Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Real-time segmentation and tracking of brain metabolic state in ICU EEG recordings of burst suppression.
We provide a method for estimating brain metabolic state based on a reduced-order model of EEG burst suppression. The model, derived from previously suggested biophysical mechanisms of burst suppression, describes important electrophysiological features and provides a direct link to cerebral metabolic rate. We design and fit the estimation method from EEG recordings of burst suppression from a neurological intensive care unit and test it on real and synthetic data.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Electrical or repetitive transcranial magnetic stimulation of primary motor cortex for intractable neuropathic pain.
To assess the pain-relieving effects of motor cortex electrical stimulation (MCS) and the predictive factors retrospectively. ⋯ The test stimulation within the central sulcus was more effective than that of the precentral gyrus. In the selected patients, chronic stimulation within the central sulcus did not significantly improve long-term results. Repeated rTMS seems to be same effective as MCS.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Tracking progression of patient state of health in critical care using inferred shared dynamics in physiological time series.
Physiologic systems generate complex dynamics in their output signals that reflect the changing state of the underlying control systems. In this work, we used a switching vector autoregressive (switching VAR) framework to systematically learn and identify a collection of vital sign dynamics, which can possibly be recurrent within the same patient and shared across the entire cohort. We show that these dynamical behaviors can be used to characterize and elucidate the progression of patients' states of health over time. Using the mean arterial blood pressure time series of 337 ICU patients during the first 24 hours of their ICU stays, we demonstrated that the learned dynamics from as early as the first 8 hours of patients' ICU stays can achieve similar hospital mortality prediction performance as the well-known SAPS-I acuity scores, suggesting that the discovered latent dynamics structure may yield more timely insights into the progression of a patient's state of health than the traditional snapshot-based acuity scores.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Analysis of adventitious lung sounds originating from pulmonary tuberculosis.
Tuberculosis is a common and potentially deadly infectious disease, usually affecting the respiratory system and causing the sound properties of symptomatic infected lungs to differ from non-infected lungs. Auscultation is often ruled out as a reliable diagnostic technique for TB due to the random distribution of the infection and the varying severity of damage to the lungs. However, advancements in signal processing techniques for respiratory sounds can improve the potential of auscultation far beyond the capabilities of the conventional mechanical stethoscope. ⋯ These features were then employed to train a neural network to automatically classify the auscultation recordings into their respective healthy or TB-origin categories. The neural network yielded a diagnostic accuracy of 73%, but it is believed that automated filtering of the noise in the clinics, more training samples and perhaps other signal processing methods can improve the results of future studies. This work demonstrates the potential of computer-aided auscultation as an aid for the diagnosis and treatment of TB.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Seizure detection methods using a cascade architecture for real-time implantable devices.
Implantable high-accuracy, and low-power seizure detection is a challenge. In this paper, we propose a cascade architecture to combine different seizure detection algorithms to optimize power and accuracy of the overall seizure detection system. ⋯ In the second-stage detector-and only for the seizure candidates detected in the first detector-a high-accuracy algorithm is used to eliminate the false positives. We show that the proposed cascade architecture can reduce power consumption of seizure detection by 80% with high accuracy, offering a suitable option for real-time implantable seizure detectors.