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MEMS pave way for medical innovation

Posted: 22 Oct 2012 ?? ?Print Version ?Bookmark and Share

Keywords:microelectromechanical systems? Sensor fusion? Kalman filtering?

The ability to detect, capture and analyze motion with microelectromechanical systems (MEMS) has become an ordinary feature on consumer and mobile devices. Where technological advances have provided high-precision motion capture, applications have extended into industrial fields. Many potential medical diagnostic and instrumentation applications can benefit from merging the precision of industrial devices with the mobility and economies of consumer devices.

In some cases, the complexity of medical motion capture rivals that of high-end military systems. For instance, precision navigation, typically associated with applications developed for land, air, and sea vehicles, is increasingly being used in medical applications ranging from surgical instrumentation to robotics. Also, while the design requirements of a surgical navigation system share broad similarities with traditional vehicle navigation, there are distinct new challenges posed by the environment and the level of required performance.

This article first introduces some of the fundamentals of MEMS motion sensing, including key understandings needed for component selection. It also looks at the unique challenges of medical navigation applications, and explores possible solutions ranging from various sensor mechanisms, to necessary sensor processing, to the unique system characteristics and data processing required to provide optimal solutions. Critical sensor specifications will be reviewed and explained for their individual contributions and, more importantly, the potential error and drift mechanisms will be discussed to aid in sensor selection. Opportunities and approaches for sensor enhancement through integration, sensor fusion, and sensor processing (such as Kalman filtering) will be highlighted as well.

Innovation in healthcare
Silicon-based accelerometer and gyroscope sensors known as MEMS are commonly found today in a wide range of devices. These inertial sensors detect and measure motion, with minimal power and size, and are valuable to nearly any application where movement is involved, and even those where lack of motion is critical. Later, more advanced applications where combinations of motion, in complex scenarios that present additional challenges, will be discussed.

Capturing motion
Many medical applications such as accurately determining position and repetition rate in CPR, or the precise positioning of scanning equipment in relation to a patient's body, can benefit from relatively basic, yet still precise, motion information. In these cases, a single sensor type may be adequate, particularly if there are other sensor inputs, or at least fixed/known boundaries to the movement and use case.

Even with limited range of motion, or simpler motion dynamics, the individual sensors must have well understood and controlled drift factors, and it is often desirable to have embedded compensation within the sensor, as well as the ability to tune it to the application via embedded filtering.

Complex motion requires precision sensors
While simple motion detection, linear movement along one axis, for example, is valuable to a number of applications, such as detecting whether an elderly person has fallen, a majority of applications involve multiple types and multiple axes of motion. Being able to capture this complex, multidimensional motion can enable new benefits while maintaining accuracy in the most critical of environments.

In many cases, it is necessary to combine multiple sensor typeslinear and rotational, for instancein order to precisely determine the motion an object has experienced. As an example, accelerometers are sensitive to the Earth's gravity, so they can be used to determine inclination angle. As a MEMS accelerometer is rotated through a 1-g field, (90?), it is able to translate that motion into an angle representation. However, the accelerometer cannot distinguish static acceleration (gravity) from dynamic acceleration. In the later case, an accelerometer can be combined with a gyroscope, and post-processing of both devices can discern the linear acceleration from the tilt, based upon known motion dynamics models. This process of sensor fusion obviously becomes more complex as the system dynamics (number of axes of motion, types, and degrees of freedom of motion) increase.

It is also important to understand the environmental influences on sensor accuracy. Temperature is obviously a key concern, and can typically be corrected for; in fact higher precision pre-calibrated sensors will dynamically compensate themselves. A less obvious factor to consider is the potential for even slight vibrations to produce accuracy shifts in rotational rate sensors. These effects, known as linear acceleration and vibration rectification, can be significant depending on the quality of the gyroscope. Sensor fusion improves performance by using an accelerometer to detect linear acceleration and compensate for the gyroscope's linear acceleration sensitivity.

For many applications, particularly those requiring performance beyond basic pointing (up, down, left, right) or simple movement (in motion, or stationary), multiple degrees-of-freedom motion detection is required. For example, a six degree-of-freedom inertial sensor has the ability to detect linear acceleration on each of three (x, y, z) axes, and rotational movement on the same three axis, also referred to as roll, pitch, and yaw (figure 1).

Figure 1: Linear x, y and z motion, plus rotational roll, pitch and yaw make up the six degrees of motion measurement required for full motion assessment; often augmented by both magnetometers and a barometer.

Basic navigation principles
The use of inertial sensors as a navigation aid has become prevalent in industry. Typically, they are used in conjunction with other navigation devices such as GPS. When GPS access is unreliable, inertial guidance fills the gap in coverage with what is called dead-reckoning. Other sensors, including optical and magnetic, may be added depending on the environment and the performance goals. Each sensor type has its own limitations. MEMS inertial sensors provide the potential to fully compensate for these other sensor inaccuracies since they are not affected by the same interferences and do not require external infrastructure: no satellite, magnetic field, or camera is needed...just inertia. The major navigational sensor approaches are outlined in table 1, along with their strengths and potential limitations.

As with the potential for GPS blockage in vehicle navigation, the medical corollary is optical guidance and the potential for line-of-sight blockages. Inertial-based sensors perform dead-reckoning during the optical blockage, as well as enhancing system reliability by providing redundant sensing.

Table 1: Outlined are various navigational sensors widely used in industry, and their applicability to medical navigation.

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