Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data

Lambrecht, Stefan and Gallego Juárez, Juan Antonio and Rocón de Lima, Eduardo and Pons Rovira, José Luis (2014). Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data. "Frontiers in Neursocience", v. 8 (n. 221); pp. 1-9. ISSN 1662-4548. https://doi.org/10.3389/fnins.2014.00221.

Description

Title: Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data
Author/s:
  • Lambrecht, Stefan
  • Gallego Juárez, Juan Antonio
  • Rocón de Lima, Eduardo
  • Pons Rovira, José Luis
Item Type: Article
Título de Revista/Publicación: Frontiers in Neursocience
Date: 24 July 2014
ISSN: 1662-4548
Volume: 8
Subjects:
Freetext Keywords: tremor, MEMS, sensor location, context awareness, real-time estimation
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. First, we describe a novel relative sensor placement identification technique based on orientation data. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. The methods presented in this study constitute an important step toward more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7ICT-2011.5.1-287739NeuroTremorUnspecifiedUnspecified
Government of SpainCSD2009-00067HYPERUnspecifiedUnspecified

More information

Item ID: 38719
DC Identifier: http://oa.upm.es/38719/
OAI Identifier: oai:oa.upm.es:38719
DOI: 10.3389/fnins.2014.00221
Official URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4110507/
Deposited by: Memoria Investigacion
Deposited on: 01 Apr 2017 10:11
Last Modified: 01 Apr 2017 10:11
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