Influence of mental stress on the pulse wave features of photoplethysmograms.

Mental stress is a major burden for our society. Invasive and non-invasive methods have been proposed to monitor and quantify it using various sensors on and off body. In this Letter, the authors investigated the use of the arm photoplethysmogram (PPG) to assess mental stress in laboratory conditions. Results were in correspondence with their previous in-silico study which guided the present study. Three wave shape parameters were identified for stress assessment from the PPG signal: (i) the time from dicrotic notch to end diastole; (ii) the time from pulse onset to systolic peak; and (iii) the ratio of diastolic to systolic area. The proposed in-vivo results showed that the two first parameters responded significantly to increased mental stress and to a breathing relaxation procedure, complementing heart rate, heart rate variability, and pulse transit time as indices of stress

Assessing mental stress from the photoplethysmogram: a numerical study.

OBJECTIVE: Mental stress is detrimental to cardiovascular health, being a risk factor for coronary heart disease and a trigger for cardiac events. However, it is not currently routinely assessed. The aim of this study was to identify features of the photoplethysmogram (PPG) pulse wave which are indicative of mental stress. APPROACH: A numerical model of pulse wave propagation was used to simulate blood pressure signals, from which simulated PPG pulse waves were estimated using a transfer function. Pulse waves were simulated at six levels of stress by changing the model input parameters both simultaneously and individually, in accordance with haemodynamic changes associated with stress. Thirty-two feature measurements were extracted from pulse waves at three measurement sites: the brachial, radial and temporal arteries. Features which changed significantly with stress were identified using the Mann-Kendall monotonic trend test. MAIN RESULTS: Seventeen features exhibited significant trends with stress in measurements from at least one site. Three features showed significant trends at all three sites: the time from pulse onset to peak, the time from the dicrotic notch to pulse end, and the pulse rate. More features showed significant trends at the radial artery (15) than the brachial (8) or temporal (7) arteries. Most features were influenced by multiple input parameters. SIGNIFICANCE: The features identified in this study could be used to monitor stress in healthcare and consumer devices. Measurements at the radial artery may provide superior performance than the brachial or temporal arteries. In vivo studies are required to confirm these observations

Wearable biosensing: signal processing and communication architectures issues, Journal of Telecommunications and Information Technology, 2005, nr 4

Long-term monitoring of human vital signs is becoming one of the most important fields of research of biomedical engineering. In order to achieve weeks to months of monitoring, new strategies for sensing, conditioning, processing and communication have to be developed. Several strategies are emerging and show different possible architectures. This paper essentially focuses on issues in wearable biosignal processing and communication architecture currently running at the Swiss Center for Electronics andMicrotechnology (CSEM) in the framework of several European projects

The perception of entropy in rapidly moving sparse dot arrays: a nonlinear dynamic perspective

In visual fields composed of dots spatially randomly distributed but moving rigidly, the percept of coherent motion is lost once Dmax is exceeded, resulting in an incoherent, random percept. We have investigated this transition both from a psychophysics perspective and in the development of a dynamic model of the visual system based on a spatially coupled array of nonlinear damped mass-springs cells. We present results of experiments using rigidly moving arrays of dots of different levels of sparseness and differing displacement magnitudes. Results show that the perception of randomness can be reliably judged and displays a transition from coherent to non-coherent motion as the motion amplitude is increased. Using standard psychophysical just noticeable difference (JND) judgements, we noted that the threshold JND was a function of displacement magnitude and sparseness and could not be explained by extant spatiotemporal filtering models. Our model qualitatively explains the important features of the data, reproducing the experimental Dmax and entropy perception effects with increased stimuli motion amplitude at different spatial sparseness levels. We have then performed some numerical simulations of the model when the masses in the array are randomly distributed. Results show that sparseness plays different role if close or far from Dmax in terms of motion coherence discrimination

Preprocessing and Time-Frequency Analysis of Newborn EEG Seizures

Neurological disease or dysfunction in newborn infants is often first manifested by seizures. Prolonged seizures can result in impaired neurodevelopment or even death. In adults, the clinical signs of seizures are well defined and easily recognized. In newborns, however, the clinical signs are subtle and may be absent or easily missed without constant close observation. This article describes the use of adaptive signal processing techniques for removing artifacts from newborn electroencephalogram (EEG) signals. Three adaptive algorithms have been designed in the context of EEG signals. This preprocessing is necessary before attempting a fine time-frequency analysis of EEG rhythmical activities, such as electrical seizures, corrupted by high amplitude signals. After an overview of newborn EEG signals, the authors describe the data acquisition set-up. They then introduce the basic physiological concepts related to normal and abnormal newborn EEGs and discuss the three adaptive algorithms for artifact removal. They also present time-frequency representations (TFRs) of seizure signals and discuss the estimation and modeling of the instantaneous frequency related to the main ridge of the TFR