Orientation Invariant ECG-Based Stethoscope Tracking for Heart Auscultation Training on Augmented Standardized Patients

Auscultation, the act of listening to the heart and lung sounds, can reveal substantial information about patients’ health and other cardiac-related problems; therefore, competent training can be a key for accurate and reliable diagnosis. Standardized patients (SPs), who are healthy individuals trained to portray real patients, have been extensively used for such training and other medical teaching techniques; however, the range of symptoms and conditions they can simulate remains limited since they are only patient actors. In this work, we describe a novel tracking method for placing virtual symptoms in correct auscultation areas based on recorded ECG signals with various stethoscope diaphragm orientations; this augmented reality simulation would extend the capabilities of SPs and allow medical trainees to hear abnormal heart and lung sounds in a normal SP. ECG signals recorded from two different SPs over a wide range of stethoscope diaphragm orientations were processed and analyzed to accurately distinguish four different heart auscultation areas, aortic, mitral, pulmonic and tricuspid, for any stethoscope’s orientation. After processing the signals and extracting relevant features, different classifiers were applied for assessment of the proposed method; 95.1% and 87.1% accuracy were obtained for SP1 and SP2, respectively. The proposed system provides an efficient, non-invasive, and cost efficient method for training medical practitioners on heart auscultation

Exploration of microRNAs as biomarkers of affective state in the pig

The assessment of animal welfare has advanced to include measures of emotions. A variety of behavioural and physiological markers are commonly used to infer affective states in animals; however, these often lack specificity, or are simply not suitable for production environments. Therefore, there is a need to develop novel measures of animal emotions. Recently, microRNA (miRNA), have emerged as diagnostic markers for a number of neurological conditions and have been implicated in human affective disorders including anxiety and depression. Thus, these molecules have the potential to become markers of the activity associated with emotional processes. In this research, I have explored the efficacy of miRNA as biomarkers for both positive and negative emotional states in pigs. I investigated how miRNA activity changes in brain during different affective states, and explored if these changes could be corroborated with changes in the blood, thus providing a peripheral measure of emotion in pigs. In chapter 3 I hypothesized that 1) pain in response to tail docking would result in differentially expressed miRNAs in both the blood and brain of piglets, and that this expression would be modulated by local anaesthetic, 2) changes in miRNA expressions would be similar between the blood and the brain, thus providing a reliable proxy marker of brain miRNA expression associated with pain processes. MiR-412 and miR-7a were differentially expressed in the Periaqueductal-grey (PAG) brain region following tail-docking, but the response was not mitigated by analgesic. MiRNA expression was not altered in either the Amygdala (AMY) region of the brain or in blood following treatment, when compared with control animals, suggesting the observed change in expression may not reflect the animal’s underlying emotional state but perhaps another biological response to tissue damage, such as inflammation. Furthermore, the sampling time-points selected in this study may have resulted in missed peaks of miRNA up- or down-regulation. Consequently, under these experimental conditions, the effectiveness of circulating miRNA as a biomarker of acute pain in pigs is questionable. Nonetheless, there may be some benefit in their application as biomarkers of inflammation in response to tissue damage. Chapter 4 tested the validity of measuring circulating cortisol as an indicator for effective delivery of a single intravenous dose of the antidepressant fluoxetine hydrochloride to the pig brain. Previously, pharmacological agents that manipulate the affective state have been used to evaluate novel biomarkers for assessment of emotional states. Antidepressant treatment resulted in increased mean plasma cortisol levels 15-165 minutes following treatment compared with saline controls, suggesting that, similar to other species, plasma cortisol is an indicator of fluoxetine hydrochloride efficacy. However, individual cortisol profiles of pigs treated with the antidepressant were highly variable with either the expected, an unorthodox, or no response. In humans, individual variation in patient responses to anti-depressant treatment has been observed previously. Therefore, I propose that variability in individual cortisol responses following anti-depressant treatment in pigs may be attributed to the following; (1) inherent pharmacological differences, including disparity in receptor numbers, structures or functions, or (2) variations in HPA axis responsiveness to the antidepressant, or (3) a combination of these. For these reasons, I conclude that the inter-individual variations in cortisol responses observed currently preclude the use of cortisol as a reporter for fluoxetine hydrochloride efficacy in pigs. In chapter 5 I exposed pigs to husbandry practices known to impact emotional states, namely barren housing to induce a negative emotional state, or highly enriched housing conditions to create a relatively more positive state. Differential expression patterns of miRNA in the brain and blood were analysed, and concentrations of the neurotransmitter’s serotonin (5-HT), and dopamine (DA), and their retrospective metabolites (5-HIAA and DOPAC), as well as Judgement Bias were used as corroborating measures to infer the emotional status in the pigs. Dopamine was altered in the brain following enriched housing when compared with barren housing. No change was observed in the miRNA, behaviour or brain serotonin. The results of this experiment imply that either A) miRNAs are not likely valid biomarkers of affective states, at least under the type of conditions employed in this study, or B) the experimental paradigm used with housing as a modifier of emotional state was not sufficient to create differential emotional states, and therefore establish the validity of miRNA as biomarkers. The outcomes of this dissertation suggest that, for the most part, the experimental conditions employed in these trials were insufficient in altering miRNA signatures in brain and blood parameters. The application of miRNA as biomarkers of emotion may not be valid for environmental and/or husbandry conditions where physiological and tissue responses are not elicited, but there may be some benefit in their application as markers of pain or inflammation. However, with regards to the latter, further investigation is required in relation to the types of tissues to be sampled, the time at which sampling occurs and the ability to effectively conclude that the measures taken are specific to the negative emotional experience of pain.Thesis (Ph.D.) -- University of Adelaide, School of Animal and Veterinary Science, 202

Affective state recognition in Virtual Reality from electromyography and photoplethysmography using head-mounted wearable sensors.

The three core components of Affective Computing (AC) are emotion expression recognition, emotion processing, and emotional feedback. Affective states are typically characterized in a two-dimensional space consisting of arousal, i.e., the intensity of the emotion felt; and valence, i.e., the degree to which the current emotion is pleasant or unpleasant. These fundamental properties of emotion can not only be measured using subjective ratings from users, but also with the help of physiological and behavioural measures, which potentially provide an objective evaluation across users. Multiple combinations of measures are utilised in AC for a range of applications, including education, healthcare, marketing, and entertainment. As the uses of immersive Virtual Reality (VR) technologies are growing, there is a rapidly increasing need for robust affect recognition in VR settings. However, the integration of affect detection methodologies with VR remains an unmet challenge due to constraints posed by the current VR technologies, such as Head Mounted Displays. This EngD project is designed to overcome some of the challenges by effectively integrating valence and arousal recognition methods in VR technologies and by testing their reliability in seated and room-scale full immersive VR conditions. The aim of this EngD research project is to identify how affective states are elicited in VR and how they can be efficiently measured, without constraining the movement and decreasing the sense of presence in the virtual world. Through a three-years long collaboration with Emteq labs Ltd, a wearable technology company, we assisted in the development of a novel multimodal affect detection system, specifically tailored towards the requirements of VR. This thesis will describe the architecture of the system, the research studies that enabled this development, and the future challenges. The studies conducted, validated the reliability of our proposed system, including the VR stimuli design, data measures and processing pipeline. This work could inform future studies in the field of AC in VR and assist in the development of novel applications and healthcare interventions