Literature DB >> 22846313

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

Rahul Soangra1, Thurmon E Lockhart.   

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.

Entities:  

Year:  2012        PMID: 22846313      PMCID: PMC3716258     

Source DB:  PubMed          Journal:  Biomed Sci Instrum        ISSN: 0067-8856


  25 in total

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Journal:  Phys Ther       Date:  2002-09

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Journal:  Gait Posture       Date:  2002-08       Impact factor: 2.840

3.  Kinematic and electromyographic analysis of rising from a chair during a "Sit-to-Walk" task in elderly subjects: role of strength.

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4.  Effects of aging on the biomechanics of slips and falls.

Authors:  Thurmon E Lockhart; James L Smith; Jeffrey C Woldstad
Journal:  Hum Factors       Date:  2005       Impact factor: 2.888

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Journal:  Med Sci Sports Exerc       Date:  1990-06       Impact factor: 5.411

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Authors:  F R Goulart; J Valls-Solé
Journal:  Clin Neurophysiol       Date:  1999-09       Impact factor: 3.708

8.  Risk factors for recurrent nonsyncopal falls. A prospective study.

Authors:  M C Nevitt; S R Cummings; S Kidd; D Black
Journal:  JAMA       Date:  1989-05-12       Impact factor: 56.272

9.  Sensitivity of accelerometry to assess balance control during sit-to-stand movement.

Authors:  Wim G M Janssen; Duygu Geler Külcü; Herwin L D Horemans; Henk J Stam; Johannes B J Bussmann
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-10       Impact factor: 3.802

10.  Sit-to-stand performance depends on sensation, speed, balance, and psychological status in addition to strength in older people.

Authors:  Stephen R Lord; Susan M Murray; Kirsten Chapman; Bridget Munro; Anne Tiedemann
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2002-08       Impact factor: 6.053

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  2 in total

1.  Older Adults with Weaker Muscle Strength Stand up from a Sitting Position with More Dynamic Trunk Use.

Authors:  Rob C van Lummel; Jordi Evers; Martijn Niessen; Peter J Beek; Jaap H van Dieën
Journal:  Sensors (Basel)       Date:  2018-04-17       Impact factor: 3.576

2.  Prediction of fall risk among community-dwelling older adults using a wearable system.

Authors:  Thurmon E Lockhart; Rahul Soangra; Hyunsoo Yoon; Teresa Wu; Christopher W Frames; Raven Weaver; Karen A Roberto
Journal:  Sci Rep       Date:  2021-10-25       Impact factor: 4.996

  2 in total

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