PORTLAND, Ore.—The infamous 1980s television commercial that featured the tag line "I've fallen and I can't get up" became the butt of a thousand jokes. But for the elderly, susceptibility to falls and resulting injuries is no laughing matter.
Now, a development effort at Texas Tech University, sponsored by Texas Instruments Inc., is taking aim at preventing falls by analyzing posture and gait to send warning alerts to the elderly before they fall. The project has already enlisted volunteers at Texas Tech's Health Science Center to perfect the wireless wearable sensor and is on track next for clinical trials at the first U.S. on-campus geriatric teaching facility, Texas Tech's Geriatric Education and Care Center.
"We have tried all sorts of sensor placements, from leg-mounted inertial sensors to slippers with pressure sensors in their soles, but Texas Instruments' low-power microcontrollers and wireless radio combined with a torso-mounted MEMS accelerometer and gyro—like an external pacemaker—gives the best results," said lead scientist on the project, Texas Tech EE professor Donald Lie.
After a three-year development effort, Lie's team has crafted not only the torso-mounted wireless sensor but also the software analytics running on a PC that wirelessly monitors patients, resulting in algorithms that can reliably detect falls regardless of in which direction, which Lie claims is difficult to differentiate from the many ways that people plop down into their beds, cars seats and the various pieces of furniture around the home.
Prototype of wireless sensor module for detecting falls in geriatric patients is small enough to clip on a belt.
Photo courtesy of Texas Tech
Next, the team is honing its software analytics even finer to detect pre-fall conditions in order to take preventative measures by virtue of clinical trials on real patients at the local Geriatric Education and Care Center where they have already installed the necessary wireless infrastructure.
The MEMS sensor and wireless radio module is clipped on the belt, or for women not wearing a belt on the back of their bra, and contains a MEMS accelerometer, MEMS gyroscope, TI's MSP430 microcontroller and CC2500 radio frequency (RF) transceiver and uses the ultra-low-power SimpliciTI network protocol running a proprietary software stack developed on TI's ez430-RF2500 development platform.
"We became interested in this project at Texas Tech, because it went beyond just fall detection, but aspired to preventative measures," said TI Fellow Allen Bowling. "By analyzing the dynamics of posture and gait--the way people are standing or walking before a fall—we hope to be able to send an alarm instructing them to grab hold of something or sit down before they fall."
If the patient does end up falling, an alarm is sent wirelessly to a care provider, but the goal is to code the analytics—which today runs on a clinician-monitored PC—for the MSP430 microcontroller so alarms can be issued to patients regardless of whether they are in range of a wireless router or not.
The team also has its sights on monitoring other vestibular (balance related) disorders and diseases including Parkinson's, dementia and epilepsy, in hopes of issuing warnings to those patients of impending episodes thereby enabling them to take preventative measures.
"We believe that these projects will really make a significant difference in the clinical care of geriatric populations," said Lie, who credits his team of collaborators, including doctors Tam Nguyen, Steven Zupancic, Andrew Dentino, Ron Banister, and Tim Dallas.
They are trying to profile what happens just before a fall--not during it. When a physical therapist observes an elderly person getting "wobbly" they will often say to them "stop, and grab onto something or sit down." By using software analytics to recognize this "wobbly" situation, they hope to use an alarm of even a voice synthesizer to fill-in for the human physical therapist.
The technology for using accelerometers to safely park a hard drive head before it hits the floor is well established. It would seem that initially the technology could be implemented as an alert to caregivers that a fall has happened. The more ambitious goal is to determine how alerting the individual can prevent a fall. If someone is dozing off and starting to topple over, a sharp alarm may enable them to catch themselves. The challenge is likely to be that falls have different root causes - which require different corrective actions.
Many research efforts have attempted to detect falls, but none has been successful enough for widespread commercialization. TI and Texas Tech, if successful, will not only detect falls, but will actually attempt to prevent them, which I believe everyone with an elderly relate will appreciate.
I am eagerly awaiting for such a device to be available. It is almost everybody experience with their elderly people in the family. I myself have seen my father-in-law who is now 86, suffering from such unexpected falls and the resultant injuries. Especially bathrooms where normally such elderly people are susceptible for such falls are places where the caretaker is unlikely to be around . And especially in homes where 24 hours monitoring of such persons is not possible , such kind of device will really be a boon.