A method for the classification of corrective activity in context dependent postural controlling tasks
Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Men...
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| Vydané v: | Computers in biology and medicine Ročník 39; číslo 10; s. 940 - 945 |
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| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.10.2009
Elsevier Limited |
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| ISSN: | 0010-4825, 1879-0534, 1879-0534 |
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| Abstract | Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the
K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. |
|---|---|
| AbstractList | Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Meniere's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. Abstract Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject.Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in the postural control system may also originate from a working environment where noise and solvents are present. Some diseases, for instance Menière's disease, can cause instability in walking and standing. Regardless of the origin of the problem in the balance system, it has to be detected in a meaningful, easily interpretable way. When detected, a suitable rehabilitation method can be proposed. In this paper we present a method which extracts a scalar feature from a stabilogram signal, which well describes the differences between young and elderly people's swaying processes. When our feature is applied to the K nearest neighbour algorithm the correct recognition accuracy is over 70% in cases where the purpose is to predict whether an unknown test feature is measured from a young or an elderly subject. |
| Author | Rasku, Jyrki |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19665113$$D View this record in MEDLINE/PubMed |
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| Snippet | Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge. Deficits in... Abstract Difficulties in maintaining postural stability are not common among young healthy people. However, with increasing age problems start to emerge.... |
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| SubjectTerms | Adult Aged Balance Female Humans Internal Medicine Male Other Posture Posturography Signal analysis Task Performance and Analysis |
| Title | A method for the classification of corrective activity in context dependent postural controlling tasks |
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