Evidence and theory indicate that laboratory measures of impairment and function do not predict how older adults actually function in daily life. Thomas Glass (1998), for example, reports marked differences between functional activities that community residents """"""""can do"""""""" and """"""""do do"""""""" in survey data from the MacArthur Studies of Successful Aging. Therefore, substantial effort has been spent on developing measures of function in daily life. Most of the new instruments, however, rely on self-report. The PI's research group and others have employed accelerometers, sensors that detect movement, to objectively measure the amount of upper- extremity activity in the community among brain injury survivors. The PI has shown that his group's measure is correlated with self-reported more-impaired arm use in daily life after brain injury, and is a reliable and valid index of rehabilitation outcome. Like other accelerometer measures, however, it can not discriminate whether a given arm movement is functional or non-functional and can not identify what tasks were performed. We propose to develop a measure of upper-extremity activity using radio frequency identification (RFID) tags paired with movement and proximity sensors. Active RFID tags are small and inexpensive (<$25) enough to be affixed to everyday objects, and can send radio signals indicating changes in object status to a central receiver. An acceleration sensor will be used to trigger the RFID tag when a tagged object is moved. A low radio frequency proximity sensor will be developed to trigger the RFID tag when the arm of interest is the one moving the tagged object. Software will be developed to track which objects are manipulated (movement sensor with unique tag ID for each object), when they are manipulated (time stamp on each trigger event), whether they are manipulated by the person and arm of interest (radio proximity sensor), and for how long they are manipulated (time for which the proximity sensor stays """"""""ON""""""""). Thus, the proposed system might permit collection of much richer objective data than possible now. In this initial, 6-month project, we will conduct benchmark testing to evaluate its limits and a laboratory study with healthy individuals (N = 26) using selected everyday objects to evaluate its reliability and validity on preliminary basis. An initial application would be determining the effect of upper-extremity rehabilitation on amount and type of functional activity performed with the more-impaired arm in the home setting by tagging a random sample of commonly used objects in the patients'homes before and after therapy. The proposed approach, however, has much wider application. For example, RFID tags could be affixed to exercise objects to monitor compliance with home exercise programs. In conjunction with a PC-based virtual therapist in the home, an RFID system could be used to reinforce functional activity in the home setting in real time, and thereby help transfer gains made in the clinical setting to the real world. Because RFID tags are already in widespread commercial use, an important factor in considering possible applications is that their cost is likely to fall sharply.

Public Health Relevance

The goal of this project is to develop and test a network of wireless sensors for measuring how long and for what activities stroke and other brain injury survivors use their impaired arm at home. If successful, this tool will permit rehabilitation researchers and clinicians to more accurately measure the effects of arm rehabilitation therapy on how patients function in their daily life, ultimately leading to more effective treatments. When paired with virtual therapist software running on a laptop in patients'home, this tool, in addition, might be incorporated into existing therapies to directly reinforce everyday use of the impaired arm.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
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Special Emphasis Panel (ZRG1-MOSS-F (15))
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Quatrano, Louis A
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Active Wave, Inc.
Boca Raton
United States
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Sokal, Brad; Uswatte, Gitendra; Barman, Joydip et al. (2014) Network of movement and proximity sensors for monitoring upper-extremity motor activity after stroke: proof of principle. Arch Phys Med Rehabil 95:499-505
Barman, Joydip; Uswatte, Gitendra; Ghaffari, Touraj et al. (2012) Sensor-enabled RFID system for monitoring arm activity: reliability and validity. IEEE Trans Neural Syst Rehabil Eng 20:771-7
Barman, Joydip; Uswatte, Gitendra; Sarkar, Nilanjan et al. (2011) Sensor-enabled RFID system for monitoring arm activity in daily life. Conf Proc IEEE Eng Med Biol Soc 2011:5219-23