patient's hypnotic state in such circumstances. F(α) and F(min) trends are responsive and their movement seems similar to changes in the clinical state of the patients.