Remembering the future: An overview of co-evolution in musical improvisation

Musical improvisation is driven mainly by the unconscious mind, engaging the dialogic imagination to reference the entire cultural heritage of an improvisor in a single flash. This paper introduces a case study of evolutionary computation techniques, in particular genetic co-evolution, as applied to the frequency domain using MPEG7 techniques, in order to create an artificial agent that mediates between an improvisor and her unconscious mind, to probe and unblock improvisatory action in live music performance or practice

Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device

This is the final version. Available on open access from IET via the DOI in this recordWearable physiological monitors are becoming increasingly commonplace in the consumer domain, but in literature there exists no substantive studies of their performance when measuring the physiology of ambulatory patients. In this Letter, the authors investigate the reliability of the heart-rate (HR) sensor in an exemplar 'wearable' wrist-worn monitoring system (the Microsoft Band 2); their experiments quantify the propagation of error from (i) the photoplethysmogram (PPG) acquired by pulse oximetry, to (ii) estimation of HR, and (iii) subsequent calculation of HR variability (HRV) features. Their experiments confirm that motion artefacts account for the majority of this error, and show that the unreliable portions of HR data can be removed, using the accelerometer sensor from the wearable device. The experiments further show that acquired signals contain noise with substantial energy in the high-frequency band, and that this contributes to subsequent variability in standard HRV features often used in clinical practice. The authors finally show that the conventional use of long-duration windows of data is not needed to perform accurate estimation of time-domain HRV features

Developing opportunities in digital health: The case of BioBeats Ltd

This is the author accepted manuscriptDeparting from established research on entrepreneurship, design-based entrepreneurship places an explicit emphasis on the entrepreneurial process as evolutionary and emergent in which knowledge and understanding of an opportunity are acquired incrementally by means of design and evaluation of alternative solutions. This paper develops a use case of BioBeats Ltd., a UK-based university spin-off which has successfully managed to turn an opportunity in digital health into a commercially viable enterprise. Adopting a design-based paradigm, the company under study started by building a technical solution informed by a set of design principles which subsequently allowed the company to convert the socio-technical nature of the opportunity into technological artefacts that were further refined and tested by means of real-world experiments with third parties and citizens.Engineering and Physical Sciences Research Council (EPSRC

ComeHere: Exploiting ethereum for secure sharing of health-care data

The problem of protecting sensitive data like medical records, and enabling the access only to authorized entities is currently a challenge. Current solutions often require trusting some centralized entity which is in charge of managing the data. The disruptive technology of blockchains may offer the possibility to change the current scenario and give to the users the control on their personal data. In this paper we propose ComeHere, a system able to store medical records and to exploit the blockchain technology to control and track the access right transfer on the blockchain. The paper shows the current status of the project, presents a preliminary proof-of-concept implementation and discusses the future improvements of the system, and some critical issues which are still open.Engineering and Physical Sciences Research Council (EPSRC)BioBeats Group Lt

The association between work-related rumination and heart rate variability: A field study

This is the final version. Available on open access from Frontiers Media via the DOI in this recordThe objective of this study was to examine the association between perseverative cognition in the form of work-related rumination, and heart rate variability (HRV). We tested the hypothesis that high ruminators would show lower vagally mediated HRV relative to low ruminators during their leisure time. Individuals were classified as being low (n = 17) or high ruminators (n = 19), using the affective scale on the work-related rumination measure. HRV was assessed using a wrist sensor band (Microsoft Band 2). HRV was sampled between 8 pm and 10 pm over three workday evenings (Monday to Wednesday) while individuals carried out their normal evening routines. Compared to the low ruminators, high affective ruminators demonstrated lower HRV in the form of root mean square successive differences (RMSSDs), relative to the low ruminators, indicating lower parasympathetic activity. There was no significant difference in heart rate, or activity levels between the two groups during the recording periods. The current findings of this study may have implications for the design and delivery of interventions to help individuals unwind post work and to manage stress more effectively. Limitations and implications for future research are discussed

A spatially-structured PCG method for content diversity in a Physics-based simulation game

This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of di ferent levels of di ficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n- body problem, a classical problem in the fi eld of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the di ficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e:, intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with di ferent di ficulty in Gravityvolve!.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Deep learning with wearable based heart rate variability for prediction of mental and general health

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordData Availability: The data collected in this study resides in a secure network and access to data for further analysis would require further ethics approval due to the data containing sensitive participant information, but may be available upon request.The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of personal healthcare data, but with limited analytics typically fed back to the user. The feasibility of feeding back more complex, seemingly unrelated measures to users was investigated, by assessing whether increased levels of stress, anxiety and depression (factors known to affect cardiac function) and general health measures could be accurately predicted using heart rate variability (HRV) data from wrist wearables alone. Levels of stress, anxiety, depression and general health were evaluated from subjective questionnaires completed on a weekly or twice-weekly basis by 652 participants. These scores were then converted into binary levels (either above or below a set threshold) for each health measure and used as tags to train Deep Neural Networks (LSTMs) to classify each health measure using HRV data alone. Three data input types were investigated: time domain, frequency domain and typical HRV measures. For mental health measures, classification accuracies of up to 83% and 73% were achieved, with five and two minute HRV data streams respectively, showing improved predictive capability and potential future wearable use for tracking stress and well-being.Engineering and Physical Sciences Research Council (EPSRC

I feel it in my finger: Measurement device affects cardiac interoceptive accuracy

This is the final version. Available on open access from Elsevier via the DOI in this recordIn recent years, measures of cardiac interoceptive accuracy have been heavily scrutinised. The focus has been on potentially confounding physiological and psychological factors; little research has examined whether the device used to record objective heartbeats may influence cardiac interoceptive accuracy. The present studies assessed whether the device employed influences heartbeat counting (HCT) accuracy and the location from which heartbeats are perceived. In Study One, participants completed the HCT using a hard-clip finger pulse oximeter, electrocardiogram (ECG) and a smartphone application. In Study Two, an ECG, hard-clip and soft-clip oximeter were compared. Moderate-strong correlations were observed across devices, however, mean HCT accuracy and confidence varied as a function of device. Increased sensation in the finger when using a hard-clip pulse oximeter was related to increased accuracy relative to ECG. Results suggest that the device employed can influence HCT performance, and argue against comparing, or combining, scores obtained using different devices.Economic and Social Research Council (ESRC)Baily Thomas TrustFonds de Recherche Québec – Sant

Efficacy of the Digital Therapeutic Mobile App "BioBase" to Reduce Stress and Improve Mental Wellbeing Among University Students: a Randomized Controlled Trial.

This is the author accepted manuscript. The final version is available from JMIR Publications via the DOI in this record.BACKGROUND: UK university students are experiencing increasing levels of anxiety. A programme designed to increase awareness of one's present levels of wellbeing and suggest personalized health behaviours may reduce anxiety and improve mental wellbeing in students. The efficacy of a digital version of such a programme, providing biofeedback and therapeutic content based on personalized wellbeing metrics, is reported here. OBJECTIVE: The aim of this study was to test the efficacy and sustained effects of using a mobile app (BioBase) and paired wearable device (BioBeam), compared to a wait-list control group, on anxiety and wellbeing in university students with elevated levels of anxiety and stress. METHODS: The study employed a randomized, wait-list controlled, trial with assessments at baseline, 2-weeks, post-intervention (4 weeks), and at follow-up (6 weeks). Participants were eligible if they were current full-time undergraduate students and (1) at least 18 years of age, (2) scored >14 points on the DASS-21 stress subscale or > 7 points on the DASS-21 anxiety subscale, (3) owned an iOS smartphone, (4) did not have any previous psychiatric or neurological conditions, (6) were not pregnant at the time of testing, and (7) were able to read and understand English. Participants were encouraged to use BioBase daily and complete at least one course of therapeutic content. A p value ≤.05 was considered statistically significant. RESULTS: We found that a 4-weeks intervention with the BioBase programme significantly reduced anxiety and increased perceived wellbeing, with sustained effects at a 2-weeks follow-up. Furthermore, a significant reduction in depression levels was found following 4-weeks usage of Biobase. CONCLUSIONS: This study shows the efficacy of a biofeedback digital intervention in reducing self-reported anxiety and increasing perceived wellbeing in UK university students. Results suggest that digital mental health interventions could constitute a novel approach to treat stress and anxiety in students, which could be combined, or integrated with, existing therapeutic pathways. CLINICALTRIAL: https://osf.io/2w5sy/

Effectiveness of a Smartphone App (BioBase) for Reducing Anxiety and Increasing Mental Well-Being: Pilot Feasibility and Acceptability Study

This is the final version. Available on open access from JMIR Publications via the DOI in this recordBACKGROUND: The prevalence of workplace-related stress and anxiety is high, resulting in stress-related physical and mental illness. Digital self-guided interventions aimed at key areas of workplace design may be able to provide remote anxiolytic effects. OBJECTIVE: The aim of this feasibility study is to assess changes in anxiety and mental wellbeing after use of the BioBase programme, a mobile phone platform for psycho-educational modules, tools and real-time feedback of physiological data. METHODS: A four-week observational study was carried out in 55 healthy adults who were screened for stress with the Depression Anxiety Stress Scales (DASS) Stress subscale. Participants completed anxiety (6-item State-Trait Anxiety Inventory; STAI) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; WEMWBS) questionnaires at baseline and at 4 weeks. Feedback questionnaires were administered after 4 weeks. RESULTS: After 4 weeks of using the programme and controlling for any effect of being paid to take part in the study, STAI significantly decreased (baseline mean= 45.52 ± 13.2, 4-weeks mean: 39.82 ± 11.2, t54 = -3.51, P < 0.001, CI: -8.88 - -2.52, Cohen's d = 0.96) and WEMWBS significantly increased (baseline mean = 48.12 ± 6.4, 4-weeks mean: 50.4 ± 6.9, t53 = 2.41, p = 0.019, CI: 0.44-4.23, Cohen's d = 0.66). Further, higher baseline stress was significantly associated with a greater decrease in STAI (t53 = -3.41, P = 0.001, CI: -8.10- -2.10, R2 = 0.180) and a greater increase in WEMWBS (t52 = 2.41, P = 0.019, CI: 0.38 - 4.11, R2 = 0.101). On feedback, participants found the programme easy to use navigate, with the content being acceptable and relevant to workplace-related stressors. 70% of participants would recommend the programme to a friend. CONCLUSIONS: The BioBase programme is a potentially effective intervention in decreasing anxiety and increasing mental wellbeing, with larger changes in those with higher baseline levels of stress. CLINICALTRIAL