Everion used in activity monitoring of hospitalized patients
PD Dr. Jens Eckstein, CMIO at Basel University Hospital, and his team are driving successfully digitalisation within their organisation and they also have a passion for wearable technology. Not surprising that they decided to deploy the Everion at the University Hospital and use it for their research.
In the trial which has started this month, the team uses the accelerometer of the device for investigating physical activity and movements of patients currently hospitalized on the internal medicine department. Close and objective monitoring of patients physical activity with a multisensor-wearable worn on the upper arm could allow the supervision of recovery and the early detection of changes in physical condition. However, movements of elderly and sick patients tend to differ significantly from the movements of healthy subjects. This makes qualification of physical activity with data from healthy subjects difficult. Patients will wear Everions for 48h straight. During that period they will perform three times a defined and well validated movement protocol (the de Morton Mobility Index). Collected data could allow a hypothesis-generating analysis for follow-up trials. Furthermore, it could help to develop automated physical activity detection algorithms in cooperation with Biovotion, which are reliably applicable on hospitalized patients. Based on those insights, physio therapy resources could be planned more efficiently for patients in need of mobilization. Higher activity levels often lead to quicker resumption of daily routines once discharged.
We are looking forward to the study results and further cooperation with the team!
In case you would like to learn more about PD Dr. Eckstein's activity, he will be speaking at the ESC congress in Munich. Visit the e-Cardiology and Digital Health session on Monday, the 27th of August 2018.
This is just one example of many innovative research projects where Everion is being used. With its 22 parameters and features measured every second it is the ideal platform to develop meaningful algorithms in a number of use cases in the healthcare and safety critical space.