scholarly journals A noninvasive, continuous brain monitoring method: rheoencephalography (REG)

2020 ◽  
Vol 1 (2) ◽  
pp. 103-119
Author(s):  
Mihály Bodó

This paper deals with the sustainability under anoxic conditions of human beings, both when healthy, and diseased. As our attention is focused these days on the environment, sustainability, and green energy, a similar effort is being made in neuromonitoring to switch from invasive to noninvasive monitoring methods. Keys to these changes are computerization and shrinking size of electronic hardware. Computerization is going on in all areas of biomedical engineering, both in research and in clinical fields of medicine. In neurology, brain imaging is the most characteristic change in recent decades. These modalities of imaging (MRI, CT, PET scan, etc.) are predominantly utilized for localizing brain pathology. Brain imaging offers great spatial resolution, but poor time resolution. Therefore, for continuous monitoring, neurocritical care departments require an additional tool with good time resolution. There are invasive and noninvasive neuromonitoring methods. The standard method to monitor intracranial pressure (ICP) is an invasive method. Computerization allows for calculating the cerebral blood flow autoregulation (CBF AR) index (pressure reactivity index - PRx) from ICP and systemic arterial pressure (SAP) in real time, continuously, but invasively. The new development, discussed in this paper, is to calculate this index noninvasively by using rheoencephalography (REG), called REGx. We present the road to this invention and summarize multifold REG related results, such as using REG for primary stroke prevention screening, comparison incidence of arteriosclerotic risk factors, various studies by using CBF manipulations, and correlations with other neuromonitoring methods, and validation with in vitro and in vivo methods. REG by using different algorithms allow for real time calculation of autoregulated blood flow. This paper presents results of validation of CBF algorithms as an effective, noninvasive method. The author’s intent is to supply sufficient physiological background information. This review covers the author’s research efforts over several decades; it pertains multiple studies and has an updated addition to human sustainability by considering that Covid-19 is increasing stroke and cardiovascular disease (CVD) morbidity and mortality.

2006 ◽  
Vol 175 (4S) ◽  
pp. 521-521
Author(s):  
Motoaki Saito ◽  
Tomoharu Kono ◽  
Yukako Kinoshita ◽  
Itaru Satoh ◽  
Keisuke Satoh

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.


2020 ◽  
Vol 39 (12) ◽  
pp. 4335-4345
Author(s):  
Jochen Franke ◽  
Nicoleta Baxan ◽  
Heinrich Lehr ◽  
Ulrich Heinen ◽  
Sebastian Reinartz ◽  
...  

2021 ◽  
Vol 7 (9) ◽  
pp. eabe5914 ◽  
Author(s):  
Qianqian Wang ◽  
Kai Fung Chan ◽  
Kathrin Schweizer ◽  
Xingzhou Du ◽  
Dongdong Jin ◽  
...  

Swarming micro/nanorobots offer great promise in performing targeted delivery inside diverse hard-to-reach environments. However, swarm navigation in dynamic environments challenges delivery capability and real-time swarm localization. Here, we report a strategy to navigate a nanoparticle microswarm in real time under ultrasound Doppler imaging guidance for active endovascular delivery. A magnetic microswarm was formed and navigated near the boundary of vessels, where the reduced drag of blood flow and strong interactions between nanoparticles enable upstream and downstream navigation in flowing blood (mean velocity up to 40.8 mm/s). The microswarm-induced three-dimensional blood flow enables Doppler imaging from multiple viewing configurations and real-time tracking in different environments (i.e., stagnant, flowing blood, and pulsatile flow). We also demonstrate the ultrasound Doppler–guided swarm formation and navigation in the porcine coronary artery ex vivo. Our strategy presents a promising connection between swarm control and real-time imaging of microrobotic swarms for localized delivery in dynamic environments.


2012 ◽  
Vol 253-255 ◽  
pp. 705-715 ◽  
Author(s):  
Mohamed Elbanhawi ◽  
Milan Simic

This paper presents one application of industrial robots in the automation of renewable energy production. The robot supports remote performance monitoring and maintenance of salinity gradient solar ponds. The details of the design, setup and the use of the robot sampling station and the remote Data Acquisition (DAQ) system are given here. The use of a robot arm, to position equipment and sensors, provides accurate and reliable real time data needed for autonomous monitoring and control of this type of green energy production. Robot upgrade of solar ponds can be easily integrated with existing systems. Data logged by the proposed system can be remotely accessed, plotted and analysed. Thus the simultaneous and remote monitoring of a large scale network of ponds can be easily implemented. This provides a fully automated solution to the monitoring and control of green energy production operations, which can be used to provide heat and electricity to buildings. Remote real time monitoring will facilitate the setup and operations of several solar ponds around cities.


2007 ◽  
Vol 56 (6) ◽  
pp. 2663-2671 ◽  
Author(s):  
Francesca Sapuppo ◽  
Maide Bucolo ◽  
Marcos Intaglietta ◽  
Paul C. Johnson ◽  
Luigi Fortuna ◽  
...  

1986 ◽  
Vol 14 (2) ◽  
pp. 135-136 ◽  
Author(s):  
Markku J. Päivänsalo ◽  
Topi M. J. Siniluoto

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