Students at the University of Strathclyde are developing a walking app designed to assist medical patients.
The app, named 6MW-app (Six-Minute Walk), aims to compact and simplify the ways in which physical activity can be monitored while patients are in recovery, offering detailed insights into activities and movements. It is being trialled with cancer patients, but the developers said it could be used for patients with other conditions in the future.
Patients using the innovative app will be able to track and assess their fitness by measuring the distance they have walked in a specific period of time.
As well as monitoring user fitness levels, the developers say the app can also be used as a tool to motivate people to exercise; providing incentives to boost their daily physical activities.
Leading the study is Dr Liane Lewis, a research associate at Strathclyde University’s Department of Computer and Information Sciences.
Lewis said the inspiration behind the app was to simplify and replace current fitness assessment practices.
“We developed the Six-Minute Walk app for self-assessment of fitness using a mobile phone,” Lewis said. “Its simplicity could lead to it replacing current assessment practice and, unlike some other apps for walking, it measures fitness using a well-validated test developed for medical patients.
“Measuring patient’s levels of fitness has many benefits in a clinical environment, such as assessment of pre-surgery fitness, a baseline measure for monitoring progress and facilitation conversation about physical activity.
Lewis suggested that the findings of their research could help enable the development of tools to improve fitness levels in both healthy people and those living with an illness.
Clinicians have already expressed an interest in using the app, she said, with many underlining its potential to be a “motivator for physical activity beyond clinical intervention.”
Although initial tests have involved healthy participants, which involved fitness tests and surveys, the app developers believe the results showcase the reliability of the app thus far and that it will be appropriate for use in an unsupervised environment.