Concept
In order to enhance rehabilitation of patients whose
extremities are affected by lesions in the central
nervous system (eg. stroke), they should practice
goal-oriented and task-specific tasks repetitively.
However, the repetitive rehabilitation process easily
decreases patients’ motivation and makes it hard to
maintain optimal challenging difficulty and to induce
neuroplasticity.
RAPAEL Smart rehabilitation solution applies the
‘Learning Schedule Algorithm’ to game-like exercises
so that patients can remain motivated and can find
the exercises gradually challenging.
Hence, therapists no longer have to manually adjust
the task’s level of difficulty in order to motivate
patients. Moreover, objective evaluation of exercises
and user-friendly reports on progress allow effective
and efficient rehabilitation process management.
Learning Schgedule Algorithm
EFFECTIVE MOTOR LEARNING & Constant Challenge
Learning Schedule
Learning Schedule Algorithm is designed to enhance
learning multiple functional tasks by proposing an
optimal task in proper challenging difficulty.
Based on patient’s data such as training progress,
prescription, personal interest, motor function scores,
and etc, it computationally selects which game to
play in which level of difficulty. In RAPAEL solution,
a novel UI/UX for task difficulty modulation process
makes patients to understand how exercise
progresses in real-time.
Bending Sensor Technology
Bending Sensor is a variable resistor that changes as it is
bent. The sensor is connected to computer system
which can accurately compute the amount of individual
finger movements. A movement of only one inch can
yield over 200,000 data points.
9 Axis Movement & Position Sensor
– 3 acceleration channels
– 3 angular rate channels
– 3 magnetic field channels