AFFECT - AI for Long Term Monitoring of Hemiplegic Patients

Purpose and goal:

In this project, a system to measure arm movement in persons suffering from stroke will be developed and tested. Furthermore, algorithms and techniques that uses data from the abovementioned system will be developed and tested to quantify arm usage. The system will be tested by patients in their home environment during the rehabilitation period.

In this way, the rehabilitation process can monitored continuously in a better way. The project will also pave way for a more individualized rehabilitation process through continuous monitoring of arm usage. Expected results and effects:

The project is expected to improve current arm-use assessment approaches and to extract deeper clinically relevant information with a specific target being patients suffering from stroke. The objective is to advance the state-of-the-art arm-use assessment methods using wearable sensors in patients with upper-limb sensorimotor impairments. The results from this project could aid in providing patients more individualized rehabilitation procedures after having suffered sensorimotor impairment.

Approach and implementation:

At the start of the project relevant hardware will be developed. This includes integration of components, pcb manufacturing and verification. After this, relevant data will be collected from healthy volunteers and patients and the data will be annotated by clinicians.

The annotated data will be used for development and validation of AI-algorithms. At a later stage, data will be collected in patients home environment during a longer period of time and the final system and algorithms will be evaluated.