Faux-floor development system for personnel detection using signal scavenging sensors.

Motivated by the need to detect motion in elderly people, resulting in falls, we have developed a low cost sensor system using aluminum foil as the sensor of static electricity and electromagnetic energy. But to make this a system we need to amplify the data and use it by displaying the motion or activity of a person. We constructed a faux floor development board to provide an initial pilot test of the idea of using stray electric energy, or as we call it signal scavenging. The foils are placed on the faux floor (in this case a 1 m X 1 m wooden surface) allowing foil excitation from the motion of a test subject. The faux floor is a useful tool allowing testing of different foils, analog and digital electronics circuits and different carpeting. Importantly, even though the system supported a small number of foil sensors its performance characteristics clearly show the excellent detection capability of the system. Testing the timing characteristics resulted in reading the 4 sensors in 3.11 msec, indicating that for even a large system of a few hundred sensors we can poll the foils in sufficient time to detect the motion of people. Our data show true positive rates of 98% and false positive and false negative rates of 2%, a high detection rate. Using the development board has provided much helpful information on the use of signal scavenging for personnel detection.

Smart Carpet: Developing a sensor system to detect falls and summon assistance.

Cognitive deficits experienced by older adults with dementia limit use of wearable devices (necklaces or bracelets) that summon assistance after the older adult falls. To use these wearable devices, older adults must choose to wear them, remember how to use them, and be conscious after falling. Devices such as the Smart Carpet substitute pre-programmed or automatic functions for functions requiring deliberation and decision. After development of a Smart Carpet prototype, 11 volunteers participated in tests to measure sensitivity of sensors embedded in the Smart Carpet. The embedded sensors were not perceptible to the volunteers as they walked across the Smart Carpet and successfully detected gait characteristics. Findings confirmed the feasibility of fall detection. Measurements obtained of gait characteristics will be used in development of more advanced versions of the Smart Carpet.