Passive BCI in Operational Environments: Insights, Recent Advances and Future Trends
Technologies able to measure even online the user’s mental states (i.e. passive Brain-Computer Interfaces (pBCI)) would result very useful in “high risk” environments to enhance human-machine interaction. This mini-review aims to highlight key aspects and recent findings to be considered and evaluated when pBCI systems would be developed and used in operational environments, and remarks future directions of their applications.
Automated Compression Device for Viscoelasticity Imaging
Non-invasive measurement of tissue viscoelastic properties is gaining more attention for screening and diagnostic purposes. Recently, measuring dynamic response of tissue under a constant force has been studied for estimation of tissue viscoelastic properties in terms of retardation times.
Evaluation of Mobile Phone Performance for Near-Infrared Fluorescence Imaging
Near-infrared (NIR) imaging represents a rapidly emerging area of biomedical optics, with applications in cancer detection and vascular mapping. We have characterized the spectral sensitivity of an NIR-enabled mobile phone camera and demonstrated fluorescence imaging with indocyanine green in the 780-900 nm range in an animal model.
System Integration and In Vivo Testing of a Robot for Ultrasound Guidance and Monitoring During Radiotherapy
Radiation therapy is planned using CT and delivered using a linear accelerator with cone beam CT (CBCT) to guide patient setup. This is challenging for soft tissue due to low CBCT contrast. Thus, we introduce a cooperatively-controlled robot for ultrasound guidance.
M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition architecture for miniaturized EEG-NIRS based hybrid BCI and monitoring
M3BA modules enable acquisition of EEG, fNIRS, head movements and other electrical biosignals, while being highly precise, miniaturized, wireless, configurable and energy efficient. Performance characterization and in-vivo experiments confirmed functionality and quality of the designed architecture.
Simple T Wave Metrics May Better Predict Early Ischemia as Compared to ST Segment
There is pressing clinical need to identify developing heart attack in patients as early as possible. State-of-the-art tools do not identify all patients with cardiac ischemia, worsening risk for adverse events and outcomes. We aimed to explore the portions of ECG cardiac repolarization that best captured electrophysiological changes associated with ischemia.