Machine Intelligence for the Essential Self
At BioBeats, we're working on projects with AXA, Microsoft and BUPA that help people be well, fight stress, and be more productive. In most of these projects, deep learning approaches are taken to train models that can classify, predict and illuminate behaviour from the person's body and actions. Most of our classifiers learn from smartphone sensors, but increasingly our algorithms ingest from wearable sensors such as the Microsoft Band, Apple Watch, and upcoming projects from Google and Samsung. Our approach to building machine-learning-driven applications learns from evidence-based psychosocial intervention practices in mental health, but embodies continuous cardiovascular, skin, and movement-based sensor data in order to arrive at profound but granular insight for the individual, and their care or employer circle.
Dr David Plans is a member of the University of Surrey’s Center for Digital Economy and Center for Vision, Speech and Signal Processing, and is working towards machine learning solutions to foster human wellbeing. His primary research focus is adaptive media and affective modelling. Having worked on early mHealth projects in the NHS, he is now leading smartphone and wearable research projects at BUPA, AXA/PPP, and Microsoft Health with his startup, BioBeats, where they are helping actuarial and care provision teams think differently about preventative health.