Liu H.1, Salem Y.2, Huang H.3, Nana A.4, Truong T.2, Salas-Nunez L.5, Pena L.2
1University of North Texas Health Science Center, Physical Therapy, Fort Worth, United States, 2University of North Texas Health Science Center, Fort Worth, United States, 3University of Texas at Arlington, Engineering, Arlington, United States, 4University of North Texas Health Science Center, Orthopedics, Fort Worth, United States, 5University of Texas at Arlington, Arlington, United States
Background: In senior living communities, the rolling walker (RW) is the most commonly used ambulatory device. The rate of falling is still high (nearly 40% based on our previous study) in these RW users. This is greatly associated with incorrect RW height (causing difference of grip strength and how holding a RW), inappropriate user's posture (causing difference of pressure/strain on walker/ground), and unalignment between the walker and the walker user in terms of center of gravity and moving speed.
Purpose: This was the phase one study of our RW modification project. This phase was to modify a regular RW by designing, instrumenting, and testing a variety of sensors installed on the RW in order to identify the improper RW use with quantitative data.
Methods: This study was conducted in an engineering lab in a local university with investigators including physical therapists, orthopedic surgeons, and engineers. Torque and pressure sensors were installed on the handgrips and strain gauges were placed on the shaft of each RW leg. Also, one accelerometer was fixed at the middle point of the RW front bar while another one was tightly attached on a belt near the L4 spinous process. Data from these sensors will be acquired by the Data Acquisition Device (DAD) and be wirelessly transmitted to a PC for monitoring the users status of using the walker.
Results: After completion of these sensors and adjustment to avoid sensor interference, five young healthy subjects had participated in trial of this smart walker. It demonstrated these sensors on RW handgrips and legs could provide instant real time data on 1) how a RW user holds on both handgrips: grip force in what angle (wrist flexion, extension, or neutral position); and 2) how a users posture affects the ground-reaction force from the walker, and if and how pressure is distributed on each RW leg during standing and ambulation. Two accelerometers could provide real time data as well showing how and if the RW user is moving properly aligned with the RWs moving in the same speed, particularly when the center of gravity changes during turn-making with the RW. All data collected for each of these subjects in two different days were highly reliable and consistent.
Conclusion(s): Quantitative data from this smart walker are able to monitor how a walker user uses the walker for mobility. Such data would provide quantitative comparison of handgrip between left and right sides, comparison of posture or leaning direction, and comparison of alignment and moving speed of the walker with the walker user.
Implications: This smart walker could be a valuable instrument for real time posture and gait evaluation. Longitudinal periodic quantitative assessment with it would assist clinicians to identify and analyze changes of data in the walker users and then provide appropriate interventions accordingly.
Funding acknowledgements: This study was funded 2014-16 Texas Medical Collaborative Research Fund.
Topic: Health promotion & wellbeing/healthy ageing
Ethics approval: This study was approved by the IRB office of University of North Texas Health Science Center (#2014-151).
All authors, affiliations and abstracts have been published as submitted.
