Literature DB >> 22698978

Validation of an accelerometer-based method to measure the use of manual wheelchairs.

Sharon Eve Sonenblum1, Stephen Sprigle, Jayme Caspall, Ricardo Lopez.   

Abstract

The goal of this project was to develop and validate a methodology for measuring manual wheelchair movement. The ability to study wheelchair movement is necessary across a number of clinical and research topics in rehabilitation, including the outcomes of rehabilitation interventions, the long-term effects of wheelchair propulsion on shoulder health, and improved wheelchair prescription and design. This study used a wheel-mounted accelerometer to continuously measure distance wheeled, and to continuously determine if the wheelchair is moving. Validation of the system and algorithm was tested across typical mobility-related activities of daily living, which included short slow movements with frequent starts, stops, and turns, and straight, steady state propulsion. Accuracy was found to be greater than 90% across wheelchair and wheel types (spoke and mag), propulsion techniques (manual and foot), speeds, and everyday mobility-related activities of daily living. Although a number of approaches for wheelchair monitoring are currently present in the literature, many are limited in the data they provide. The methodology presented in this paper can be applied to a variety of commercially available products that record bi-axial accelerations, and used to answer many research questions in wheeled mobility.
Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Mesh:

Year:  2012        PMID: 22698978     DOI: 10.1016/j.medengphy.2012.05.009

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  20 in total

1.  Development and evaluation of a gyroscope-based wheel rotation monitor for manual wheelchair users.

Authors:  Shivayogi V Hiremath; Dan Ding; Rory A Cooper
Journal:  J Spinal Cord Med       Date:  2013-07       Impact factor: 1.985

2.  Measurement of self-propulsion distance of wheelchair using cycle computer excluding assistance distance by touch switch: A pilot study.

Authors:  Shunsuke Ohji; Yosuke Kimura; Yuhei Otobe; Naohito Nishio; Daisuke Ito; Ryota Taguchi; Hideyuki Ogawa; Minoru Yamada
Journal:  J Spinal Cord Med       Date:  2019-04-11       Impact factor: 1.985

Review 3.  Data logger technologies for manual wheelchairs: A scoping review.

Authors:  François Routhier; Josiane Lettre; William C Miller; Jaimie F Borisoff; Kate Keetch; Ian M Mitchell; CanWheel Research Team
Journal:  Assist Technol       Date:  2017-01-04

4.  Measuring Physical Activity in Spinal Cord Injury Using Wrist-Worn Accelerometers.

Authors:  Susan L Murphy; Anna L Kratz; Aaron J Zynda
Journal:  Am J Occup Ther       Date:  2019 Jan/Feb

5.  A novel mobile-cloud system for capturing and analyzing wheelchair maneuvering data: A pilot study.

Authors:  Jicheng Fu; Maria Jones; Tao Liu; Wei Hao; Yuqing Yan; Gang Qian; Yih-Kuen Jan
Journal:  Assist Technol       Date:  2016

6.  Wheeled-mobility correlates of life-space and social participation in adult manual wheelchair users aged 50 and older.

Authors:  Brodie M Sakakibara; François Routhier; William C Miller
Journal:  Disabil Rehabil Assist Technol       Date:  2016-07-04

7.  Characterization of wheelchair maneuvers based on noisy inertial sensor data: a preliminary study.

Authors:  Jicheng Fu; Tao Liu; Maria Jones; Gang Qian; Yih-Kuen Jan
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

8.  Outcome Measures of Free-Living Activity in Spinal Cord Injury Rehabilitation.

Authors:  Brianna M Goodwin; Emma Fortune; Meegan G P Van Straaten; Melissa M B Morrow
Journal:  Curr Phys Med Rehabil Rep       Date:  2019-05-28

9.  Estimation of manual wheelchair-based activities in the free-living environment using a neural network model with inertial body-worn sensors.

Authors:  Emma Fortune; Beth A Cloud-Biebl; Stefan I Madansingh; Che G Ngufor; Meegan G Van Straaten; Brianna M Goodwin; Dennis H Murphree; Kristin D Zhao; Melissa M Morrow
Journal:  J Electromyogr Kinesiol       Date:  2019-07-17       Impact factor: 2.368

10.  Sudden stop detection and automatic seating support with neural stimulation during manual wheelchair propulsion.

Authors:  Kevin M Foglyano; Lisa M Lombardo; John R Schnellenberger; Ronald J Triolo
Journal:  J Spinal Cord Med       Date:  2020-08-14       Impact factor: 1.985

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