A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

Thyroid function within the normal range and risk of coronary heart disease: an individual participant data analysis of 14 cohorts

IMPORTANCE Some experts suggest that serum thyrotropin levels in the upper part of the current reference range should be considered abnormal, an approach that would reclassify many individuals as having mild hypothyroidism. Health hazards associated with such thyrotropin levels are poorly documented, but conflicting evidence suggests that thyrotropin levels in the upper part of the reference range may be associated with an increased risk of coronary heart disease (CHD). OBJECTIVE To assess the association between differences in thyroid function within the reference range and CHD risk. DESIGN, SETTING, AND PARTICIPANTS Individual participant data analysis of 14 cohorts with baseline examinations between July 1972 and April 2002 and with median follow-up ranging from 3.3 to 20.0 years. Participants included 55,412 individuals with serum thyrotropin levels of 0.45 to 4.49 mIU/L and no previously known thyroid or cardiovascular disease at baseline. EXPOSURES Thyroid function as expressed by serum thyrotropin levels at baseline. MAIN OUTCOMES AND MEASURES Hazard ratios (HRs) of CHD mortality and CHD events according to thyrotropin levels after adjustment for age, sex, and smoking status. RESULTS Among 55,412 individuals, 1813 people (3.3%) died of CHD during 643,183 person-years of follow-up. In 10 cohorts with information on both nonfatal and fatal CHD events, 4666 of 48,875 individuals (9.5%) experienced a first-time CHD event during 533,408 person-years of follow-up. For each 1-mIU/L higher thyrotropin level, the HR was 0.97 (95% CI, 0.90-1.04) for CHD mortality and 1.00 (95% CI, 0.97-1.03) for a first-time CHD event. Similarly, in analyses by categories of thyrotropin, the HRs of CHD mortality (0.94 [95% CI, 0.74-1.20]) and CHD events (0.97 [95% CI, 0.83-1.13]) were similar among participants with the highest (3.50-4.49 mIU/L) compared with the lowest (0.45-1.49 mIU/L) thyrotropin levels. Subgroup analyses by sex and age group yielded similar results. CONCLUSIONS AND RELEVANCE Thyrotropin levels within the reference range are not associated with risk of CHD events or CHD mortality. This finding suggests that differences in thyroid function within the population reference range do not influence the risk of CHD. Increased CHD risk does not appear to be a reason for lowering the upper thyrotropin reference limit.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

Stable isotope analysis and temperature reconstruction data from DSDP Hole 94-609B and ODP Hole 162-984B

The Greenland ice sheet is accepted as a key factor controlling the Quaternary glacial scenario. However, the origin and mechanisms of major Arctic glaciation starting at 3.15 Ma and culminating at 2.74 Ma are still controversial. For this phase of intense cooling Ravelo et al. proposed a complex gradual forcing mechanism. In contrast, our new submillennial-scale paleoceanographic records from the Pliocene North Atlantic suggest a far more precise timing and forcing for the initiation of northern hemisphere glaciation (NHG), since it was linked to a 2-3 °C surface water warming during warm stages from 2.95 to 2.82 Ma. These records support previous models, claiming that the final closure of the Panama Isthmus (3.0- ~2.5 Ma induced an increased poleward salt and heat transport. Associated strengthening of North Atlantic Thermohaline Circulation and in turn, an intensified moisture supply to northern high latitudes resulted in the build-up of NHG, finally culminating in the great, irreversible climate crash at marine isotope stage G6 (2.74 Ma). In summary, there was a two-step threshold mechanism that marked the onset of NHG with glacial-to-interglacial cycles quasi-persistent until today.

Snow and ice surfaces on King George Island (Antarctic Peninsula) with high-resolution TerraSAR-X time series, with links to shapfiles and GeoTIFFs

Changes of glaciers and snow cover in polar regions affect a wide range of physical and ecosystem processes on land and in the adjacent marine environment. In this study, we investigate the potential of 11-day repeat high-resolution satellite image time series from the TerraSAR-X mission to derive glaciological and hydrological parameters on King George Island, Antarctica during the period Oct/25/2010 to Apr/19/2011. The spatial pattern and temporal evolution of snow cover extent on ice-free areas can be monitored using multi-temporal coherence images. SAR coherence is used to map glacier extent of land terminating glaciers with an average accuracy of 25 m. Multi-temporal SAR color composites identify the position of the late summer snow line at about 220 m above sea level. Glacier surface velocities are obtained from intensity feature-tracking. Surface velocities near the calving front of Fourcade Glacier were up to 1.8 ± 0.01 m/d. Using an intercept theorem based on fundamental geometric principles together with differential GPS field measurements, the ice discharge of Fourcade Glacier was estimated to 20700 ± 5500 m**3/d (corresponding to ~19 ± 5 kt/d). The rapidly changing surface conditions on King George Island and the lack of high-resolution digital elevation models for the region remain restrictions for the applicability of SAR data and the precision of derived products.