Bulk silicon etching techniques, used to selectively remove silicon from substrates, have been broadly applied in the fabrication of micromachined sensors, actuators, and structures. Despite the more recent emergence of higher resolution, surfacemicromachining approaches, the majority of currently shipping silicon sensors are made using bulk etching. Particularly in light of newly introduced dry etching methods compatible with complementary metal-oxide-semiconductors, it is unlikely that bulk micromachining will decrease in popularity in the near future. The available etching methods fall into three categories in terms of the state of the etchant: wet, vapor, and plasma. For each category, the available processes are reviewed and compared in terms of etch results, cost, complexity, process compatibility, and a number of other factors. In addition, several example micromachined structures are presented.

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Automatic electrocardiogram (ECG) beat classification is essential to timely diagnosis of dangerous heart conditions. Specifically, accurate detection of premature ventricular contractions (PVCs) is imperative to prepare for the possible onset of life-threatening arrhythmias. Although many groups have developed highly accurate algorithms for detecting PVC beats, results have generally been limited to relatively small data sets. Additionally, many of the highest classification accuracies (> 90%) have been achieved in experiments where training and testing sets overlapped significantly. Expanding the overall data set greatly reduces overall accuracy due to significant variation in ECG morphology among different patients. As a result, we believe that morphological information must be coupled with timing information, which is more constant among patients, in order to achieve high classification accuracy for larger data sets. With this approach, we combined wavelet-transformed ECG waves with timing information as our feature set for classification. We used select waveforms of 18 files of the MIT/BIH arrhythmia database, which provides an annotated collection of normal and arrhythmic beats, for training our neural-network classifier. We then tested the classifier on these 18 training files as well as 22 other files from the database. The accuracy was 95.16% over 93,281 beats from all 40 files, and 96.82% over the 22 files outside the training set in differentiating normal, PVC, and other beats.

We investigate the signaling mechanisms that induce retinal ganglion cell (RGC) axon elongation by asking whether surviving neurons extend axons by default. We show that bcl-2 overexpression is sufficient to keep purified RGCs alive in the absence of any glial or trophic support. The bcl-2-expressing RGCs do not extend axons or dendrites unless signaled to do so by single peptide trophic factors. Axon growth stimulated by peptide trophic factors is remarkably slow but is profoundly potentiated by physiological levels of electrical activity spontaneously generated within embryonic explants or mimicked on a multielectrode silicon chip. These findings demonstrate that these surviving neurons do not constitutively extend axons and provide insight into the signals that may be necessary to promote CNS regeneration.

The ballistocardiogram (BCG) measures the reaction of the body to cardiac ejection forces, and is an effective, non-invasive means of evaluating cardiovascular function. A simple, robust method is presented for acquiring high-quality, repeatable BCG signals from a modified, commercially available scale. The measured BCG waveforms for all subjects qualitatively matched values in the existing literature and physiologic expectations in terms of timing and IJ amplitude. Additionally, the BCG IJ amplitude was shown to be correlated with diastolic filling time for a subject with premature atrial contractions, demonstrating the sensitivity of the apparatus to beat-by-beat hemodynamic changes. The signal-to-noise ratio (SNR) of the BCG was estimated using two methods, and the average SNR over all subjects was greater than 12 for both estimates. The BCG measurement was shown to be repeatable over 50 recordings taken from the same subject over a three week period. This approach could allow patients at home to monitor trends in cardiovascular health.

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