Mostra el registre d'ítem simple
Comparative and adaptation of step detection and step length estimators to a lateral belt worn accelerometer
dc.contributor.author | Sayeed, Taufique |
dc.contributor.author | Samà Monsonís, Albert |
dc.contributor.author | Català Mallofré, Andreu |
dc.contributor.author | Cabestany Moncusí, Joan |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2014-04-02T08:31:35Z |
dc.date.created | 2013 |
dc.date.issued | 2013 |
dc.identifier.citation | Sayeed, T. [et al.]. Comparative and adaptation of step detection and step length estimators to a lateral belt worn accelerometer. A: IEEE International Conference on e-Health Networking, Applications and Services. "Proceedings of IEEE 15th International Conference on e-Health Networking, Applications and Services". Lisboa: 2013, p. 105-109. |
dc.identifier.uri | http://hdl.handle.net/2117/22480 |
dc.description.abstract | Parkinson’s Disease (PD) is a neurodegenerative disease that predominantly alter patients’ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients’ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drug-administration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and three step detection methods and three step length estimators are compared considering the proposed sensor placement in signals obtained from healthy volunteers and PD patients. Adaptation methods to these step length estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance with the new proposed step detection method and reduce errors in respect of the original methods. |
dc.format.extent | 5 p. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Ciències de la salut |
dc.subject.other | Parkinson disease(PD) |
dc.subject.other | step length |
dc.subject.other | gait speed |
dc.subject.other | center of mass (COM) |
dc.title | Comparative and adaptation of step detection and step length estimators to a lateral belt worn accelerometer |
dc.type | Conference lecture |
dc.subject.lemac | Parkinson, Malaltia de |
dc.contributor.group | Universitat Politècnica de Catalunya. GREC - Grup de Recerca en Enginyeria del Coneixement |
dc.contributor.group | Universitat Politècnica de Catalunya. AHA - Arquitectures Hardware Avançades |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6720648&tag=1 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 13394818 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Sayeed, T.; Sama, A.; Catala, A.; Cabestany, J. |
local.citation.contributor | IEEE International Conference on e-Health Networking, Applications and Services |
local.citation.pubplace | Lisboa |
local.citation.publicationName | Proceedings of IEEE 15th International Conference on e-Health Networking, Applications and Services |
local.citation.startingPage | 105 |
local.citation.endingPage | 109 |