Mandible movement recording and its dedicated signal processing for sleep/wake recognition improve sleep disorder index accuracy by assessing the total sleep time. Such a feature is welcome in home screening methods.

Given the importance of the detection and classification of sleep apneas and hypopneas (SAHs) in the diagnosis and the characterization of the SAH syndrome, there is a need for a reliable non-invasive technique measuring respiratory effort. This paper proposes a new method for the scoring of SAHs based on the recording of the midsagittal jaw motion (mouth opening) and on a dedicated automatic analysis of this signal. Continuous wavelet transform is used to quantize respiratory effort from the jaw motion, to detect salient mandibular movements related to SAHs and to delineate events which are likely to contain the respiratory events. The classification of the delimited events is performed using multi-layer perceptrons which were trained and tested on sleep data from 34 recordings. Compared with SAHs scored manually by an expert, the sensitivity and specificity of the detection were 86.1% and 87.4% respectively. Moreover, the overall classification agreement in the recognition of obstructive, central and mixed respiratory events between the manual and automatic scorings was 73.1%. The midsagittal jaw motion signal is hence a reliable marker of respiratory effort and allows an accurate detection and classification of SAHs.

The seriousness of the Obstructive Sleep Apnea/Hypopnea Syndrome is measured by the apnea-hypopnea index (AHI), the number of sleep apneas and hypopneas over the total sleep time (TST). Cardiorespiratory signals are used to detect respiratory events while the TST is usually assessed by the analysis of electroencephalogram traces in polysomnography (PSG) or wrist actigraphy trace in portable monitoring. This paper presents a sleep/wake automatic detector that relies on a wavelet-based complexity measure of the midsagittal jaw movement signal and multilayer perceptrons. In all, 63 recordings were used to train and test the method, while 38 recordings constituted an independent evaluation set for which the sensitivity, the specificity, and the global agreement of sleep recognition, respectively, reached 85.1%, 76.4%, and 82.9%, compared with the PSG data. The AHI computed automatically and only from the jaw movement analysis was significantly improved (p < 0.0001) when considering this sleep/wake detector. Moreover, a sensitivity of 88.6% and a specificity of 83.6% were found for the diagnosis of the sleep apnea syndrome according to a threshold of 15. Thus, the jaw movement signal is reasonably accurate in separating sleep from wake, and, in addition to its ability to score respiratory events, is a valuable signal for portable monitoring.

We evaluated suitability of AJP (Aerosol Jet Printing) deposited silver layer on variety of organic substrates for the most common interconnect techniques used for electronic packaging. Specifically, we checked if the AJP silver layer can be electrically interconnected by Au and Al wires bonding technique. We also evaluated suitability of AJP silver layer for surface-mount technology (SMT). We performed electrical characterization of the AJP silver layer. We realized a fully functional working prototype of Autonomous Wireless Sensor Node system using AJP silver conductive track as an electrical interconnection. IntroductionAerosol Jet Printing (AJP) is an innovative technology for a selective maskless deposition of wide range of materials (conductive, dielectric, biological, nanoparticles etc.) at micron-scale (minimum features of 10µm line and 10µm space are achieved). Because it is a contactless technology, it suits for application on any flat and non-flat, flexible and rigid substrates, and moreover for complex 3D systems. The technology is particularly unique for deposition of a conductive silver paste on plastic substrates. It is known that the organic substrates are particularly sensitive to thermal treatment, as a maximum temperature and time of thermal exposure. AJP silver layer has very low sintering temperature, as low as 100-150°C. The AJP silver layer fine pattern of 10µm line and 10µm space features is reportedly achieved [1][2][3][4][5].That result is much better than a pattern realized by stateof-art a conventional screen printing technology there 100-150µm is an absolute minimum value of line/space features, and it is still better than a 30µm smallest features achieved by inkjet printing [6]. Remarkably, the conventional screen printing and inkjet printing technology are not suitable for 3D application.Despite the advantages listed above the AJP technology remains still a novel technology there number issues must be studied and the technology is not yet widely accepted by industry.

We describe a circuit-element model for the electric detection of biomolecules in translocation through a nanopore in a SOS semiconductor membrane. The biomolecules are simulated as a superposition of individual charges moving through the nanopore and inducing a charge variation on the membrane electrodes that is modeled as a current source. The SOS membrane is discretized into interconnected elementary circuit elements. The model is tested on the translocation of 11 base single-stranded C3AC7 DNA molecule, for which the electric signal shows good qualitative agreement with the multi-scale device approach of Gracheva et al., while quantifying the low-pass filtering in the membrane. Overall, the model confirms the possibility of identifying electrically the sequence of the DNA bases.