Characterization of the electrical conductivity of bone and its correlation to osseous structure.

The interaction of osseous tissue with electric fields is an important subject. The electrical stimulation of bone promotes osteogenesis, while bone impedance has been proposed as a measure of osteoporosis, to follow fracture healing, or as a method to improve safety of surgical procedures. However, a deeper understanding of the electrical properties of bone and their relation to the architecture of osseous tissue is required to extend the range of use of electrical measurements to clinical studies. In this paper we apply electrical impedance spectroscopy to study the conductivity of fresh bovine tibia and we correlate the measured conductivities with its structural properties. Impedance was measured using a custom-made cell and a potentiostat. Bone conductivity was determined at 100 kHz, where the phase shift was negligible. A good agreement (R = 0.83) was found between the measured conductivity and the bone volume fraction, determined on microCT images. Based on this relationship, an equivalent circuit model was created for bone samples. The results of this ex-vivo study are comparable to previous in-vivo observations reporting bone resistivity as a function of bone density. This information can be used to construct a map of the tissue resistivity directly derived from clinical images

In-vivo Electrical Impedance Measurement in Mastoid Bone

Nerve monitoring is a safety mechanism to detect the proximity between surgical instruments and important nerves during surgical bone preparation. In temporal bone, this technique is highly specific and sensitive at distances below 0.1 mm, but remains unreliable for distances above this threshold. A deeper understanding of the patient-specific bone electric properties is required to improve this range of detection. A sheep animal model has been used to characterize bone properties in vivo. Impedance measurements have been performed at low frequencies (<1 kHz) between two electrodes placed inside holes drilled into the sheep mastoid bone. An electric circuit composed of a resistor and a Fricke constant phase element was able to accurately describe the experimental measurements. Bone resistivity was shown to be linearly dependent on the inter-electrode distance and the local bone density. Based on this model, the amount of bone material between the electrodes could be predicted with an error of 0.7 mm. Our results indicate that bone could be described as an ideal resistor while the electrochemical processes at the electrode-tissue interface are characterized by a constant phase element. These results should help increasing the safety of surgical drilling procedures by better predicting the distance to critical nerve structures

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here we present a graphics processor unit (GPU) based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to auto-regressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and 4 times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a 7-day high-resolution ECG is computed within less than 3 seconds. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced

Interactions Between Flowering Plants and Arthropods in Organic Agroecosystems

This chapter concerns the use of flowering plants in organic agroecosystems. First, a review of the available literature explores the use of flower strips in controlling pest populations as part of conservation biological control. The positive effects of flower strips on beneficial insects are then explored and potential candidates for flower strips proposed. Finally, practical recommendations for installing flower strips are given. Secondly, a case study is presented: The use of flowering plants in organic mango orchards in Reunion. We study the interactions between selected flowering plants and beneficial and pest arthropods. We initially focus on all arthropods and we characterize the insect fauna present on three selected plants. We then focus on the entomological group Parasitica (Hymenoptera), many of which are parasitoids of other insects, including pests. The plant with the greatest abundance and diversity of Parasitica is Lobularia maritima (Brassicaceae). In 2013, we used malaise traps to ascertain that an orchard containing flower strips harbors 10 times more parasitoids than a bare orchard. These results confirm the value of using flowering plants as a conservation biological control tool to encourage pest parasitoids in organic farming