Continuous electronic data capture of physiology, behavior and experience in real life: towards ecological momentary assessment of emotion

Emotions powerfully influence our physiology, behavior, and experience. A comprehensive assessment of affective states in health and disease would include responses from each of these domains in real life. Since no single physiologic parameter can index emotional states unambiguously, a broad assessment of physiologic responses is desirable. We present a recently developed system, the LifeShirt, which allows reliable ambulatory monitoring of a wide variety of cardiovascular, respiratory, metabolic, motor-behavioral, and experiential responses. The system consists of a garment with embedded inductive plethysmography and other sensors for physiologic data recording and a handheld computer for input of experiential data via touch screen. Parameters are extracted offline using sophisticated analysis and display software. The device is currently used in clinical studies and to monitor effects of physical and emotional stress in naturalistic settings. Further development of signal processing and pattern recognition algorithms will enhance computerized identification of type and extent of physical and emotional activatio

Categorizing the Role of Respiration in Cardiovascular and Cerebrovascular Variability Interactions

Objective: Respiration disturbs cardiovascular and cerebrovascular controls but its role is not fully elucidated. Methods: Respiration can be classified as a confounder if its observation reduces the strength of the causal relationship from source to target. Respiration is a suppressor if the opposite situation holds. We prove that a confounding/suppression (C/S) test can be accomplished by evaluating the sign of net redundancy/synergy balance in the predictability framework based on multivariate autoregressive modelling. In addition, we suggest that, under the hypothesis of Gaussian processes, the C/S test can be given in the transfer entropy decomposition framework as well. Experimental protocols: We applied the C/S test to variability series of respiratory movements, heart period, systolic arterial pressure, mean arterial pressure, and mean cerebral blood flow recorded in 17 pathological individuals (age: 648 yrs; 17 males) before and after induction of propofol-based general anesthesia prior to coronary artery bypass grafting, and in 13 healthy subjects (age: 278 yrs; 5 males) at rest in supine position and during head-up tilt with a table inclination of 60. Results: Respiration behaved systematically as a confounder for cardiovascular and cerebrovascular controls. In addition, its role was affected by propofol-based general anesthesia but not by a postural stimulus of limited intensity. Conclusion: The C/S test can be fruitfully exploited to categorize the role of respiration over causal variability interactions. Significance: The application of the C/S test could favor the comprehension of the role of respiration in cardiovascular and cerebrovascular regulations

The effect of spontaneous versus paced breathing on EEG, HRV, skin conductance and skin temperature

A dissertation submitted in fulfilment of the requirements for the degree Master of Science in Engineering, in the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg. January 2017 JohannesburgIt is well known that emotional stress has a negative impact on people’s health and physical, emotional and mental performance. Previous research has investigated the effects of stress on various aspects of physiology such as respiration, heart rate, heart rate variability (HRV), skin conductance, skin temperature and electrical activity in the brain. Essentially, HRV, Electroencephalography (EEG), skin conductance and skin temperature appear to reflect a stress response or state of arousal. Whilst the relationship between respiration rate, respiration rhythm and HRV is well documented, less is known about the relationship between respiration rate, EEG, skin conductance and skin temperature, whilst HRV is maximum (when there is resonance between HRV and respiration i.e. in phase with one another). This research project aims to investigate the impact that one session of slow paced breathing has on EEG, heart rate variability (HRV), skin conductance and skin temperature. Twenty male participants were randomly assigned to either a control or intervention group. Physiological data were recorded for the intervention and control group during one breathing session, over a short initial baseline (B1), a main session of 12 minutes, and a final baseline (B2). The only difference between the control and intervention groups was that during the main session, the intervention group practiced slow paced breathing (at 6 breaths per minute), while the control group breathed spontaneously. Wavelet transformation was used to analyse EEG data while Fourier transformation was used to analyse HRV. The study shows that slow-paced breathing significantly increases the low frequency and total power of the HRV but does not change the high frequency power of HRV. Furthermore, skin temperature significantly increased for the control group from B1 to Main, and was significantly higher for the control group when compared to the intervention group during the main session. There were no significant skin temperature changes between sessions for the intervention group. Skin conductance increased significantly from Main to B2 for the control group. No significant changes were found between sessions for the intervention group and between groups. EEG theta power at Cz decreased significantly from Main to B2 for the control group only, while theta power decreased at F4 from Main to B2 for both groups. Lastly, beta power at Cz decreased from B1 to B2 for the control group only. This significant effect that slow-paced breathing has on HRV suggests the hypothesis that with frequent practice, basal HRV would increase, and with it, potential benefits such as a reduction in anxiety and improved performance in specific tasks. Slow-paced breathing biofeedback thus shows promise as a simple, cheap, measurable and effective method to reduce the impact of stress on some physiological signals, suggesting a direction for future research.MT201

Acute Physiological, Symptomatic and Affective Responses to Exercise Training and Relationship with Exercise Adherence in Chronic Obstructive Pulmonary Disease

Study Objectives: i) To describe and compare, in COPD patients, the acute physiological, symptomatic, and affective responses to continuous training at a high intensity (CTHI), continuous training at the ventilatory threshold (CTVT), and interval training (IT); ii) To examine the nature and degree of association between acute measures of intensity and adherence to a 12-week exercise-training program; iii) To investigate whether the relationship between acute responses and adherence is mediated or moderated by affect/vigor. Methods: Thirty-five COPD patients (FEV1 = 60.2 ± 15.8 % predicted) underwent baseline assessments, were randomly assigned to CTHI, CTVT, or IT, were monitored during a single exercise-training bout, and subsequently took part in a 12-week exercise-training program. Physiological, symptomatic, and affective responses were measured using a portable system, the PANAS and GVA questionnaires, and the Borg scale; respectively. Adherence was defined as the percent time spent within the target heart rate range for attended sessions. Results: In comparison to CTHI, CTVT was associated with lower levels of RER, HR, and RR, whereas IT was associated with higher levels of VE, VE/MVV, RR, and a greater drop in SpO2. Affective state generally improved from pre- to post-exercise, with increases in positive affect (F=9.74, p<0.001) and decreases in negative affect (F=6.43, p=0.005). The CTVT group experienced a greater dip in global affect mid-exercise compared to CTHI (p=0.04), yet had a higher level of end-exercise alertness compared to CTHI (p=0.01) and IT (p=0.02). The IT group reported the lowest levels of post-exercise alertness (p=0.04 versus CTHI and p=0.02 versus CTVT), and significantly lower 12-week adherence rates (F=6.69, p=0.004). Mean exercise VO2 (r=-0.466, p=0.007) and end-exercise global vigor (r=0.420, p=0.017) were most strongly correlated with adherence. The moderation model was supported, where end-exercise global vigor moderated the relationship between VO2 and adherence (β=2.74, t (32)=2.32, p=0.03). Conclusion: Compared to CTHI, CTVT was associated with less physiological strain, and greater end-exercise alertness, while IT was associated with slightly more physiological strain, lower post-exercise alertness, and lower 12-week adherence rates. VO2 and end-exercise global vigor were most strongly associated with adherence. Acute end-exercise vigor was found to moderate the relationship between acute VO2 and adherence

Stress response index for adverse childhood experience based on fusion of hypothalamus pituitary adrenocorticol and autonomic nervous system biomarkers

Early life exposure to stress such as adverse childhood experiences has been suggested to cause changes in physiological processes and alteration in stress response magnitude which might have significant impact on health later in life. For this reason, detection of this altered stress response can be used as an indicator for future health. To date, there is no study that utilized this information to indicate future health. In order to detect the altered stress response, biomarkers that represent both Autonomic Nervous System (ANS) and Hypothalamic-Pituitary-Adrenocorticol (HPA) is proposed. Among the available biomarkers, Heart Rate Variability (HRV) has been proven as a powerful biomarker that represents ANS. Meanwhile, salivary cortisol has been suggested as a biomarker that reflects the HPA. Even though many studies used multiple biomarkers to measure the stress response, the results for each biomarker were analysed separately. Therefore, this study fuses the biomarker that represents both ANS and HPA as a single measure, proposes a new method to classify the stress response based on adverse childhood experience in the form of stress response index as a future health indicator. Electrocardiograph, blood pressure, pulse rate and Salivary Cortisol (SCort) were collected from 23 participants, 12 participants who had adverse childhood experience while the remaining 11 act as the control group. The recording session was done during a Paced Auditory Serial Addition Test (PASAT). HRV features were then extracted from the electrocardiograph (ECG) using time, frequency, time-frequency analysis, and wavelet transform. Following this, genetic algorithm was implemented to select a subset of 12 HRV features from 83 features. Next, the selected HRV features were combined with other biomarkers using parallel and serial fusion for performance comparison. Using Support Vector Machine (SVM), results showed that fused feature of the parallel fusion, so-called Euclidean distance (ed), demonstrated the highest performance with 80.0% accuracy, 83.3% sensitivity and 78.3% specificity. Finally, the fused feature of the Euclidean distance was fed into SVM in order to model the stress response index as an indicator for future health. This index was validated using all samples and achieved 91.3% accuracy. From this study, a new method based on HRV-SCort biomarker using Euclidean distance and SVM named as ed-SVM was proven to be an effective method to classify the stress response and could further be used to model a stress response index. This index can then be benefited as an indicator for future health to improve the health care management in adulthood

Stress response index for adverse childhood experience based on fusion of hypothalamus pituitary adrenocorticol and autonomic nervous system biomakers

Early life exposure to stress such as adverse childhood experiences has been suggested to cause changes in physiological processes and alteration in stress response magnitude which might have significant impact on health later in life. For this reason, detection of this altered stress response can be used as an indicator for future health. To date, there is no study that utilized this information to indicate future health. In order to detect the altered stress response, biomarkers that represent both Autonomic Nervous System (ANS) and Hypothalamic-Pituitary-Adrenocorticol (HPA) is proposed. Among the available biomarkers, Heart Rate Variability (HRV) has been proven as a powerful biomarker that represents ANS. Meanwhile, salivary cortisol has been suggested as a biomarker that reflects the HPA. Even though many studies used multiple biomarkers to measure the stress response, the results for each biomarker were analysed separately. Therefore, this study fuses the biomarker that represents both ANS and HPA as a single measure, proposes a new method to classify the stress response based on adverse childhood experience in the form of stress response index as a future health indicator. Electrocardiograph, blood pressure, pulse rate and Salivary Cortisol (SCort) were collected from 23 participants, 12 participants who had adverse childhood experience while the remaining 11 act as the control group. The recording session was done during a Paced Auditory Serial Addition Test (PASAT). HRV features were then extracted from the electrocardiograph (ECG) using time, frequency, time-frequency analysis, and wavelet transform. Following this, genetic algorithm was implemented to select a subset of 12 HRV features from 83 features. Next, the selected HRV features were combined with other biomarkers using parallel and serial fusion for performance comparison. Using Support Vector Machine (SVM), results showed that fused feature of the parallel fusion, so-called Euclidean distance (ed), demonstrated the highest performance with 80.0% accuracy, 83.3% sensitivity and 78.3% specificity. Finally, the fused feature of the Euclidean distance was fed into SVM in order to model the stress response index as an indicator for future health. This index was validated using all samples and achieved 91.3% accuracy. From this study, a new method based on HRV-SCort biomarker using Euclidean distance and SVM named as ed-SVM was proven to be an effective method to classify the stress response and could further be used to model a stress response index. This index can then be benefited as an indicator for future health to improve the health care management in adulthood