A Simple Low-Cost Electrocardiogram Synchronizer.

Electrocardiogram (ECG) synchronization is useful to avoid the effects of cardiac motion in medical measurements, and is widely used in standard medical imaging. A number of medical equipment include embedded commercial synchronizers. However, the use of independent synchronization modules is sometimes needed when several non-integrated instruments are used, or in the development of new medical instruments and procedures. We present a simple low-cost ECG synchronizer module based on an Arduino controller board that converts the ECG signal into a transistor-transistor-logic (TTL) one, allowing real-time medical measurements triggered at specific phases of the cardiac cycle. The device and conversion algorithm developed is optimized in vitro using synthetic and human ECG signals, and tested in vivo on three swine specimens. Error rates during the in vivo testing stage remain below the 2% of the cycles in all animals and critical false positives are less than 1%, which is sufficient for most applications. Possible algorithm updates are discussed if its performance needs to be improved.

Ex vivo assessment and in vivo validation of non-invasive stent monitoring techniques based on microwave spectrometry.

Some conditions are well known to be directly associated with stent failure, including in-stent re-occlusion and stent fracture. Currently, identification of these high-risk conditions requires invasive and complex procedures. This study aims to assess microwave spectrometry (MWS) for monitoring stents non-invasively. Preliminary ex vivo data are presented to move to in vivo validation. Fifteen mice were assigned to receive subcutaneous stent implantations (n = 10) or sham operations (n = 5). MWS measurements were carried out at 0, 2, 4, 7, 14, 22, and 29 days of follow-up. Additionally, 5 stented animals were summited to micro-CT analyses at the same time points. At 29 days, 3 animals were included into a stent fracture subgroup and underwent a last MWS and micro-CT analysis. MWS was able to identify stent position and in-stent stenosis over time, also discerning significant differences from baseline measures (P < 0.001). Moreover, MWS identified fractured vs. non-fractured stents in vivo. Taken together, MWS emerges as a non-invasive, non-ionizing alternative for stent monitoring. MWS analysis clearly distinguished between in-stent stenosis and stent fracture phenomena.