Comparing three CPR feedback devices and standard BLS in a single rescuer scenario: a randomised simulation study

BACKGROUND Efficiently performed basic life support (BLS) after cardiac arrest is proven to be effective. However, cardiopulmonary resuscitation (CPR) is strenuous and rescuers' performance declines rapidly over time. Audio-visual feedback devices reporting CPR quality may prevent this decline. We aimed to investigate the effect of various CPR feedback devices on CPR quality. METHODS In this open, prospective, randomised, controlled trial we compared three CPR feedback devices (PocketCPR, CPRmeter, iPhone app PocketCPR) with standard BLS without feedback in a simulated scenario. 240 trained medical students performed single rescuer BLS on a manikin for 8min. Effective compression (compressions with correct depth, pressure point and sufficient decompression) as well as compression rate, flow time fraction and ventilation parameters were compared between the four groups. RESULTS Study participants using the PocketCPR performed 17±19% effective compressions compared to 32±28% with CPRmeter, 25±27% with the iPhone app PocketCPR, and 35±30% applying standard BLS (PocketCPR vs. CPRmeter p=0.007, PocketCPR vs. standard BLS p=0.001, others: ns). PocketCPR and CPRmeter prevented a decline in effective compression over time, but overall performance in the PocketCPR group was considerably inferior to standard BLS. Compression depth and rate were within the range recommended in the guidelines in all groups. CONCLUSION While we found differences between the investigated CPR feedback devices, overall BLS quality was suboptimal in all groups. Surprisingly, effective compression was not improved by any CPR feedback device compared to standard BLS. All feedback devices caused substantial delay in starting CPR, which may worsen outcome.

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

Quantifying the vestibulo-ocular reflex with video-oculography: nature and frequency of artifacts

Video-oculography devices are now used to quantify the vestibulo-ocular reflex (VOR) at the bedside using the head impulse test (HIT). Little is known about the impact of disruptive phenomena (e.g. corrective saccades, nystagmus, fixation losses, eye-blink artifacts) on quantitative VOR assessment in acute vertigo. This study systematically characterized the frequency, nature, and impact of artifacts on HIT VOR measures. From a prospective study of 26 patients with acute vestibular syndrome (16 vestibular neuritis, 10 stroke), we classified findings using a structured coding manual. Of 1,358 individual HIT traces, 72% had abnormal disruptive saccades, 44% had at least one artifact, and 42% were uninterpretable. Physicians using quantitative recording devices to measure head impulse VOR responses for clinical diagnosis should be aware of the potential impact of disruptive eye movements and measurement artifacts.