Affective Computing Based on Morphological Features of Photoplethysmography for Patients with Hypertension.

Negative and positive emotions are the risk and protective factors for the cause and prognosis of hypertension. This study aimed to use five photoplethysmography (PPG) waveform indices and affective computing (AC) to discriminate the emotional states in patients with hypertension. Forty-three patients with essential hypertension were measured for blood pressure and PPG signals under baseline and four emotional conditions (neutral, anger, happiness, and sadness), and the PPG signals were transformed into the mean standard deviation of five PPG waveform indices. A support vector machine was used as a classifier. The performance of the classifier was verified by using resubstitution and six-fold cross-validation (CV) methods. Feature selectors, including full search and genetic algorithm (GA), were used to select effective feature combinations. Traditional statistical analyses only differentiated between the emotional states and baseline, whereas AC achieved 100% accuracy in distinguishing between the emotional states and baseline by using the resubstitution method. AC showed high accuracy rates when used with 10 waveform features in distinguishing the records into two, three, and four classes by applying a six-fold CV. The GA feature selector further boosted the accuracy to 78.97%, 74.22%, and 67.35% in two-, three-, and four-class differentiation, respectively. The proposed AC achieved high accuracy in categorizing PPG records into distinct emotional states with features extracted from only five waveform indices. The results demonstrated the effectiveness of the five indices and the proposed AC in patients with hypertension.

Electroencephalogram patterns in patients comorbid with major depressive disorder and anxiety symptoms: Proposing a hypothesis based on hypercortical arousal and not frontal or parietal alpha asymmetry.

BACKGROUND: Major depressive disorder (MDD) is often comorbid with anxiety disorders or symptoms. Brain hyperactivity, frontal alpha asymmetry (FAA), and parietal alpha asymmetry (PAA) have been considered as trait markers in patients with MDD. This study investigated the electroencephalogram (EEG) patterns among patients with MDD comorbid with anxiety symptoms. METHODS: One hundred and thirty-five patients with MDD comorbid with anxiety (MDD group) and 135 healthy controls (HC group) were analyzed. The Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) were completed, and 19 EEG channels were measured during the resting state, depressive recall and recovery tasks, and happiness recall and recovery tasks. FAA and PAA were computed by log (F4 alpha)-log (F3 alpha) and log (P4 alpha)-log (P3 alpha). RESULTS: The FAA and PAA indices between the two groups showed no significant differences; however, compared with the HC group, the MDD group had lower total delta and theta values, and higher total beta, low beta, and high beta values in the resting state. The total beta value positively correlated with the BDI-II and BAI scores in the MDD group. LIMITATIONS: Most patients had anxious MDD and taking prescriptions, antidepressants or benzodiazepine may affect EEG patterns. CONCLUSION: Compared with HCs, patients with MDD comorbid with anxiety had a higher beta activity in the entire brain region, supporting the role of brain hyperactivity, instead of FAA or PAA, as a trait marker in these patients. A neurofeedback protocol could be developed in future based on the brain hyperactivity findings.

A Single Session of Heart Rate Variability Biofeedback Produced Greater Increases in Heart Rate Variability Than Autogenic Training.

Heart rate variability biofeedback (HRV-BF) has been confirmed to increase heart rate variability (HRV) and cardiac outflows by baroreflex in healthy populations and clinical patients. Autogenic training (AT) is common used in the psychological intervention. This study integrates a single-session of HRV-BF and AT into a high-technology mobile application (app), and examines the effects on HRV indices, breathing rates, and subjective relaxation scores. Healthy college students were recruited and assigned to the single-session HRV-BF group or AT group. Participants in the HRV-BF group received HRV-BF combined with paced breathing training, which gradually stepped down their breathing rates from 12, to 8, to 6 breaths/per min; and received feedback of HRV indices from the app. Participants in the AT group received autogenic training and feedback of heart rate from the app. A chest belt Zephyr BioHarness was connected through Bluetooth to a Zenfone5 mobile phone, it collected the signals of interbeat intervals and breathing rates at pre-training, mid-training, and post-training stages. The Kubios HRV software was used to analyze HRV indices. The results reveal higher HRV indices and lower breathing rates during mid-training and post-training in the HRV-BF group compared to the AT group. There were higher high-frequency of HRV at post-training than pre-training in the AT group. Participants of both groups increased their subjective relaxation scores after training. The HRV-BF protocol increased cardiac outflows by baroreflex and decreased breathing rates, and the AT protocol increased high-frequency of HRV. These high-technology wearable devices combined with psychological interventions will apply to various populations in the future.

The effects of alpha asymmetry and high-beta down-training neurofeedback for patients with the major depressive disorder and anxiety symptoms.

BACKGROUND: Alpha-asymmetry neurofeedback (ALAY) was applied to patients with major depressive disorder (MDD) based on the theory of frontal alpha asymmetry. Neurophysiological studies have found a higher high-beta activity of electroencephalography (EEG) at the posterior cortex among patients with comorbid MDD and anxiety symptoms. The present study examined the effects of ALAY and high-beta down-training (Beta) neurofeedback in symptoms of depression and anxiety and EEG parameters. METHOD: Eighty-seven patients with comorbid MDD and anxiety symptoms were allocated to the ALAY, Beta, or control groups. Both neurofeedback groups received ten-session neurofeedback. All participants completed the Beck Depression Inventory II (BDI-II), Beck Anxiety Inventory (BAI), and five minutes resting EEG recording at pre-test and post-test. EEG raw signals were transformed into an A1 score [log (F4 alpha) - log (F3 alpha)], P3 and P4 high-beta power. RESULTS: BDI-II and BAI scores decreased at post-test in both ALAY and Beta groups, but no significant difference between the two groups. No significant interaction effect in A1 score at pre-test and post-test between the ALAY, Beta, and control groups. The P3 high-beta was significantly decreased in the Beta group, an increase in the control group, and no change in the ALAY group at post-test compared to the pre-test. CONCLUSIONS: Both neurofeedback groups decreased symptoms of depression and anxiety. The Beta group was more effective in decreasing high-beta power at the parietal cortex compared to other groups. This non-invasive psychological intervention can be used in the future for patients with comorbid MDD and anxiety symptoms.

The Association of Type D personality with Heart Rate Variability and Lipid Profiles Among Patients with Coronary Artery Disease.

PURPOSE: Characteristics of the distressed (Type D) personality include negative affectivity (NA) and social inhibition (SI), which are associated with an increased risk of major adverse cardiac events and mortality among patients with coronary artery disease (CAD). The aims of this study were to examine: (1) the correlation of NA and SI with psychological characteristics, heart rate variability (HRV) indices, and lipids profiles and (2) the differences in psychological characteristics, HRV indices, and lipid profiles between patients with CAD with Type D personality and those with non-Type D personality. METHOD: A cross-sectional study was conducted on 168 patients with CAD. The Taiwanese 14-item Type D Scale, Chinese Hostility Inventory-Short Form, Beck Depression Inventory-II, Beck Anxiety Inventory, and Anger Rumination Scale were administered to all of the participants. The raw signals of electrocardiograms were recorded over a 5-min baseline resting period and then transformed to HRV indices representing short-term cardiac autonomic activations. Lipid profiles were acquired from patients' medical records. RESULTS: NA was positively correlated with hostility, depression, anxiety, and anger rumination. With respect to pathophysiological mechanisms for CAD with Type D personality, NA was negatively correlated with standard deviation of all normal-to-normal intervals (SDNN) and total power of HRV and positively correlated with total cholesterol. SI was positively correlated with suppressive hostility behavior and anger rumination; however, SI was not significantly correlated with expressive hostility behavior, or HRV indices and lipid profiles. CONCLUSION: Pathophysiological mechanisms leading to higher rates of adverse outcomes in CAD in individuals with Type D personalities may involve cardiac autonomic imbalance and lipid dysregulation.