Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/14062
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dc.contributor.authorPonciano, Vascoen_US
dc.contributor.authorPires, Ivan Miguelen_US
dc.contributor.authorRibeiro, Fernando Reinaldoen_US
dc.contributor.authorMarques, Gonçaloen_US
dc.contributor.authorGarcia, Nuno M.en_US
dc.contributor.authorPombo, Nunoen_US
dc.contributor.authorSpinsante, Susannaen_US
dc.contributor.authorZdravevski, Eftimen_US
dc.date.accessioned2021-07-06T14:03:11Z-
dc.date.available2021-07-06T14:03:11Z-
dc.date.issued2020-03-23-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/14062-
dc.description.abstract<jats:p>The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject’s performance during the test execution.</jats:p>en_US
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.relation.ispartofElectronicsen_US
dc.titleIs The Timed-Up and Go Test Feasible in Mobile Devices? A Systematic Reviewen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.3390/electronics9030528-
dc.identifier.urlhttps://www.mdpi.com/2079-9292/9/3/528/pdf-
dc.identifier.volume9-
dc.identifier.issue3-
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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