Low power biomedical actuator

IMEC has developed an actuator that runs on ultra-low power and that is watertight which makes it suitable for use in in-vivo biomedical applications

The new actuator is fabricated using SOI-based (silicon-on-insulator) micromachining. The actuator combines a large range (±50µm) with sufficient force (±195µN) to position for example in-vivo brain electrodes. It works at 11V, which is three times lower than the operating voltages of the current available actuators. Moreover, the actuator consumes below 100nW and can therefore be used in applications that require a long battery life. IMEC has integrated the actuator with a micro-needle in a watertight encapsulation that does not hinder the movement of actuator and needle. The package includes a flip-chip mounted glass cap and hydrophobic surface treatment to prevent water ingress.

A micro-actuator is a MEMS-device (micro-electromechanical system) that converts energy into micro-movements, allowing it to position or control elements with a high precision, and with steps of a few micrometers or even nanometers. IMEC’s actuator is an electrostatic inchworm actuator, having six arms that selectively latch, unlatch, and drive.

Today, micro-actuators are already used in medical applications where biological objects or their environment need to be controlled at the microscopic scale. Examples are micro-manipulators, micro-surgery tools, micro-pumps, and micro-needles. One particular biomedical application of micro-actuators is to integrate them with microprobes for brain applications.

Actuators for brain implants are already used during brain research; but they are placed outside the body. IMEC’s inchworm actuator combines small size with water tightness and a long autonomy, enabling implantation and thus long-term patient treatment. The actuator could be used to accurately control the position of micro-needles used in brain applications. This is necessary to reach the correct groups of neurons for the specific disorder and to get near the neurons for a better signal to noise ratio.

Recent articles

Info Message

Our sites use cookies to support some functionality, and to collect anonymous user data.

Learn more about IET cookies and how to control them

Close