Use of Intrinsic Entropy to Assess the Instantaneous Complexity of Thoracoabdominal Movement Patterns to Indicate the Effect of the Iso-Volume Maneuver Trial on the Performance of the Step Test.

The recent surge in interest surrounds the analysis of physiological signals with a non-linear dynamic approach. The measurement of entropy serves as a renowned method for indicating the complexity of a signal. However, there is a dearth of research concerning the non-linear dynamic analysis of respiratory signals. Therefore, this study employs a novel method known as intrinsic entropy (IE) to assess the short-term dynamic changes in thoracoabdominal movement patterns, as measured by respiratory inductance plethysmography (RIP), during various states such as resting, step test, recovery, and iso-volume maneuver (IVM) trials. The findings reveal a decrease in IE of thoracic wall movement (TWM) and an increase in IE of abdominal wall movement (AWM) following the IVM trial. This suggests that AWM may dominate the breathing exercise after the IVM trial. Moreover, due to the high temporal resolution of IE, it proves to be a suitable measure for assessing the complexity of thoracoabdominal movement patterns under non-stationary states such as the step test and recovery. The results also demonstrate that the instantaneous complexity of TWM and AWM can effectively capture instantaneous changes during non-stationary states, which may prove valuable in understanding the respiratory mechanism for healthcare purposes in daily life.

Toward Evaluating Critical Factors of Extubation Outcome with XCSR-Generated Rules.

Predicting the correct timing for extubation is pivotal for critically ill patients with mechanical ventilation support. Evidence suggests that extubation failure occurs in approximately 15-20% of patients, despite their passing of the extubation evaluation, necessitating reintubation. For critically ill patients, reintubation invariably increases mortality risk and medical costs. The numerous parameters that have been proposed for extubation decision-making, which constitute the key predictors of successful extubation, remains unclear. In this study, an extended classifier system capable of processing real-value inputs was proposed to select features of successful extubation. In total, 40 features linked to clinical information and variables acquired during spontaneous breathing trial (SBT) were used as the environmental inputs. According to the number of "don't care" rules in a population set, Probusage, the probability of the feature not being classified as above rules, can be calculated. A total of 228 subjects' results showed that Probusage was higher than 90% for minute ventilation at the 1st, 30th, 60th, and 90th minutes; respiratory rate at the 90th minute; and body weight, indicating that the variance in respiratory parameters during an SBT are critical predictors of successful extubation. The present XCSR model is useful to evaluate critical factors of extubation outcomes. Additionally, the current findings suggest that SBT duration should exceed 90 min, and that clinicians should consider the variance in respiratory variables during an SBT before making extubation decisions.

The Indices of Instantaneous Pulse Rate Variability Are Indicators for Daily Life Quality Assessment in Patients with COPD.

Chronic obstructive pulmonary disease (COPD) is a progressive respiratory illness. Questionnaires such as modified Medical Research Council (mMRC) dyspnea scale and COPD assessment test (CAT) are useful for COPD condition and life quality assessment. These questionnaires reflect how respiratory disorder affects daily life. Breathing and autonomic nervous system (ANS) usually regulate each other. Few studies discussed the ANS activity and daily life quality in patients with COPD. Therefore, this study aimed to find the relationship between daily life quality assessed by mMRC or CAT and ANS assessed by a novel method, instantaneous pulse rate variability (iPRV), a method indicating not only the ANS activity but also the peripheral response. The result showed that the change in mMRC and the change in low frequency power to high frequency power ratio, which usually represents the sympathetic activity in conventional heart rate variability analysis, had significant correlation (r = 0.63; p < 0.05). The change in CAT and the change in high frequency power (regulated by vagal nervous and respiratory system) or very high frequency power (new frequency band can be indicated in iPRV spectrum) had significant negative correlation (r = -0.64 and -0.55, respectively; p < 0.05 for both). This study showed the change in iPRV indices when the condition of COPD was improvement or exacerbation. This study presents a possible way to show how cardiovascular activity affects daily life quality in patients with COPD. Increase in LF or decrease in HF and VHF would cause poorer quality of daily life in patients with COPD. The result can also be a reference for patients with COPD to choose the breathing type to adjust rehabilitation and therapy program for ANS regulation to indicate or improve their daily life quality.

Toward instantaneous frequency of respiration to investigate the risk of internet gaming disorder.

With the development of Internet, the number of people with symptoms of Internet gaming disorder (IGD) has increased. In the past, psychologists used retrospective questionnaires to diagnose IGD. However, it is difficult to diagnose IGD symptoms instantaneously using retrospective questionnaires due to the requirement of an Internet gaming experience of greater than 6 months and the limitations of retrospective memory. Observing the physiological regulation system might instantaneously diagnose IGD. However, observation of instantaneous physiological response is limited due to the lack of appropriate techniques. Our previous study successfully combined complimentary ensemble empirical mode decomposition and normalized direct quadrature to obtain respiratory instantaneous frequency (IF) to overcome this limitation. This study uses game-related films as stimulus materials to observe the difference in respiratory IF response per second of gamers with high-risk IGD (HIGD) and low-risk IGD (LIGD). The result showed that the respiratory IF of gamers with HIGD is lower than those of gamers with LIGD at the time of stimulation. In addition, the study also observes the dynamic change in respiratory IF per second (IFdiff). The results showed that the instant at which a significant difference is observed in IFdiff between HIGD and LIGD can be matched to the stimulation of the films. In summary, this study demonstrated that the IFdiff of gamers with HIGD and LIGD are different when stimulated. Therefore, this suggests that IFdiff might be used as a potential physiological marker to instantaneously distinguish and diagnosis the risk of IGD.Clinical Relevance- This study investigates the dynamically psychophysiological response regulation by analyzing the respiratory IF of gamers diagnosed with IGD.

Is the asynchronous phase of thoracoabdominal movement a novel feature of successful extubation? A preliminary result.

Mechanical ventilation is necessary to maintain patients' life in intensive care units. However, too early or too late extubation may injure the muscles or lead to respiratory failure. Therefore, the spontaneous breathing trial (SBT) is applied for testing whether the patients can spontaneously breathe or not. However, previous evidence still reported 15%~20% of the rate of extubation fail. The monitor only considers the ventilation variables during SBT. Therefore, this study measures the asynchronization between thoracic and abdomen wall movement (TWM and AWM) by using instantaneous phase difference method (IPD) during SBT for 120 minutes. The respiratory inductive plethysmography were used for TWM and AWM measurement. The preliminary result recruited 31 signals for further analysis. The result showed that in successful extubation group can be classified into two groups, IPD increase group, and IPD decrease group; but in extubation fail group, the IPD value only increase. Therefore, the IPD decrease group can almost perfectly be discriminated with extubation fail group, especially after 70 minutes (Area under curve of operating characteristic curve was 1). These results showed IPD is an important key factor to find whether the patient is suitable for extubation or not. These finding suggest that the asynchronization between TWM and AWM should be considered as a predictor of extubation outcome. In future work, we plan to recruit 150 subjects to validate the result of this preliminary result. In addition, advanced machine learning method is considered to apply for building effective models to discriminate the IPD increase group and extubation fail group.Clinical Relevance- The finding of this study is that the patients whose average IPD of 95 to 100 minutes was smaller than average IPD of first 5 minutes of SBT could be 100% successful extubation. In addition, ability of discrimination of average IPD after 70 minutes presents AUC 1.

Classification of the risk of internet gaming disorder by flow short scale and cardiovascular response.

The American Psychiatric Association has identified Internet gaming disorder (IGD) as a potential psychiatric disorder. Questionnaires are the main method to classify high-risk IGD (HIGD) and low-risk IGD (LIGD). However, the results obtained using questionnaires might be affected due to several factors. Flow can measure a person's state of concentration and cardiovascular signals can reflect the autonomic responses of a person. We propose to observe the cardiovascular responses and flow scores from the flow short scale of the HIGD and LIGD groups to assist questionnaires in IGD risk assessment. The preliminary study recruited 18 gamers from colleges. Games with the easy and hard levels were set to arouse desire for playing. The result showed that the flow scores of five HIGD participants were significantly lower compared with that of 13 LIGD participants. The stroke volume (SV) of the LIGD group during baseline (67.06 ± 11.61) was significantly greater that of (p < 0.05) while playing the easy game (64.08 ± 10.37) and playing the hard game (63.70 ± 9.89). For the LIGD group, the cardiac output (CO) during baseline (5.28 ± 0.97) was significantly greater (p < 0.01) than that of recovery (5.03 ± 0.83), and while playing the easy game (5.34 ± 0.98) it was significantly more than that during recovery (p < 0.05). For the HIGD group, a significant difference in the heart rate, SV, and CO was not observed. The changes in cardiovascular responses of the LIGD group are greater than that of the HIGD group. Gamers with LIGD might have a higher susceptibility to the negative effect of playing video games, but gamers with HIGD might not. The finding of this study might help psychologists to estimate the IGD risk.Clinical Relevance- This study investigated the differences in the score of flow short scale, self-assessment manikin, challenge/skill, emotional questionnaire, and the changes in the cardiovascular responses between the HIGD and LIGD groups.

Extended classifier system with continuous real-coded variables for feature extraction of instantaneous pulse-rate variability and respiration of individuals with gaming disorder.

BACKGROUND: Individuals with gaming disorder (GD) exhibit autonomic nervous system responses that indicate dysfunctional emotion regulation. Pulse rate variability (PRV) is a valuable biomarker for investigating the autonomic function of patients with mental disorders. Because individuals with GD dynamically regulate emotions during gaming, the PRV response relating to GD is not well understood. To investigate the dynamic PRV responses of individuals with GD, this study proposed the indexes of instantaneous PRV (iPRV) and instantaneous respiratory frequency (IFresp) of arterial blood pressure signals using empirical mode decomposition and normalized direct-quadrature algorithms. iPRV consists of low-frequency (LF), high-frequency (HF), and very high-frequency (VHF) bands. Moreover, a novel method of extended classifier system with continuous real-coded variables (XCSR) was used to detect GD and extract GD-related iPRV features using iPRV and IFresp as input data. RESULTS: A total of 32 college students without depressive and anxiety symptoms or cardiovascular diseases were recruited in this study. Participants were grouped into the high-risk GD and low-risk GD using both Chen Internet Addiction Scale and Internet Gaming Disorder Questionnaire. Their arterial blood pressures signals were measured while they watched gameplay videos with negative or positive emotional stimuli. Seven participants with high-risk GD exhibited significantly increased normalized VHF (nVHF) PRV and IFresp readings and significantly decreased normalized LF (nLF) PRV readings and LF/HF PRV ratios (from baseline) during negative or positive gameplay videos stimuli. These participants also exhibited higher nVHF PRV and lower nLF PRV readings and LF/HF PRV ratios when they experienced negative gameplay video stimuli relative to 17 participants with low-risk GD. The classification accuracy of the XCSR reached 90% for both negative and positive video stimuli, and nVHF PRV was most frequently used to detect GD risk. CONCLUSIONS: iPRV and IFresp can be used to detect GD and analyze the autonomic mechanism of individuals with GD.

Instantaneous Respiratory Response of Gamer with High-Risk Internet Gaming Disorder during Game-Film Stimuli by Using Complementary Ensemble Empirical Mode Decomposition.

Gamers with Internet gaming disorder (IGD) dynamically regulate their psychophysiological responses during playing; however, analyzing instantaneous psychophysiological responses in these gamers has been limited by a lack of appropriate methods. We propose combining the Complementary Ensemble Empirical Mode Decomposition and Direct Quadrature methods to overcome this limitation. The related effect of abdominal breathing (AB) training (as a relaxing psychology method) on the distribution of instantaneous frequency (IF) was investigated by calculating median (IFmed), kurtosis (IFkurt) and skewness (IFskew), and 19 participants with high-risk IGD (HIGD) were found to have increased IFmed [massively multiplayer online role-playing game (MMORPG): 0.36 ± 0.08; first-person shooter game (FPSG): 0.34 ± 0.08] but decreased IFkurt (MMORPG: 5.98 ± 2.31; FPSG: 6.84 ± 4.61) and IFskew (MMORPG: 0.40 ± 0.69; FPSG: 0.64 ±1.04) during game-film stimuli compared with baseline and recovery states. After AB training, IFmed of these 19 participants (MMORPG: 0.24 ± 0.11; FPSG: 0.18 ± 0.06) decreased significantly. This study is firstly to observe the IF distribution of respiratory signal in gamers with HIGD; thus, this distribution may be used as a respiratory physiological marker of IGD risk.

A Novel Cue-Induced Abdominal Reaction Analysis for Internet Gaming Disorder.

Individuals with Internet gaming disorder (IGD) frequently play online games to achieve satisfaction. Numerous signal processing questions regarding the negative consequences and characteristic respiration in a long-term sitting posture remain unanswered. This study recruited 50 individuals with high-risk and low-risk IGD (HIGD and LIGD); these participants were taught to perform a specific respiration during game-film stimuli. The instantaneous frequencies on abdominal movement (fDF) were calculated with ensemble empirical mode decomposition (EEMD). The difference value (ΔfDF) between rest and stimulus statuses was calculated and found that HIGD showed ΔfDF values of 0.060 during positive stimuli and 0.055 during negative stimuli before the exercise but 0.020 and 0.016, respectively, after the exercise. However, the ΔfDF value for those with LIGD during negative stimuli before the exercise was 0.013, and it increased to 0.025 after the exercise. This is the first approach to IGD discrimination toward abdominal response with EEMD.

Development of Limited-Angle Iterative Reconstruction Algorithms with Context Encoder-Based Sinogram Completion for Micro-CT Applications.

Limited-angle iterative reconstruction (LAIR) reduces the radiation dose required for computed tomography (CT) imaging by decreasing the range of the projection angle. We developed an image-quality-based stopping-criteria method with a flexible and innovative instrument design that, when combined with LAIR, provides the image quality of a conventional CT system. This study describes the construction of different scan acquisition protocols for micro-CT system applications. Fully-sampled Feldkamp (FDK)-reconstructed images were used as references for comparison to assess the image quality produced by these tested protocols. The insufficient portions of a sinogram were inpainted by applying a context encoder (CE), a type of generative adversarial network, to the LAIR process. The context image was passed through an encoder to identify features that were connected to the decoder using a channel-wise fully-connected layer. Our results evidence the excellent performance of this novel approach. Even when we reduce the radiation dose by 1/4, the iterative-based LAIR improved the full-width half-maximum, contrast-to-noise and signal-to-noise ratios by 20% to 40% compared to a fully-sampled FDK-based reconstruction. Our data support that this CE-based sinogram completion method enhances the efficacy and efficiency of LAIR and that would allow feasibility of limited angle reconstruction.

Towards estimation of respiratory muscle effort with respiratory inductance plethysmography signals and complementary ensemble empirical mode decomposition.

Respiratory inductance plethysmography (RIP) sensor is an inexpensive, non-invasive, easy-to-use transducer for collecting respiratory movement data. Studies have reported that the RIP signal's amplitude and frequency can be used to discriminate respiratory diseases. However, with the conventional approach of RIP data analysis, respiratory muscle effort cannot be estimated. In this paper, the estimation of the respiratory muscle effort through RIP signal was proposed. A complementary ensemble empirical mode decomposition method was used, to extract hidden signals from the RIP signals based on the frequency bands of the activities of different respiratory muscles. To validate the proposed method, an experiment to collect subjects' RIP signal under thoracic breathing (TB) and abdominal breathing (AB) was conducted. The experimental results for both the TB and AB indicate that the proposed method can be used to loosely estimate the activities of thoracic muscles, abdominal muscles, and diaphragm. Graphical abstract ᅟ.

Instantaneous phase difference analysis between thoracic and abdominal movement signals based on complementary ensemble empirical mode decomposition.

BACKGROUND: Thoracoabdominal asynchrony is often adopted to discriminate respiratory diseases in clinics. Conventionally, Lissajous figure analysis is the most frequently used estimation of the phase difference in thoracoabdominal asynchrony. However, the temporal resolution of the produced results is low and the estimation error increases when the signals are not sinusoidal. Other previous studies have reported time-domain procedures with the use of band-pass filters for phase-angle estimation. Nevertheless, the band-pass filters need calibration for phase delay elimination. METHODS: To improve the estimation, we propose a novel method (named as instantaneous phase difference) that is based on complementary ensemble empirical mode decomposition for estimating the instantaneous phase relation between measured thoracic wall movement and abdominal wall movement. To validate the proposed method, experiments on simulated time series and human-subject respiratory data with two breathing types (i.e., thoracic breathing and abdominal breathing) were conducted. Latest version of Lissajous figure analysis and automatic phase estimation procedure were compared. RESULTS: The simulation results show that the standard deviations of the proposed method were lower than those of two other conventional methods. The proposed method performed more accurately than the two conventional methods. For the human-subject respiratory data, the results of the proposed method are in line with those in the literature, and the correlation analysis result reveals that they were positively correlated with the results generated by the two conventional methods. Furthermore, the standard deviation of the proposed method was also the smallest. CONCLUSIONS: To summarize, this study proposes a novel method for estimating instantaneous phase differences. According to the findings from both the simulation and human-subject data, our approach was demonstrated to be effective. The method offers the following advantages: (1) improves the temporal resolution, (2) does not introduce a phase delay, (3) works with non-sinusoidal signals, (4) provides quantitative phase estimation without estimating the embedded frequency of breathing signals, and (5) works without calibrated measurements. The results demonstrate a higher temporal resolution of the phase difference estimation for the evaluation of thoracoabdominal asynchrony.

Respiratory sinus arrhythmia reactivity of internet addiction abusers in negative and positive emotional states using film clips stimulation.

BACKGROUND AND AIMS: People with internet addiction (IA) suffer from mental, physical, social, and occupational problems. IA includes psychological and physiological syndromes, and among the syndromes, emotion was suggested important mental and physiological expressions of IA. However, few physiologically emotional characters of IA were investigated. Autonomic nervous system (ANS) activity was a good link between IA and emotion, and respiratory sinus arrhythmia (RSA) gained from ANS was hypothesized related to IA. METHODS: An emotional induction experiment using negative and positive emotional films was conducted to validate the hypotheses. Thirty-four participants recruited from college were classified into high-risk IA group (HIA) and low-risk IA group (LIA). The respiratory signals, ECG signals, and self-assessed emotional intensity were acquired. The relationship and difference between IA and RSA was tested using descriptive statistics and inferential statistics. RESULTS: The RSA values of HIA were lower than those of LIA both before and after the induction of positive and negative emotions. When participants experienced a negative emotion (anger or fear), their RSA values declined; the decline for HIA was greater than that for LIA. The RSA values of HIA participants before induction of fear, happiness, or surprise, statistically significantly differed from that after induction of those emotions, with p values of 0.007, 0.04 and 0.01 respectively. The difference between the changes in RSA values upon the induction of surprise of HIA and LIA was statistically significant difference (p = 0.03). The interaction between two IA groups among emotional induction states was statistically significant difference. CONCLUSIONS: RSA value here was the main variable that reflected ANS activity, and especially vagus nerve regulation. The results revealed that the changes in RSA values were biologically significantly different between HIA and LIA, especially when sadness, happiness, or surprise was induced. HIA people exhibited stronger RSA reactivity following negative emotion than LIA people, but the RSA reactivity following positive emotion was weaker. This study provides more physiological information about IA and assists further investigation on the regulation of the ANS for IA abusers. The results will benefit the further application, early detection, therapy, and even early prevention. Clinical trial registration details This study was approved by the Institution Review Board of the National Taiwan University Hospital, Hsinchu Branch (Hsinchu, Taiwan), under the research project: A study of interactions between cognition, emotion and physiology (contract no.100IRB-32).

Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning.

Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction.

The Influence of Emotion on Keyboard Typing: An Experimental Study Using Auditory Stimuli.

In recent years, a novel approach for emotion recognition has been reported, which is by keystroke dynamics. The advantages of using this approach are that the data used is rather non-intrusive and easy to obtain. However, there were only limited investigations about the phenomenon itself in previous studies. Hence, this study aimed to examine the source of variance in keyboard typing patterns caused by emotions. A controlled experiment to collect subjects' keystroke data in different emotional states induced by International Affective Digitized Sounds (IADS) was conducted. Two-way Valence (3) x Arousal (3) ANOVAs was used to examine the collected dataset. The results of the experiment indicate that the effect of arousal is significant in keystroke duration (p < .05), keystroke latency (p < .01), but not in the accuracy rate of keyboard typing. The size of the emotional effect is small, compared to the individual variability. Our findings support the conclusion that the keystroke duration and latency are influenced by arousal. The finding about the size of the effect suggests that the accuracy rate of emotion recognition technology could be further improved if personalized models are utilized. Notably, the experiment was conducted using standard instruments and hence is expected to be highly reproducible.

Impact of vehicular networks on emergency medical services in urban areas.

The speed with which emergency personnel can provide emergency treatment is crucial to reducing death and disability among acute and critically ill patients. Unfortunately, the rapid development of cities and increased numbers of vehicles are preventing emergency vehicles from easily reaching locations where they are needed. A significant number of researchers are experimenting with vehicular networks to address this issue, but in most studies the focus has been on communication technologies and protocols, with few efforts to assess how network applications actually support emergency medical care. Our motivation was to search the literature for suggested methods for assisting emergency vehicles, and to use simulations to evaluate them. Our results and evidence-based studies were cross-referenced to assess each method in terms of cumulative survival ratio (CSR) gains for acute and critically ill patients. Simulation results indicate that traffic light preemption resulted in significant CSR increases of between 32.4% and 90.2%. Route guidance was found to increase CSRs from 14.1% to 57.8%, while path clearing increased CSRs by 15.5% or less. It is our hope that this data will support the efforts of emergency medical technicians, traffic managers, and policy makers.

The influence of emotion on keyboard typing: an experimental study using visual stimuli.

BACKGROUND: Emotion recognition technology plays the essential role of enhancement in Human-Computer Interaction (HCI). In recent years, a novel approach for emotion recognition has been reported, which is by keystroke dynamics. This approach can be considered to be rather desirable in HCI because the data used is rather non-intrusive and easy to obtain. However, there were only limited investigations about the phenomenon itself in previous studies. This study aims to examine the source of variance in keystroke typing patterns caused by emotions. METHODS: A controlled experiment to collect subjects' keystroke data in different emotional states induced by International Affective Picture System (IAPS) was conducted. Two-way Valence (3) × Arousal (3) ANOVAs were used to examine the collected dataset. RESULTS: The results of the experiment indicate that the effect of emotion is significant (p<.001) in the keystroke duration, keystroke latency, and accuracy rate of the keyboard typing. However, the size of the emotional effect is small, compare to the individual variability. CONCLUSIONS: Our findings support the conclusion that the keystroke duration, keystroke latency, and also the accuracy rate of typing, are influenced by emotional states. Notably, the finding about the size of effect suggests that the accuracy rate of the emotion recognition could be further improved if personalized models are utilized. On the other hand, the finding also provides an explanation of why real-world applications which authenticate the identity of users by monitoring keystrokes may not be interfered by the emotional states of users. The experiment was conducted using standard instruments and hence is expected to be highly reproducible.

The interpretation of very high frequency band of instantaneous pulse rate variability during paced respiration.

BACKGROUND: Pulse rate (PR) indicates heart beat rhythm and contains various intrinsic characteristics of peripheral regulation. Pulse rate variability (PRV) is a reliable method to assess autonomic nervous system function quantitatively as an effective alternative to heart rate variability. However, the frequency range of PRV is limited by the temporal resolution of PR based on heart rate and it is further restricted the exploration of optimal autoregulation frequency based on spectral analysis. METHODS: Recently, a new novel method, called instantaneous PRV (iPRV), was proposed. iPRV breaks the limitation of temporal resolution and extends the frequency band. Moreover, iPRV provides a new frequency band, called very high frequency band (VHF; 0.4-0.9 Hz). RESULTS: The results showed that the VHF indicated the influences of respiratory maneuvers (paced respiration at 6-cycle and 30-cycle) and the nonstationary condition (head-up tilt; HUT). CONCLUSIONS: VHF is as a potential indication of autoregulation in higher frequency range and with peripheral regulation. It helps for the frequency exploration of cardiovascular autoregulation.

Frequency range extension of spectral analysis of pulse rate variability based on Hilbert-Huang transform.

Heart rate variability (HRV) is a well-accepted indicator for neural regulatory mechanisms in cardiovascular circulation. Its spectrum analysis provides the powerful means of observing the modulation between sympathetic and parasympathetic nervous system. The timescale of HRV is limited by discrete beat-to-beat time intervals; therefore, the exploration region of frequency band of HRV spectrum is relatively narrow. It had been proved that pulse rate variability (PRV) is a surrogate measurement of HRV in most of the circumstances. Moreover, arterial pulse wave contains small oscillations resulting from complex regulation of cardiac pumping function and vascular tone at higher frequency range. This study proposed a novel instantaneous PRV (iPRV) measurement based on Hilbert-Huang transform. Fifteen healthy subjects participated in this study and received continuous blood pressure wave recording in supine and passive head-up tilt. The result showed that the very-high-frequency band (0.4-0.9 Hz) varied during head-up tilt and had strong correlation (r = 0.77) with high-frequency band and medium correlation (r = 0.643) with baroreflex sensitivity. The very-high-frequency band of iPRV helps for the exploration of non-stationary autoregulation and provides the non-stationary spectral evaluation of HRV without distortion or information loss.

Fluorescence intrinsic characterization of excitation-emission matrix using multi-dimensional ensemble empirical mode decomposition.

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes.