Publication date: Available online 5 March 2016
Source:Gait & Posture
Author(s): Nienke M Kosse, Nicolas Vuillerme, Tibor Hortobágyi, Claudine JC Lamoth
IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims 1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and 2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
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Κυριακή 6 Μαρτίου 2016
Multiple gait parameters derived from iPod accelerometry predict age-related gait changes
Publication date: Available online 5 March 2016
Source:Gait & Posture
Author(s): Nienke M Kosse, Nicolas Vuillerme, Tibor Hortobágyi, Claudine JC Lamoth
IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims 1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and 2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
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Source:Gait & Posture
Author(s): Nienke M Kosse, Nicolas Vuillerme, Tibor Hortobágyi, Claudine JC Lamoth
IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims 1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and 2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
from #Audiology via ola Kala on Inoreader http://ift.tt/1TAPehC
via IFTTT
Multiple gait parameters derived from iPod accelerometry predict age-related gait changes
Publication date: Available online 5 March 2016
Source:Gait & Posture
Author(s): Nienke M Kosse, Nicolas Vuillerme, Tibor Hortobágyi, Claudine JC Lamoth
IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims 1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and 2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
from #Audiology via ola Kala on Inoreader http://ift.tt/1TAPehC
via IFTTT
Source:Gait & Posture
Author(s): Nienke M Kosse, Nicolas Vuillerme, Tibor Hortobágyi, Claudine JC Lamoth
IntroductionNormative data of how natural aging affects gait can serve as a frame of reference for changes in gait dynamics due to pathologies. Therefore, the present study aims 1) to identify gait variables sensitive to age-related changes in gait over the adult life span using the iPod and 2) to assess if these variables accurately distinguish young (aged 18-45) from healthy older (aged 46-75) adults.MethodsTrunk accelerations were recorded with an iPod Touch in 59 healthy adults during three minutes of overground walking. Gait variables included gait speed and accelerometry-based gait variables (stride, amplitude, frequency, and trajectory-related variables) in the anterior-posterior (AP) and medio-lateral (ML) directions. Multivariate partial least square analysis (PLS) identified variables sensitive to age-related differences in gait. To classify young and old adults, a PLS-discriminant analysis (PLS-DA) was used to test the accuracy of these variables.ResultsThe PLS model explained 42% of variation in age. Influential variables were: mean stride time, phase variability index, root mean square, stride variability, AP sample entropy and ML maximal Lyaponov exponent. PLS-DA classified 83% of the participants correctly with a sensitivity of 83% and specificity of 71%.DiscussionContrary to the frequently reported high gait variability observed in old adults with frailty and fall history, the present study showed that younger compared with older healthy adults had a more variable, less predictable and more symmetrical gait pattern. A model based on a combination of variables reflecting gait dynamics, could distinguish healthy younger adults from older adults.
from #Audiology via ola Kala on Inoreader http://ift.tt/1TAPehC
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