The use of non-invasive signal acquisition methods is today the standard for testing pattern recognition algorithms in prosthetic control. Such research had shown consecutively high performance on both prerecorded and real time data, yet when tested in real life they deteriorate.
To investigate why, the author who is a congenital amputee, wore a prosthetic system utilizing pattern recognition control on a daily basis for a five-day period. The system generated one new classification every 50 ms and movement execution was made continuously; for classifying open/close; and by winning a majority vote; for classifying side grip, fine grip and pointer. System data was continuously collected and errors were registered through both a manual and an automatic log system.
Calculations on extracted data show that grip classifications had an individual accuracy of 47%- 70% while open/close got 95%/98%, but if classified according to a majority vote, grips increased their accuracy to above 90% while open/close dropped to 80%. The conclusion was that majority vote might help complex classifications, like fine grips, while simpler proportional movements is exacerbated by majority voting. Major error sources were identified as signal similarities, electrode displacements and socket design.
After the daily monitoring ended the systems functionality was tested using the "Assessment of Capacity for Myoelectric Control". The ACMC results showed that the system has similar functionality to commercial threshold control and thus is a possible viable option for both acquired and congenital amputees.
Every year in Sweden there is about 24,000 head injuries due to external trauma and 30,000 strokes. A significant number may develop secondary damage because of the increased water content around the damaged brain tissue. The proposed method is to induce water flow from damaged to healthy tissue based on the theory of electroosmosis. The theory behind the electroosmosis is that a flow is induced when a voltage is applied across a medium. The theory of electroosmosis is applied in industry and called electro-osmotic dewatering (EOD) which is used as a drying technique for the dewatering of bio-materials, clays, tofu sheets and electroosmosis is also applied in clinical treatment of tumors. Several experiments were performed on brain phantoms consisting of agarose gel to examine whether the method can be used to divert water. The first experiment was done prove that a flow can be induced when a voltage is applied over the phantom. The second experiment was to investigate the relationship between the flow rate, voltage and current. The result showed linear correlation between flow rate and voltage, flow rate and current, and between the voltage and current. The literature sources and experimental results were referred to a relationship which is developed to determine the flow induced by electrical field. The work was completed with recommendations in electrode material, design and placement. The recommendations are to use plate electrodes at a current density under 25 mA/m2. Electrode placement is predetermined by Finite Element (FE) simulations of different types of injuries.
Both diagnostic ultrasound (US) and magnetic resonance imaging (MRI) accuracy can be improved by using contrast enhancement. For US gas-filled microbubbles (MBs) or silica nanoparticles (SiNPs), and for MRI superparamagnetic or paramagnetic agents, contribute to this. However, interactions of MBs with the vascular wall and cells are not fully known for all contrast media. We studied the in vitro interactions between three types of non-targeted air-filled MBs with a polyvinyl-alcohol shell and murine macrophages or endothelial cells. The three MB types were plain MBs and two types that were labelled (internally and externally) with superparamagnetic iron oxide nanoparticles (SPIONs) for US/MRI bimodality. Cells were incubated with MBs and imaged by microscopy to evaluate uptake and adhesion. Interactions were quantified and the MB internalization was confirmed by fluorescence quenching of non-internalized MBs. Macrophages internalized each MB type within different time frames: plain MBs 6 h, externally labelled MBs 25 min and internally labelled MBs 2 h. An average of 0.14 externally labelled MBs per cell were internalized after 30 min and 1.34 after 2 h; which was 113% more MBs than the number of internalized internally labelled MBs. The macrophages engulfed these three differently modified new MBs at various rate, whereas endothelial cells did not engulf MBs. Polyvinyl-alcohol MBs are not taken up by endothelial cells. The MB uptake by macrophages is promoted by SPION labelling, in particular external such, which may be important for macrophage targeting.
The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources.