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Image by Corinne Kutz


Near-patient sensing covers the use of a range of technologies that help understand and monitor human behaviour and health in the community. These include a range of devices, apps and modalities, and one of the challenges - and one of our areas of focus - is trying to work out which types of near-patient sensing are best for different groups of patients.

Much of our work has been based on activity monitoring, using wearable accelerometers to track movement and walking in patients over time. We have started to add other modalities, such as speech, balance and photos, to see how these relate to each other.

There are three main elements to our near-patient sensing work:

  1. Which types of sensing, and in which patients, are most useful, and how to interpret the data

  2. Developing an evidence base for the use of near-patient sensing in different patient groups

  3. Collaborating to develop novel hardware and computational approaches for better sensing and interpretation of the data

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