Compressed AFM-IR hyperspectral nanoimaging

Infrared (IR) hyperspectral imaging is a powerful approach in the field of materials and life sciences. However, for the extension to modern sub-diffraction nanoimaging it still remains a highly inefficient technique, as it acquires data via inherent sequential schemes. Here, we introduce the mathematical technique of low-rank matrix reconstruction to the sub-diffraction scheme of atomic force microscopy-based infrared spectroscopy (AFM-IR), for efficient hyperspectral IR nanoimaging. To demonstrate its application potential, we chose the trypanosomatid unicellular parasites Leishmania species as a realistic target of biological importance. The mid-IR spectral fingerprint window covering the spectral range from 1300 to 1900 cm−1 was chosen and a distance between the data points of 220 nm was used for nanoimaging of single parasites. The method of k-means cluster analysis was used for extracting the chemically distinct spatial locations. Subsequently, we randomly selected only 10% of an originally gathered data cube of 134 (x) × 50 (y) × 148 (spectral) AFM-IR measurements and completed the full data set by low-rank matrix reconstruction. This approach shows agreement in the cluster regions between full and reconstructed data cubes. Furthermore, we show that the results of the low-rank reconstruction are superior compared to alternative interpolation techniques in terms of error-metrics, cluster quality, and spectral interpretation for various subsampling ratios. We conclude that by using low-rank matrix reconstruction the data acquisition time can be reduced from more than 14 h to 1–2 h. These findings can significantly boost the practical applicability of hyperspectral nanoimaging in both academic and industrial settings involving nano- and bio-materials

Individual identification via electrocardiogram analysis

Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations

Nonpharmacological therapies and provision of aids in outpatient dementia networks in Germany: utilization rates and associated factors

Markus Wübbeler,1 Jochen René Thyrian,1 Bernhard Michalowsky,2 Johannes Hertel,2 Franziska Laporte Uribe,3 Karin Wolf-Ostermann,4 Susanne Schäfer-Walkmann,6 Wolfgang Hoffmann2,5 1Interventional Health Care Research Group, German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, 2German Center for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Greifswald, Germany; 3Implementation and Dissemination Research Group, German Center for Neurodegenerative Diseases (DZNE), Witten, Germany; 4Department of Human and Health Science, University of Bremen, Bremen, Germany; 5Epidemiology of Health Care and Community Health, Institute for Community Medicine, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany; 6Institute for Applied Social Sciences, Stuttgart, Germany Background: Nonpharmacological therapies and the provision of aids are described to be supportive in the treatment of persons with dementia (PWDs). These aim to maintain individuals' participation in daily activities as long as possible, to slow the progression of their disease, and to support their independent living at home. However, there is a lack of knowledge about the utilization of therapies and aids among community-dwelling PWDs.Objective: The aims of the study were a) to describe the utilization of nonpharmacological therapies and aids among community-dwelling PWDs and b) to analyze the factors associated with utilization.Method: As part of a cross-sectional study of n=560 caregivers of PWDs in dementia networks throughout Germany, we assessed sociodemographics, clinical variables, and the utilization of nonpharmacological therapies (physiotherapy [PT], occupational therapy [OT]), and aids (sensory, mobility, and others), using face-to-face interviews and questionnaires.Results: Approximately every fourth PWD received PT and every seventh PWD received OT. Sensory aids were utilized by 91.1%, personal hygiene aids by 77.2%, mobility aids by 58.6%, and medical aids by 57.7% of the sample. Regression analysis revealed that the utilization of PT and medical aids was associated with comorbidities (odds ratio [OR] 1.17 and OR 1.27, respectively) and that the utilization of OT and sensory aids was associated with age (OR 1.06 and OR 0.95, respectively).Conclusion: The utilization of nonpharmacological therapies and aids among community-dwelling people served by dementia networks is more frequent than that reported for people in other settings. This result indicates that PWDs in integrated care models such as dementia networks receive better health care. Keywords: aid, integrated care, collaborative car

SQUID measurements of human nerve and muscle near-DC injury-currents using a mechanical modulation of the source position

| We apply a recently developed multi-variate statistical data analysis technique - so called blind source separation by independent component analysis - to process MEG recordings of near-DC fields. The extraction of nearDC fields from MEG recordings has great relevance for medical applications since slowly varying DC-phenomena have been found e.g. in cerebral anoxia and spreading depression in animals. Comparing several blind source separation approaches, it turns out that an algorithm based on temporal decorrelation successfully extracted a DC-component which was induced in the auditory cortex by presentation of music. The task is challenging because of the limited amount of available data and the corruption by outliers, which makes it an interesting real-world testbed for studying the robustness of ICA methods. Keywords| Biomagnetism, biomedical data processing, blind source separation, DC-recordings, independent component analysis, magnetoencephalography (MEG). I. Introduction Rec..