Pumps in medical applications require a steady and controllable flow. We designed a medical pump consisting of valves and pistons, but due to the limited length of the pistons and the fluid displacement by the valves, the dynamics of this pump are discontinuous and non-linear.

Critically ill patients who are unable to breathe (sufficiently) on their own receive respiratory support. It is essential that this support is synchronized (in time) with the patient’s spontaneous breaths.

Sorting of food is inherently complex because of the great variation in food and specifically in organic produce. Machine learning is a powerful tool and very fitting to this task.

sEMG measurements can be used to estimate breathing effort by patients under respiratory support and be used to optimize care.