Literature DB >> 25465284

Detection of physical activities using a physical activity monitor system for wheelchair users.

Shivayogi V Hiremath1, Stephen S Intille2, Annmarie Kelleher3, Rory A Cooper4, Dan Ding5.   

Abstract

Availability of physical activity monitors for wheelchair users can potentially assist these individuals to track regular physical activity (PA), which in turn could lead to a healthier and more active lifestyle. Therefore, the aim of this study was to develop and validate algorithms for a physical activity monitoring system (PAMS) to detect wheelchair based activities. The PAMS consists of a gyroscope based wheel rotation monitor (G-WRM) and an accelerometer device (wocket) worn on the upper arm or on the wrist. A total of 45 persons with spinal cord injury took part in the study, which was performed in a structured university-based laboratory environment, a semi-structured environment at the National Veterans Wheelchair Games, and in the participants' home environments. Participants performed at least ten PAs, other than resting, taken from a list of PAs. The classification performance for the best classifiers on the testing dataset for PAMS-Arm (G-WRM and wocket on upper arm) and PAMS-Wrist (G-WRM and wocket on wrist) was 89.26% and 88.47%, respectively. The outcomes of this study indicate that multi-modal information from the PAMS can help detect various types of wheelchair-based activities in structured laboratory, semi-structured organizational, and unstructured home environments.
Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Activity monitor system; Classification; Machine learning; Physical activity; Smartphones; Spinal cord injury; Wheelchair users

Mesh:

Year:  2014        PMID: 25465284     DOI: 10.1016/j.medengphy.2014.10.009

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


  13 in total

1.  Telehealth monitor to measure physical activity and pressure relief maneuver performance in wheelchair users.

Authors:  Ariel V Dowling; Valerie Eberly; Somboon Maneekobkunwong; Sara J Mulroy; Philip S Requejo; Joseph T Gwin
Journal:  Assist Technol       Date:  2016-09-29

2.  Characterisation of rollator use using inertial sensors.

Authors:  Tsu-Jui Cheng; Laurence Kenney; James David Amor; Sibylle Brunhilde Thies; Eleonora Costamagna; Christopher James; Catherine Holloway
Journal:  Healthc Technol Lett       Date:  2016-11-02

3.  Posture Detection Based on Smart Cushion for Wheelchair Users.

Authors:  Congcong Ma; Wenfeng Li; Raffaele Gravina; Giancarlo Fortino
Journal:  Sensors (Basel)       Date:  2017-03-29       Impact factor: 3.576

Review 4.  Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions.

Authors:  Tom E Nightingale; Peter C Rouse; Dylan Thompson; James L J Bilzon
Journal:  Sports Med Open       Date:  2017-03-01

5.  Duration of Static and Dynamic Periods of the Upper Arm During Daily Life of Manual Wheelchair Users and Matched Able-Bodied Participants: A Preliminary Report.

Authors:  Brianna M Goodwin; Omid Jahanian; Stephen M Cain; Meegan G Van Straaten; Emma Fortune; Melissa M Morrow
Journal:  Front Sports Act Living       Date:  2021-03-26

6.  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

7.  Is Fitbit Charge 2 a feasible instrument to monitor daily physical activity and handbike training in persons with spinal cord injury? A pilot study.

Authors:  M C Maijers; O Verschuren; J M Stolwijk-Swüste; C F van Koppenhagen; S de Groot; M W M Post
Journal:  Spinal Cord Ser Cases       Date:  2018-09-11

8.  A study on effects of backrest thickness on the upper arm and trunk muscle load during wheelchair propulsion.

Authors:  Joo-Hyun Lee; In-Gyu Yoo
Journal:  J Phys Ther Sci       Date:  2016-05-31

9.  Estimation of Energy Expenditure in Wheelchair-Bound Spinal Cord Injured Individuals Using Inertial Measurement Units.

Authors:  Werner L Popp; Lea Richner; Michael Brogioli; Britta Wilms; Christina M Spengler; Armin E P Curt; Michelle L Starkey; Roger Gassert
Journal:  Front Neurol       Date:  2018-07-03       Impact factor: 4.003

10.  Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments.

Authors:  Fabian Marcel Rast; Rob Labruyère
Journal:  J Neuroeng Rehabil       Date:  2020-11-04       Impact factor: 4.262

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