Summary: Microvascular anastomotic failure remains an uncommon but devastating problem. Although the implantable Doppler probe is helpful in flap monitoring, the devices are cumbersome, easily dislodged, and plagued by false-positive results. The authors have developed an implantable wireless Doppler monitor prototype from off-the-shelf components and tested it in a swine model. The wireless probe successfully distinguished between femoral vein flow, occlusion, and reflow, and wirelessly reported the different signals reliably. This is the first description of a wireless implantable blood flow sensor for flap monitoring. Future iterations will incorporate an integrated microchip-based Doppler system that will decrease the size to 1 mm2, small enough to fit onto an anastomotic coupler.

Emerging methods for the spectral analysis of graphs are analyzed in this paper, as graphs are currently used to study interactions in many fields from neuroscience to social networks. There are two main approaches related to the spectral transformation of graphs. The first approach is based on the Laplacian matrix. The graph Fourier transform is defined as an expansion of a graph signal in terms of eigenfunctions of the graph Laplacian. The calculated eigenvalues carry the notion of frequency of graph signals. The second approach is based on the graph weighted adjacency matrix, as it expands the graph signal into a basis of eigenvectors of the adjacency matrix instead of the graph Laplacian. Here, the notion of frequency is then obtained from the eigenvalues of the adjacency matrix or its Jordan decomposition. In this paper, advantages and drawbacks of both approaches are examined. Potential challenges and improvements to graph spectral processing methods are considered as well as the generalization of graph processing techniques in the spectral domain. Its generalization to the time-frequency domain and other potential extensions of classical signal processing concepts to graph datasets are also considered. Lastly, it is given an overview of the compressive sensing on graphs concepts.

Objective: The effects of the chin-tuck maneuver, a technique commonly employed to compensate for dysphagia, on cervical auscultation are not fully understood. Characterizing a technique that is known to affect swallowing function is an important step on the way to developing a new instrumentation-based swallowing screening tool. Methods: In this study, we recorded data from 55 adult participants who each completed five saliva swallows in a chin-tuck position. The resulting data were processed using previously designed filtering and segmentation algorithms. We then calculated nine time-, frequency-, and time-frequency-domain features for each independent signal. Results: We found that multiple frequency- and time-domain features varied significantly between male and female subjects as well as between swallowing sounds and vibrations. However, our analysis showed that participant age did not play a significant role on the values of the extracted features. Finally, we found that various frequency features corresponding to swallowing vibrations did demonstrate statistically significant variation between the neutral and chin-tuck positions but sounds showed no changes between these two positions. Conclusion: The chin-tuck maneuver affects many facets of swallowing vibrations and sounds and its effects can be monitored via cervical auscultation. Significance: These results suggest that a subject's swallowing technique does need to be accounted for when monitoring their performance with cervical auscultation-based instrumentation.

Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put toward developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients' health and safety. This paper provides an overview of these signal-processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify these data into “normal” and “abnormal” categories. Both linear as well as nonlinear techniques are presented in this regard.

Passive RFID is rapidly expanding for asset tracking while simultaneously opening broader fronts in passive communications and sensing as a platform technology. As technology improves and power requirements are lowered, the possibilities for increased flexibility bring about new "RFID" opportunities with active functionality (e.g., a Passive Camera). In addition, new manufacturing technologies can now provide flexibility and cost advantages for early stage developers when compared to ASIC ICs. This paper addresses a potential security application and other applications including passive camera technologies, inter-chip systems communications on an RFID tag, and new core prototyping and manufacturing technologies to accelerate development in the total RFID space.