Deconstructing Haptic Feedback Information in Robot-Assisted Needle Insertion in Soft Tissues.

This paper evaluates the role and effectiveness of different types of haptic feedback in presenting relevant feedback information during needle insertion in soft tissues through a remotely operated robot. We carried out three experiments with human subjects to analyze the effect of grounded kinesthetic feedback, cutaneous vibrotactile feedback, and cutaneous pressure feedback for rendering the elastic and the viscous force components of a simplified needle-tissue interaction model in a simulated environment. Results showed that providing the two pieces of feedback information through different channels, i.e., kinesthetic and cutaneous, led to the best performance, yielding an improvement in detecting a different tissue layer with respect to providing both information through the same commercial grounded kinesthetic interface. Moreover, results indicate that cutaneous pressure feedback is more suited for rendering the elastic component of the interaction with respect to vibrotactile cutaneous sensations. Finally, results suggest that rendering this elastic component where the user holds the input interface is not so important, confirming that delocalized cutaneous sensations can be an effective solution.

Impact of Segmented Magnetization on the Flagellar Propulsion of Sperm-Templated Microrobots.

Technical design features for improving the way a passive elastic filament produces propulsive thrust can be understood by analyzing the deformation of sperm-templated microrobots with segmented magnetization. Magnetic nanoparticles are electrostatically self-assembled on bovine sperm cells with nonuniform surface charge, producing different categories of sperm-templated microrobots. Depending on the amount and location of the nanoparticles on each cellular segment, magnetoelastic and viscous forces determine the wave pattern of each category during flagellar motion. Passively propagating waves are induced along the length of these microrobots using external rotating magnetic fields and the resultant wave patterns are measured. The response of the microrobots to the external field reveals distinct flow fields, propulsive thrust, and frequency responses during flagellar propulsion. This work allows predictions for optimizing the design and propulsion of flexible magnetic microrobots with segmented magnetization.

Construction, training and clinical validation of an interpretation system for genotypic HIV-1 drug resistance based on fuzzy rules revised by virological outcomes.

OBJECTIVES: To evaluate whether fuzzy operators can be usefully applied to the interpretation of genotypic HIV-1 drug resistance by experts, and to improve the prediction of salvage therapy outcome by adapting interpretation rules of genotypic resistance on the basis of their association with virological response data. METHODS: We used a clinical dataset of 231 patients failing highly active antiretroviral therapy (HAART) and starting salvage therapy with baseline resistance genotyping and virological outcomes after 3 and 6 months. A set of rules predicting genotypic resistance was initially derived from an expert (ADL). Rules were implemented using a fuzzy logic approach and the virological outcomes dataset used for the training phase. The resulting algorithm was validated using a separate set of 184 selected patients by correlating the resulting predicted activity with observed virological response at 3 months. For comparison, the expert systems from the drug resistance group of the Agence Nationale de Recherches sur le SIDA (ANRS-AC11) and the algorithm from the Stanford's HIV drug resistance database (Stanford HIVdb) were evaluated on the same set. RESULTS: The starting algorithm had a correlation with virological outcomes of R2=0.06 (P=0.0001). After the training phase the correlation with virological outcomes increased to R2=0.19 (P<0.000001). In the validation set of patients, the activity of the salvage regimen predicted by the fuzzy algorithm was the only variable independently predictive of the 3-month viral load change even after adjusting by the activity predicted by the two expert systems and baseline viral load (for each 10% salvage regimen's activity increase, mean HIV RNA change from baseline: -0.27 log10 copies/ml; 95% CI -0.39, -0.15). CONCLUSION: Using fuzzy operators in a virological outcomes training database to implement a rules-based algorithm for genotypic resistance interpretation, significant improvements of outcomes prediction were obtained. The resulting algorithm showed an independent predictive capability of virological outcomes over that of two rules-based interpretation algorithms made by experts. Although the system was trained and validated on a limited number of cases, the approach deserves further evaluation.