A real-time ST-segment monitoring algorithm for implantable devices.

Continuous ST-segment monitoring by implantable devices may lead to clarification of the substrate of arrhythmias, clarification of the origin of nonspecific chest pain, and titration or preventative application of established anti-ischemic therapies. Although ST-segment monitoring algorithms are available for surface electrocardiogram, the computational demand of algorithms for implantable devices must be minimized for considerations of device longevity. The new algorithm first locates a fiducial point (FPT) at the dominant peak of each QRS complex. The ST-segment deviation (measured at 2 rate-adaptive delays after FPT, eg, FPT + 96 ms and FPT + 152 ms at 60 BPM) with respect to the isoelectric level (measured at the minimum slope preceding the QRS) is then measured. The following features are also quantified by simple operations: R-R interval, R-wave slope, R-wave amplitude, ST-segment slope, and noise content during the isoelectric segment. Inconsistencies in these features relative to their adaptive normal ranges are used to reject noisy or ectopic beats and sudden morphology changes. Finally, the ST-segment deviation over time is filtered to reject rates of change that are not likely attributable to human ischemia. Performance of the algorithm was evaluated on the European Society of Cardiology ST-T Database, which contains 180 hours of ambulatory electrocardiogram with 250 expert-annotated ischemic episodes. The sensitivity was 79% [74% 84%] (mean [95% CI]) and positive predictivity was 81% [76% 86%]. This performance is statistically equivalent to that of published electrocardiogram algorithms that were validated on the same dataset. Estimates of computational burden suggest that the algorithm could process two channels of electrogram continuously for more than 5 years with current implanted device technology. In conclusion, we have developed an algorithm for ST-segment monitoring that can be implemented in current implantable devices with sensitivity and positive predictivity that are comparable with the state-of-the-art.

Long-term testing of an intracranial pressure monitoring device.

OBJECT: Long-term monitoring of intracranial pressure (ICP) is limited by the lack of an implantable sensor with low drift. The goal of this study was to demonstrate that a new capacitive transducer system will produce accurate and stable ICP records over extended periods. METHODS: Intracranial pressure sensors were implanted into the frontal white matter of four dogs. In addition, a fluid-filled catheter was placed in the cisterna magna (CM) to measure cerebrospinal fluid (CSF) pressure. The animals were tested using standard physiological maneuvers such as jugular vein compression, head elevation, and CSF withdrawal from and saline injection into the CM to verify that the ICP sensor precisely matched CSF pressure changes. The mean ICP pressure and CM pressure were compared for months to demonstrate that the transducer system produced minimal drift over time. The change in the ICP sensor record closely duplicated that of the CSF waveform in the CM in response to well-known physiological stimuli. More important, mean ICP pressure remained within 3 mm Hg of CM pressure for months, with a mean difference of less than 0.3 mm Hg. Histological examination of the dog brains revealed only minimal tissue reaction to the presence of the sensor. CONCLUSIONS: The authors demonstrate a new implantable solid-state sensor that reliably measures ICP for months, with minimal drift. The clinical application of this sensor and its telemetry is for long-term monitoring of patients with head injury, mass lesions, and hydrocephalus.