Yisheng Zhu

Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise

With the advance of computer and photonics technology, imaging photoplethysmography [(PPG), iPPG] can provide comfortable and comprehensive assessment over a wide range of anatomical locations. However, motion artifact is a major drawback in current iPPG systems, particularly in the context of clinical assessment. To overcome this issue, a new artifact-reduction method consisting of planar motion compensation and blind source separation is introduced in this study. The performance of the iPPG system was evaluated through the measurement of cardiac pulse in the hand from 12 subjects before and after 5 min of cycling exercise. Also, a 12-min continuous recording protocol consisting of repeated exercises was taken from a single volunteer. The physiological parameters (i.e., heart rate, respiration rate), derived from the images captured by the iPPG system, exhibit functional characteristics comparable to conventional contact PPG sensors. Continuous recordings from the iPPG system reveal that heart and respiration rates can be successfully tracked with the artifact reduction method even in high-intensity physical exercise situations. The outcome from this study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, with clear applications in triage and sports training.

Abnormal EEG complexity in patients with schizophrenia and depression

OBJECTIVE Schizophrenics are usually unable to perform well on cognitive tasks due to disturbances in cortical information processing that are observable as abnormalities in electroencephalogram (EEG) signals. However, whether such cortical disturbances can be assessed by quantitative EEG analysis remains unclear. The purpose of this study was to characterize EEG disturbances, using the Lempel-Ziv complexity (LZC), in the subjects with schizophrenia at rest or while performing mental arithmetic tasks. The results were compared to those from the subjects with depression and with healthy controls. METHODS The subjects included 62 schizophrenia patients, 48 depression patients and 26 age-matched healthy controls. EEG was recorded under two conditions: (i) resting with eyes closed, and (ii) a mentally active condition wherein the subjects were asked to subtract 7 from 100 iteratively with their eyes closed. EEG signals were analyzed by LZC and conventional spectral methods. RESULTS In all the groups, LZC of EEG decreased during the mental arithmetic compared with those under the resting conditions. Both the schizophrenia and the depression groups had a higher LZC (p<0.05) than the controls. Also, the schizophrenia group had a lower LZC (p<0.05) than the depression group during the mental arithmetic task as well as during the resting state. Significant differences in LZC, at some symmetrically located loci (FP1/FP2, F7/F8), between the two hemispheres were found in all the patient groups only during the arithmetic task. CONCLUSIONS Compared with conventional spectral analysis, LZC was more sensitive to both the power spectrum and the temporal amplitude distribution. LZC was associated with the ability to attend to the task and adapt the information processing system to the cognitive challenge. Thus, it would be useful in studying the disturbances in the cortical information processing patients with depression or schizophrenia. SIGNIFICANCE LZC of EEG is associated with mental activity. Thus, LZC analysis can be an important tool in understanding the pathophysiology of schizophrenia and depression in future studies.

Identification of β-barrel membrane proteins based on amino acid composition properties and predicted secondary structure

Unlike all-helices membrane proteins, beta-barrel membrane proteins can not be successfully discriminated from other proteins, especially from all-beta soluble proteins. This paper performs an analysis on the amino acid composition in membrane parts of 12 beta-barrel membrane proteins versus beta-strands of 79 all-beta soluble proteins. The average and variance of the amino acid composition in these two classes are calculated. Amino acids such as Gly, Asn, Val that are most likely associated with classification are selected based on Fishers discriminant ratio. A linear classifier built with these selected amino acids composition in observed beta-strands achieves 100% classification accuracy for 12 membrane proteins and 79 soluble proteins in a four-fold cross-validation experiment. Since at present the accuracy of secondary structure prediction is quite high, a promising method to identify beta-barrel membrane proteins is presented based on the linear classifier coupled with predicted secondary structure. Applied to 241 beta-barrel membrane proteins and 3855 soluble proteins with various structures, the method achieves 85.48% (206/241) sensitivity and 92.53% specificity (3567/3855).

Electroencephalographic differences between depressed and control subjects: An aspect of interdependence analysis

Anomalies in beta-waves have been found to be associated with mental depression. However, little is known about the causality of cortical inter- and intrahemispheric dependence of depressed patients in various cognitive states. This study investigates the possibility of beta-wave interdependence in depressed patients subjected to mental arithmetic tasks following relaxation. The EEGs of 12 depressed patients (age=37.2+/-11.8 years from 15 to 74 years, male/female=7/5) and 12 healthy volunteers (age=37.5+/-11.7 years from 22 to 58 years, male/female=6/6) were analyzed using a causality measure, partial directed coherence (PDC). The depressed patients showed lower frontal cortical interdependence in both the resting and mental arithmetic task states, confirming the histopathological evidence which shows that supra- and infragranular layers of the dorsolateral prefrontal cortex of depressed patients decrease both in density and in the size of neurons and glial cells. On the other hand, the mental arithmetic task was found to enhance inter- and intrahemispheric interactions in both groups, and such hemispheric hyperactivation is consistent with findings from functional imaging. The results presented here indicate that PDC can be a useful tool for evaluating changes in cortical interdependence in different psychotic or mental states and might well be used for diagnosis and therapeutic assessment in affective disorders.

Describing the Nonstationarity Level of Neurological Signals Based on Quantifications of Time–Frequency Representation

Most neurological signals including electroencephalogram (EEG), evoked potential (EP) and local field potential (LFP) have been known to be time varying and nonstationary, especially in some pathological conditions. Currently, the most widely used quantitative tool for such nonstationary signals is time-frequency representation (TFR) which demonstrates the temporal evolution of different frequency components. However, TFR does not directly provide a quantitative measure of nonstationarity level, e.g., how far the process deviates from stationarity. In this study, we introduced three different quantifications of TFR (qTFR) to characterize the nonstationarity level of the involving signals: 1) degree of stationarity (DS); 2) Shannon entropy (SE) of the marginal spectrum; and 3) Kullback-Leibler distance (KLD) between a TFR and a uniform distribution. These descriptors provide quantitative analysis of stationarity of a signal such that the stationarity of different signals could be compared. In this study, we obtained the TFRs of the EEG signals before and after the hypoxic-ischemic (HI) brain injury and examined the stationarity of the EEG. DS, SE, and KLD can indicate the nonstationarity change of EEG at each frequency following the HI injury, especially in the upperdelta-and lower thetas-band (e.g., [2 Hz, 8 Hzi) as well as in the beta2 band (e.g., [22 Hz-26 Hzi). Moreover, it is shown that the stationarity of the EEG changes differently in different frequencies following the HI injury.

Impaired neuronal synchrony after focal ischemic stroke in elderly patients

OBJECTIVE This study investigated whether cortical synchrony derived from electroencephalography (EEG) in elderly patients is impaired and if the impairment might reflect long-term functional recovery after stroke. METHODS The scalp EEG signals of stroke patients (N=42) were collected within seven days after the onset of stroke and analyzed with phase synchronization (PS). Neurodeficit outcome was scored twice according to the National Institute of Health Stroke Scale (NIHSS): (1) at the same day of EEG recording and (2) two months after stroke. The correlation between cortical synchrony and NIHSS was analyzed. RESULTS The level of synchronization between lesion and intact areas in the ipsilateral hemisphere was reduced significantly after stroke, while the synchronization among intact areas increased to 114% among the control subjects. Furthermore, the patients with lower inter-hemispheric synchrony after stroke were observed to have a higher NIHSS two months after stroke. CONCLUSIONS Results indicated that the infarct broke down the cortical synchrony networks and affected large-scale neural communication. Inter-hemispheric synchrony was relevant to long-term functional recovery after stroke. SIGNIFICANCE The prognostic value of PS for functional recovery after stroke might be helpful in understanding the alteration of cortical networks after ischemic injury.

Analysis of pulse rate variability derived from photoplethysmography with the combination of lagged Poincaré plots and spectral characteristics

A combination of lagged Poincaré plots and spectral characteristics were used to investigate the effect of cigarette smoking on the autonomic nervous system (ANS). Heart rate variability (HRV) was determined from pulse-to-pulse intervals (PPI) of ear photoplethysmography (PPG) waveforms. Spectral power analysis of the pulse rate variability (PRV) was performed to determine low frequency (LF) and high frequency (HF) components, and a lagged Poincaré plot was introduced to evaluate the nonlinear characteristics of PRV. The correlations between lagged Poincaré plot and spectral power indices were studied in a group of apparently healthy habitual cigarette smokers and compared to non-smokers. The width (SD1m) and the length (SD2m) of lagged Poincaré plots significantly shrunk in the smokers for all lags (p<0.05) except SD1(4) and SD1(5). The results of this pilot study indicated that habitual smoking is associated with parasympathetic withdrawal and augments sympathetic nerve activity. The results also demonstrated that the combination of lagged Poincaré plots and spectral characteristics could show promise as a method for distinguishing between different cardiovascular disease groups.

Influences of Hypothermia on the Cortical Blood Supply by Laser Speckle Imaging

Induced hypothermia has been broadly applied in neurological intensive care unit (NICU). Meanwhile, accidental hypothermia is also a threatening condition in daily life. It is meaningful to investigate the influences of temperature change on the cerebral blood flow (CBF). In the present study, temporal laser speckle image contrast analysis (tLASCA) was implemented to study the relative CBF change in cerebral artery, vein and capillary level under mild (35 degrees C) and moderate (32 degrees C) hypothermia. Twelve male Sprague-Dawley rats (300 +/-50 g) were anesthetized with sodium pentobarbital and randomly assigned to mild and moderate hypothermia groups (n=9 each). Laser speckle imaging (LSI) trials were acquired from baseline (37 degrees C), hypothermia (35 degrees C or 32 degrees C), and post-rewarming (37 degrees C) phases. In the mild group, mean CBF in different vessels all increased throughout the hypothermic and post-rewarming phases. On the contrary, mean CBF reduced by 10%-20% at 32 degrees C and returned to approximately 95% of the baseline level during the post-rewarming session in the moderate group. Besides, in the moderate group, a CBF rebound in vein was found in the post-rewarming phase. Our results suggested that the CBF changed differently between mild and moderate hypothermia, which may be worth for further study in clinic. And we demonstrated LSI as a promising method to achieve high spatiotemporal resolution CBF change with minimal invasion.

Influences of brain development and ageing on cortical interactive networks

OBJECTIVE To study the effect of brain development and ageing on the pattern of cortical interactive networks. METHODS By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). RESULTS By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. CONCLUSIONS The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. SIGNIFICANCE Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing.

More normal EEGs of depression patients during mental arithmetic than rest

The aim of this study is to compare the brain activities in depression patients and healthy controls by a quantitative method. In the present study, the wavelet entropy (WE) and subband segmentation analysis are proposed to characterize the degree of disorder and complexity of the electroencephalographic (EEG) signals recorded from 16 scalp electrodes in 20 depression patients and 20 normal controls at rest and during mental arithmetic. The WE analysis demonstrates the EEGs of the depression subjects have higher WE than those of the controls at rest, which indicates a less rhythmic and ordered status in depression, whereas such difference is not significant during mental arithmetic. These results provide evidence that depression patients have more regular brain wave during mental arithmetic than rest. Furthermore, the WE of the depression patients is higher during rest than mental arithmetic at almost all electrodes, and this phenomenon is not found in the controls. It may suggest that larger parts of the brain of the patients are active during rest than performing a cognitive task. In addition, marginal effect of hemisphere is detected for the patients during mental arithmetic. Our results show that the we could be a useful tool in cognitive process analysis, especially in depression.