A Multi-feature Fuzzy Index to Assess Stress Level from Bio-signals.

A mono-feature fuzzy index that evaluates the stress level from one feature extracted from ECG or GSR is presented. It is build using several measures of the feature recorded when the subject is at rest. The mono-feature fuzzy index can be merged in a multi-feature stress index without any tuning. It can be used to select relevant features and to detect stress. The performance of the stress index is analyzed on a data set made of 160 time periods of time when 20 subjects had to perform stressful tasks and corresponding control tasks. The stress was induced by 4 different tasks. The performances reached are 72% of correctly classified time periods in stress and no stress situations. Interesting conclusions could also be made on the tasks ability to induce stress.

Efficient mental workload estimation using task-independent EEG features.

OBJECTIVE: Mental workload is frequently estimated by EEG-based mental state monitoring systems. Usually, these systems use spectral markers and event-related potentials (ERPs). To our knowledge, no study has directly compared their performance for mental workload assessment, nor evaluated the stability in time of these markers and of the performance of the associated mental workload estimators.  This study proposes a comparison of two processing chains, one based on the power in five frequency bands, and one based on ERPs, both including a spatial filtering step (respectively CSP and CCA), an FLDA classification and a 10-fold cross-validation. APPROACH: To get closer to a real life implementation, spectral markers were extracted from a short window (i.e. towards reactive systems) that did not include any motor activity and the analyzed ERPs were elicited by a task-independent probe that required a reflex-like answer (i.e. close to the ones required by dead man's vigilance devices). The data were acquired from 20 participants who performed a Sternberg memory task for 90 min (i.e. 2/6 digits to memorize) inside which a simple detection task was inserted. The results were compared both when the testing was performed at the beginning and end of the session. MAIN RESULTS: Both chains performed significantly better than random; however the one based on the spectral markers had a low performance (60%) and was not stable in time. Conversely, the ERP-based chain gave very high results (91%) and was stable in time. SIGNIFICANCE: This study demonstrates that an efficient and stable in time workload estimation can be achieved using task-independent spatially filtered ERPs elicited in a minimally intrusive manner.

A new NMR technique to probe protein-ligand interaction.

Non covalent grafting of proteins on affinity phases is a very common approach for isolation, purification and re-concentration of tagged proteins. Many biophysical studies are conducted on these grafted proteins (surface plasmon resonance, quartz crystal microbalance, etc.) showing that the integrity and function of the protein is usually maintained. However, NMR studies of such samples were not undertaken so far, due to the broadening observed on this kind of heterogeneous samples. We present here the use of the HR-MAS technology to obtain 2D NMR spectra of the MAGI-1 PDZ2/6 protein domain, C13-labeled, tagged with a His-tag and grafted on a Nickel affinity resin. We optimized the C13 Methyl SOFAST HMQC experiment allowing important gains in terms of signal-to-noise. The gain comes from the gathering of proton magnetization from the resin material to the protein under study. Several methyl signals from the unstructured C-terminal tail, which is involved in the binding of the PDZ domain to C-terminal peptides of its partners, were observed and measured. The interaction of the bound PDZ domain with cognate peptides was monitored using <500µg of protein sample. A response proportional to the peptide Kd is obtained, indicating that the method can be used to rapidly and efficiently monitor protein-ligand interactions.

Self-evaluated automatic classifier as a decision-support tool for sleep/wake staging.

An automatic sleep/wake stages classifier that deals with the presence of artifacts and that provides a confidence index with each decision is proposed. The decision system is composed of two stages: the first stage checks the 20s epoch of polysomnographic signals (EEG, EOG and EMG) for the presence of artifacts and selects the artifact-free signals. The second stage classifies the epoch using one classifier selected out of four, using feature inputs extracted from the artifact-free signals only. A confidence index is associated with each decision made, depending on the classifier used and on the class assigned, so that the user's confidence in the automatic decision is increased. The two-stage system was tested on a large database of 46 night recordings. It reached 85.5% of overall accuracy with improved ability to discern NREM I stage from REM sleep. It was shown that only 7% of the database was classified with a low confidence index, and thus should be re-evaluated by a physiologist expert, which makes the system an efficient decision-support tool.

Effects of oxysterols on cell viability, inflammatory cytokines, VEGF, and reactive oxygen species production on human retinal cells: cytoprotective effects and prevention of VEGF secretion by resveratrol.

BACKGROUND AND AIMS: Oxysterols are assumed to play important roles in age-related macular degeneration, a major cause of blindness. So we characterized the cytotoxic, oxidative, inflammatory, and angiogenic activities of oxysterols (7ß-hydroxycholesterol (7ß-OH), 7-ketocholesterol (7KC), 25-hydroxycholesterol (25-OH)) in human retinal ARPE-19 cells, and evaluated the protective effects of resveratrol (Rsv: 1 µM), a polyphenol from red wine. METHODS: ARPE-19 cells were treated with 7ß-OH, 7KC, or 25-OH (5-40 µg/mL; 24-48 h) without or with Rsv. Cell viability was determined using trypan blue and the MTT assay. Cell death was characterized by electron microscopy and in situ detection of activated caspases with fluorochrome-labeled inhibitors of caspases. Reactive oxygen species (ROS) production was measured with hydroethidine. ELISA methods and a cytometric bead assay were used to quantify cytokines involved in inflammation (IL-8, IL-1ß, IL-6, IL-10, IL-12p70, TNF-α, MCP-1) and VEGF. RESULTS: 7ß-OH and 7KC triggered a caspase-independent cell death process associated with the presence of multilamellar cytoplasmic structures evocating phospholipidosis, increased ROS production, and IL-8 secretion. 7ß-OH enhanced VEGF secretion. No cytotoxic effects were identified with 25-OH, which highly stimulated ROS production, MCP-1, and VEGF secretion. With oxysterols, no IL-10, TNF-α, and IL-12p70 secretion were detected. 25-OH induced IL-8 secretion through the MEK/ERK½ signaling pathway, and Rsv showed cytoprotective activities and inhibited VEGF secretion. CONCLUSION: 7ß-OH, 7KC, and 25-OH have cytotoxic, oxidative, inflammatory, and/or angiogenic activities on ARPE-19 cells. As Rsv has some protective effects against oxysterol-induced cell death and VEGF secretion it could be valuable in ARMD treatment.

New sea spiders from the Jurassic La Voulte-sur-Rhône Lagerstätte.

The diverse and exceptionally well-preserved pycnogonids described herein from the Middle Jurassic La Voulte Lagerstätte fill a 400 Myr gap of knowledge in the evolutionary history of this enigmatic group of marine arthropods. They reveal very close morphological and functional (locomotion, feeding) similarities with present-day pycnogonids and, by contrast, marked differences with all Palaeozoic representatives of the group. This suggests a relatively recent, possibly Mesozoic origin for at least three major extant lineages of pycnogonids (Ammotheidae, Colossendeidae, Endeidae). Combined evidence from depositional environment, faunal associates and recent analogues indicate that the La Voulte pycnogonids probably lived in the upper bathyal zone (ca 200 m). Our results point to a remarkable morphological and ecological stability of this arthropod group over at least 160 Myr and suggest that the colonization of the deep sea by pycnogonids occurred before the Jurassic.

On line extraction of temporal episodes from ICU high-frequency data: a visual support for signal interpretation.

This paper presents a method to extract on line temporal episodes from high-frequency physiological parameters monitored in ICU, as a visual support for signal interpretation. Temporal episodes are expressions such as: "systolic blood pressure is steady at 120 mmHg from time t(0) until time t(1); it increases from 120 to 160 mmHg from time t(1) to time t(2) ...". Three words are used to describe the data evolution: {steady, increasing, decreasing}. The method deals with noisy data and missing values. It uses a segmentation algorithm that was developed previously and a classification of the segments into temporal patterns. The results obtained on simulated data are quite satisfactory. They show that the method is able to detect rapid variations as well as slow trends. Episodes extracted from real S(p)o(2) data recorded over a period of 44 h from 10 different adult patients are analysed. The visual representation of the temporal episodes is a powerful tool to help the physicians analyse in a glance the evolution in time of the variables monitored. It can help carer personnel to make quicker decisions in alarm situations.

Automatic characterization of events on SpO2 signal: comparison of two methods.

Two methods based on trend extraction have been designed to provide automatic analysis of physiological data recorded on adult patients hospitalized in intensive care unit. We focused our work on the characterization of events occurring on SpO2 signal, this signal being used to detect vital problems. Our aim was to recognize events related to technical or vital problems to assist medical staff in his decision process. Our results show that both methods are able to detect and distinguish between probe deconnection, transient hypoxia and desaturation events.

Toward a portable blood pressure recorder device equipped with an accelerometer.

The 24-h ambulatory systolic blood pressure (ASBP) recording has become a helpful tool in the diagnosis of hypertension and evaluation of the efficiency of anti-hypertensive drugs. Yet, the very high variability of ASBP makes the analysis of the recording rather difficult. A potential solution to reduce ASBP variability has been studied and is presented in this article. It consists of equipping the portable ASBP recorder device with other sensors, a three axes accelerometer and a heart rate recorder, so as to enable an analysis to be undertaken of the arterial pressure profile in the light of these concomitant data. A database has been collected, and a model linking ASBP variations with body acceleration and heart rate measurements is developed. Its performance is tested in prediction and the results compared with those obtained from one of the solutions currently used by physicians to deal with ASBP variability. The results obtained with 16 young subjects from the database, for whom two 24-h recordings are available, are significantly improved and very encouraging.

[A quantitative analysis of a predictive model of ambulatory blood pressure monitoring integrating physical activity recording]. / Intérêt de la quantification automatique de l'activité sur la reproductibilité des variations circadiennes de la pression artérielle.

OBJECTIVE: To determine how much of the variations of blood pressure during a 24 hour period could be accounted for by a change in activity using an accelerometer to detect the physical activity and establish a predictive model. MATERIALS AND METHODS: 18 healthy subjects (mean age 25 +/- 2 yrs) were studied during daily life (24 hours) twice one week apart. The systolic and diastolic blood pressure, heart rate (HR), and time of measure were recorded by ambulatory monitoring using Spacelabs (4 measures per hour). A portable digital memory device was designed for the 24 hours ambulatory monitoring of HR (ECG) and physical activity. This device consists of an ECG Holter (ELA medical model Cinesis with digital memory) and a three piezoresistive type accelerometer sensors (prototype ELA research) able to record physical activity in the 3 space dimension. RESULTS: The data of the first recording were compared to the predicated values from the application of a logarithmic model of activity to the second recording. The model then predicted 53 +/- 19% of the systolic BP values of the test day. The mean individual difference for a given time period of one hour between the measured and the predicted systolic BP from the model was 1.45 +/- 3.1 mmHg with a range of [-6.9; 3.4 mmHg]. The mean individual systolic BP difference for the same given time period of one hour but without predictive model was 1.29 +/- 10 mmHg with a range of [-28; 43 mmHg]. CONCLUSION: This study show that 3 D accelerometer is an easy tool to program individual model of ambulatory blood pressure variability. The introduction of this qualitative method seems logical in therapeutic trial.

[Value of a predictive model of ambulatory blood pressure integrating physical activity]. / Intérêt d'un modèle prédictif de la pression artérielle en ambulatoire intégrant l'activité physique.

OBJECTIVE: To determine how much of the variations of blood pressure during a 24 hour period could be accounted for by a change in activity and establish a predictive model. MATERIALS AND METHODS: Twenty three healthy subjects (mean age 25 +/- 2 years) were studied. The BP, heart rate (HR), and time of measure (T) were recorded by ambulatory BP monitoring using Spacelabs (4 measures per hour). At each measure the subject noted in a diary the degree of activity on a six level semi-quantitative scale. DATA ANALYSIS: A model was constructed using an analysis of covariance. Different parameters were added in succession to reach a model of the type P: P0 + A + beta + (HR-HR0) + H, were P = predicted systolic pressure, P0 = mean systolic BP over the 24 hours. A variation in systolic BP for activity level, beta = the slope of the regression between systolic BP and HR during activity A, and HR0 the mean HR during this activity. RESULTS: 1) In order to test the model, the values measured in one subject were compared to the predicted values from the model in 22 others. The procedure was then repeated for the other subjects. This common model predicted 41 +/- 21% of fluctuations in BP of the subject analysed with a range of 0 to 66%. 2) In order to refine the individual model two subjects were explored 7 times over 24 h of non consecutive days. The measures of the last recording were compared to the predicted values from the application of the model to the six preceding recordings. The model then predicted 81% and 66% of the BP values of the test day. The mean of the 24 hour individual difference over a one hour period between the measures and its predicted value by the model was 0.13 +/- 4.8 mmHg, and -0.75 +/- 7.7 mmHg. CONCLUSION: This study expresses in a quantitative fashion the importance of the level of activity in the evaluation of the level of ambulatory BP. The introduction of this method of quantification and analysis seems logical in therapeutic trial. The difference in the predictions by the model for some subjects poses the problem of uniform coding of activities and that of the recognition of other events such as stress and dreaming in sleep.

Structured modeling and state estimation in a fermentation process: Lipase production by Candida rugosa.

A simple structured mathematical model coupled with a methodology of state and parameter estimation is developed for lipase production by Candida rugosa in batch fermentation. The model describes the system according to the following qualitative observations and hypothesis: Lipase production is induced by extracellular oleic acid present in the medium. The acid is transported into the cell where it is consumed, transformed, and stored. Lipase is excreted to the medium where it is distributed between the available oil-water interphase and aqueous phase. Cell growth is modulated by the intracellular substrate concentration. Model parameters have been determined and the whole model validated against experiments not used in their determination. The estimation problem consists in the estimation of three state variables (biomass, intra- and extracellular substrate) and two kinetic parameters by using only the on-line measurement provided by exhaust gas analysis. The presented estimation strategy divides the complex problem into three subproblems that can be solved by stable algorithms. The estimation of biomass (X) and the specific growth rate (mu), is achieved by a recursive prediction error algorithm using the on-line measurement of the carbon dioxide evolution rate. mu is then used to perform an estimation of intracellular substrate and the other kinetic parameter related to substrate transport (A) by an adaptive observer. Extracellular substrate is then evaluated by means of the estimated values of intracellular substrate and biomass through the material balance of the reactor. Simulation and experimental tests showed good performance of the developed estimator, which appears suitable to be used for process control and monitoring. (c) 1995 John Wiley & Sons, Inc.