Non-invasive estimation of static and pulsatile intracranial pressure from transcranial acoustic signals.

The aim of the present study was to examine whether a method for estimation of non-invasive ICP (nICP) from transcranial acoustic (TCA) signals mixed with head-generated sounds estimate the static and pulsatile invasive ICP (iICP). For that purpose, simultaneous iICP and mixed TCA signals were obtained from patients undergoing continuous iICP monitoring as part of clinical management. The ear probe placed in the right outer ear channel sent a TCA signal with fixed frequency (621 Hz) that was picked up by the left ear probe along with acoustic signals generated by the intracranial compartment.

Estimation of left ventricular function using a novel acoustic-based device.

Background: We examined the feasibility of estimating left ventricular ejection fraction (LVEF) by a novel acoustic-based device [vibration response imaging (VRI); Deep Breeze].

Methods: One hundred and forty-one subjects (117 patients and 24 healthy volunteers; age 55 ± 15 years, 82% men) were examined by both VRI and echocardiography. LVEF was determined by echocardiography (echo-LVEF) using the biplane Simpson's method.

Detecting REM sleep from the finger: an automatic REM sleep algorithm based on peripheral arterial tone (PAT) and actigraphy.

Scoring of REM sleep based on polysomnographic recordings is a laborious and time-consuming process. The growing number of ambulatory devices designed for cost-effective home-based diagnostic sleep recordings necessitates the development of a reliable automatic REM sleep detection algorithm that is not based on the traditional electroencephalographic, electrooccolographic and electromyographic recordings trio. This paper presents an automatic REM detection algorithm based on the peripheral arterial tone (PAT) signal and actigraphy which are recorded with an ambulatory wrist-worn device (Watch-PAT100).