Limbprove: a tool for remote monitoring and rehabilitation of finger function

Our innovative technology (called Limbprove) provides a solution for daily monitoring and assessment of patients with functional neurological disorder. Some health conditions such as stroke may damage areas of the brain associated with certain functions such as hand/finger movement. With therapy however, healthy parts of the brain eventually take over those functions and the abilities can be restored. Unfortunately, this rehabilitation is often a slow, gradual journey involving small daily routines of repetitive finger exercises. This is typically performed outside healthcare settings which makes it difficult to monitor and track patients’ progress.

Limbprove provides a remote tracking and rehabilitation solution that leverages the patient’s unique digital behaviour on the keyboard, mouse and/or touchscreen. First, standardised therapies (e.g., finger exercises) are replicated on a web-based application using key combinations on a standard computer keyboard and/or traceable paths displayed on screen. Then, we capture patients’ behaviour whilst undertaking the exercises such as key press intensity; typing speed (or flight time between key press); mouse and touchscreen trajectory are captured. The behaviour data is analysed programmatically to model a progressive track record of patients, that is remotely accessible to clinicians (e.g., physiotherapists) via a dashboard. Limbprove will also employ advanced data modelling techniques (commonly called Machine Learning) to determine personalised goals for each patient based on prior knowledge from similar patients.

Our approach has strong foundational character and is very likely to be a disruptive technological solution in digital health rehabilitation. This is because existing tools used for hand/finger neuro-function rehabilitation are intrusive and expensive (e.g., wearable devices with sensors); whereas, Limbprove requires minimal installation, and builds on data collected seamlessly from a patient’s interaction with their personal computer or tablet.

This project received £8K from Innovate UK