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Biomed Sci Instrum. 2012;48:407-14.

A comparative study for performance evaluation of sit-to-stand task with body worn sensor and existing laboratory methods.

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  • 1Virginia Tech.

Abstract

uman movement such as sit-to-stand (STS) is one of the most fundamental and essential movement among daily living activities. Elderly who are unable to stand are severely limited in daily activities and rely on others for their care. In the coming next two decades about 20% of US population will be above the age of 65 years, and considering ever-increasing elderly population and health care expenses, the rehabilitation of functionally limited elderly is becoming a topic of greater concern. Clinically STS movement is looked upon with great interest, such as its analysis is meaningful in order to evaluate motor control and stability in elderly patients with functional limitations and may be more helpful than traditional medical evaluations in diagnosing and treating mobility problems in elderly. A few previous research studies describe controlled STS movements with constrains in laboratory environments and have established STS standardized events. A comparative study is presented in this work using and inertial measurement unit (IMU) and existing laboratory based sit-to-stand phases and events. The aims of this study are (1) to define phases and identify events of STS movement based on those previously described, using wireless IMU (2) to test the consistency of these events and phases in total of seven young healthy subjects (ages 25-35 years). We found significant differences in peak flexion angular velocities (p<0.001), peak extension angular velocities (p<0.01) and accelerations at seat-off (p<0.01) between participants when using chair arm rest versus knee as support during rising. Also, we have found significant differences in time events for pre seat off flexion decelerations and post seat off extension angular accelerations with the two different rising supports. Thus these distinct and consistent phases of STS movement using IMU can help identify individuals at fall risk in non-laboratory environments.

PMID:
22846313
[PubMed - in process]
PMCID:
PMC3716258
Free PMC Article
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