Modelling stabilograms with hidden Markov models

Autor:	Timo Tossavainen, Martti Juhola, Esko Toppila, I. Pyykkö, Jyrki Rasku
Rok vydání:	2008
Předmět:	Adult Male Engineering Posture Biomedical Engineering Markov model Machine learning computer.software_genre Models Biological Sensitivity and Specificity Humans Computer Simulation Force platform Diagnosis Computer-Assisted Hidden Markov model Physical Examination Meniere Disease Observer Variation Signal processing Models Statistical business.industry Reproducibility of Results General Medicine Middle Aged Markov Chains Variable-order Bayesian network Female Noise (video) Artificial intelligence business computer Algorithms
Zdroj:	Journal of Medical Engineering & Technology. 32:273-283
ISSN:	1464-522X 0309-1902
DOI:	10.1080/03091900600968908
Popis:	Hidden Markov models are an effective computational method for modelling and interpreting digital signals of biological, as well as other, origin. In the current investigation, we explored whether hidden Markov models can be used to control and represent phenomena in human balance signals recorded from subjects standing on a force platform. Additionally, our aim was to classify healthy controls and patients who suffered from Meniere's disease into their own classes. Hidden Markov models were capable of these tasks and of overcoming such disturbances as noise and other unforeseen perturbations in balance signals, which are inherently complex and possibly difficult to visually specify.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::759221e5e9ad1aeafc7600ba5ba4730a https://doi.org/10.1080/03091900600968908 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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