I’ve written a few times about the growing number of health apps and technologies that attempt to coach and cajole us into living a healthier lifestyle, whether that’s the Vida health coach or the eGym connected personal trainer.

Such services typify the ability of health technologies to both monitor what we’re doing, and then use smart algorithms to suggest improvements to our lifestyle.

Understanding the user

Key to the success of such projects is accurately understanding the intentions and purpose of the user so that they can then be coached in the right way.  It’s a task that a Swedish team have tackled head on via a new model that utilizes activity-centric and argument-based methods.

The aim of the model was to better take account of the rather less tangible and explicit factors that go into improving health, such as our motivations and issues around social inclusion.  The developers believe that when these factors are included, very different methods are required to accurately coach us towards better health.

The model incorporates theories of human activity and reasoning to try and generate different ways of interpreting a situation.  What’s more, the model makes it easy for the situation to be reassessed on the fly as new information comes in so that users can participate in the improvement of the model.

It has been built into a number of e-health apps that have been subsequently tested on older adults to evaluate capacity and performance in a range of exercises designed to gauge strength and balance.  The team believe the approach could have a number of applications.

“The methods could be used in for instance “smart homes”, for example diagnosis and treatment apps that the person can use at home, or an app measuring and evaluating balance and strength for preventing falls in older adults”, they say.