Motion-sensing technology found in devices like Microsoft's Xbox 360 are effective at detecting the early onset of illness and fall risk in seniors, according to research from the University of Missouri.

In one study, researchers used Microsoft Kinect, the Xbox 360's motion-sensing camera, to monitor behavior and routine changes in patients at TigerPlace, an independent living community located in Columbia, Mo.

In a second study, a fall detection system used Doppler radar to recognize changes in walking, bending, and other body movements that may signal a heightened risk for falls.

"Different human body parts create unique images, or 'signatures,' on Doppler radar. Since falls combine a series of body part motions, the radar system can recognize a fall based on its distinct 'signature,'" researchers said in a statement.

Marjorie Skubic, professor of electrical and computer engineering at the University of Missouri-Columbia college of engineering, and one of the researchers involved with the Microsoft Kinect project, told InformationWeek Healthcare that researchers' approaches to these monitoring systems has been to look for sensor patterns that mirror activity behavior and health conditions.

"Changes in the sensor patterns can then be used to detect early signs of illness and functional decline," Skubic said. "The gait analysis provides a method to assess fall risk, which is one indicator of health changes. Early detection of health changes facilitates early interventions, which keeps people healthier."

Both motion-sensing systems provide information to detect walking and other activities. Computer networks and wireless technology are used to send automated data to alert clinicians when patients need assistance or medical intervention.

Since many older adults receive a gait analysis and fall risk assessment only once a year, or sometimes not at all, researchers said their goal is to provide a continuous assessment in the home every day so that very early changes can be detected. These might be in the form of walking speed changes or asymmetry in the gait pattern such as limping, variations in step length, or variability in stride-to-stride parameters.

"We have shown in the lab that these parameters can be measured with the webcam system (using silhouettes) and have now begun to capture this type of data in the home," Skubic said. "In this current study, we are also investigating the use of radar and the Kinect for capturing in-home gait parameters."

"The radar and Kinect systems are not currently connected to the [electronic health record], but I would envision them becoming part of that," Skubic said. "We have been logging motion and bed sensor data in TigerPlace apartments for almost 6 years and are now linking up the sensor data with the EHR at TigerPlace."

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