David Plans

Senior Lecturer

David Plans initially studied artificial intelligence and media, using evolutionary algorithms to investigate the nature of human improvisation. He helped build the first European merger for Open Source startups and worked within the UK’s National Health Service to deploy the first mobile application to let users self-report in chronic illness. He has given papers and talks at the European Conference on Artificial Life, IRCAM, the Darwin Symposium, and the Computer Arts Society in London.

His first PhD focused on genetic algorithms for classification of human musical behaviour in MPEG7 time series. He then led BioBeats as CEO, a startup that focuses on machine learning models of mental health and disorder. He is a member of the INDEX group and a Senior Lecturer in Organisational Neuroscience at the University of Exeter, and is a Fellow of the Alan Turing Institute.



Journal articles

Hemmings NR, Kawadler JM, Whatmough R, Ponzo S, Rossi A, Morelli D, Bird G, Plans D (2021). Development and Feasibility of a Digital Acceptance and Commitment Therapy-Based Intervention for Generalized Anxiety Disorder: Pilot Acceptability Study. JMIR Form Res, 5(2)  Abstract.  Author URL. DOI.
Clift AK, Le Lannou E, Tighe CP, Shah SS, Beatty M, Hyvärinen A, Lane SJ, Strauss T, Dunn DD, Lu J, et al (2021). Development and Validation of Risk Scores for All-Cause Mortality for a Smartphone-Based "General Health Score" App: Prospective Cohort Study Using the UK Biobank. JMIR Mhealth Uhealth, 9(2)  Abstract.  Author URL. DOI.
Coutts LV, Plans D, Brown AW, Collomosse J (2020). Deep learning with wearable based heart rate variability for prediction of mental and general health. Journal of Biomedical Informatics, 112, 103610-103610. Full text. DOI.
Kawadler JM, Hemmings NR, Ponzo S, Morelli D, Bird G, Plans D (2020). Effectiveness of a Smartphone App (BioBase) for Reducing Anxiety and Increasing Mental Well-Being: Pilot Feasibility and Acceptability Study. JMIR Form Res, 4(11)  Abstract.  Author URL.  Full text. DOI.
Ponzo S, Morelli D, Kawadler JM, Hemmings NR, Bird G, Plans D (2020). Efficacy of the Digital Therapeutic Mobile App BioBase to Reduce Stress and Improve Mental Well-Being Among University Students: Randomized Controlled Trial. JMIR Mhealth Uhealth, 8(4)  Abstract.  Author URL.  Full text. DOI.
Chelidoni O, Plans D, Ponzo S, Morelli D, Cropley M (2020). Exploring the effects of a brief biofeedback breathing session delivered through the biobase app in facilitating employee stress recovery: Randomized experimental study. JMIR mHealth and uHealth, 8(10)  Abstract. DOI.
Murphy J, Brewer R, Coll M-P, Plans D, Hall M, Shiu SS, Catmur C, Bird G (2019). I feel it in my finger: Measurement device affects cardiac interoceptive accuracy. Biol Psychol, 148  Abstract.  Author URL.  Full text. DOI.
Murphy J, Brewer R, Plans D, Khalsa S, Catmur C, Bird G (2019). Testing the independence of self-reported interoceptive accuracy and attention. Quarterly Journal of Experimental Psychology Full text. DOI.
Plans D, Morelli D, Sütterlin S, Ollis L, Derbyshire G, Cropley M (2019). Use of a Biofeedback Breathing App to Augment Poststress Physiological Recovery: Randomized Pilot Study. JMIR Form Res, 3(1)  Abstract.  Author URL. DOI.
Inceoglu I, Thomas G, Chu C, Plans D, Gerbasi A (2018). Leadership behavior and employee well-being: an integrated review and a future research agenda. Leadership Quarterly Full text. DOI.
Morelli D, Bartoloni L, Colombo M, Plans D, Clifton DA (2018). Profiling the propagation of error from PPG to HRV features in a wearable physiological-monitoring device. Healthcare Technology Letters, 5(2), 59-64.  Abstract.  Full text. DOI.
Bacciu D, Colombo M, Morelli D, Plans D (2018). Randomized neural networks for preference learning with physiological data. Neurocomputing, 298, 9-20. DOI.
Cropley M, Plans D, Morelli D, Sütterlin S, Inceoglu I, Thomas G, Chu C (2017). The Association between Work-Related Rumination and Heart Rate Variability: a Field Study. Frontiers in Human Neuroscience, 11  Abstract.  Full text. DOI.
Plans D, Morelli D (2012). Experience-driven procedural music generation for games. IEEE Transactions on Computational Intelligence and AI in Games, 4(3), 192-198.  Abstract. DOI.


Franceschi M, Morelli D, Plans D, Brown A, Collomosse J, Coutts L, Ricci L (2019). ComeHere: Exploiting ethereum for secure sharing of health-care data.  Abstract.  Full text. DOI.
Bacciu D, Colombo M, Morelli D, Plans D (2017). ELM preference learning for physiological data.  Abstract.
Font F, Brookes T, Fazekas G, Guerber M, La Burthe A, Plans D, Plumbley MD, Shaashua M, Wang W, Serra X, et al (2016). Audio commons: Bringing Creative commons audio content to the creative industries.  Abstract.
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