An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education

ABSTRACT: The traditional neurosurgical apprenticeship scheme includes the assessment of trainee’s manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator befo...

Full description

Autores:
Hernández Valdivieso, Alher Mauricio
Soto Romero, Georges
Tipo de recurso:
Article of investigation
Fecha de publicación:
2017
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/12828
Acceso en línea:
http://hdl.handle.net/10495/12828
Palabra clave:
Evaluación de la destreza manual
Sensores IMU
Simulación quirúrgica
Procesamiento de señales de movimiento
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/
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repository_id_str
dc.title.spa.fl_str_mv An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
title An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
spellingShingle An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
Evaluación de la destreza manual
Sensores IMU
Simulación quirúrgica
Procesamiento de señales de movimiento
title_short An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
title_full An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
title_fullStr An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
title_full_unstemmed An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
title_sort An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education
dc.creator.fl_str_mv Hernández Valdivieso, Alher Mauricio
Soto Romero, Georges
dc.contributor.author.none.fl_str_mv Hernández Valdivieso, Alher Mauricio
Soto Romero, Georges
dc.contributor.researchgroup.spa.fl_str_mv Grupo de Investigación en Bioinstrumentación e Ingeniería Clínica (GIBIC)
dc.subject.none.fl_str_mv Evaluación de la destreza manual
Sensores IMU
Simulación quirúrgica
Procesamiento de señales de movimiento
topic Evaluación de la destreza manual
Sensores IMU
Simulación quirúrgica
Procesamiento de señales de movimiento
description ABSTRACT: The traditional neurosurgical apprenticeship scheme includes the assessment of trainee’s manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator before putting them into practice in real patients. Unfortunately, in this new scheme, an experienced surgeon will not always be available to evaluate trainee’s performance. For this reason, it is necessary to develop automatic mechanisms to estimate metrics for assessing manual dexterity in a quantitative way. Authors have proposed some hardware-software approaches to evaluate manual dexterity on surgical simulators. This paper presents IGlove, a wearable device that uses inertial sensors embedded on an elastic glove to capture hand movements. Metrics to assess manual dexterity are estimated from sensors signals using data processing and information analysis algorithms. It has been designed to be used with a neurosurgical simulator called Daubara NS Trainer, but can be easily adapted to another benchtop- and manikin-based medical simulators. The system was tested with a sample of 14 volunteers who performed a test that was designed to simultaneously evaluate their fine motor skills and the IGlove’s functionalities. Metrics obtained by each of the participants are presented as results in this work; it is also shown how these metrics are used to automatically evaluate the level of manual dexterity of each volunteer.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2020-01-05T01:04:37Z
dc.date.available.none.fl_str_mv 2020-01-05T01:04:37Z
dc.type.spa.fl_str_mv Artículo de investigación
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dc.identifier.citation.spa.fl_str_mv Lemos Duque, J. D., Hernández Valdivieso, A. M., & Soto-Romero, G. (2017). An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education. Sensors, 17(5), 2-26. https://doi.org/10.3390/s17050988
dc.identifier.issn.none.fl_str_mv 1424-8220
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/12828
dc.identifier.doi.none.fl_str_mv 10.3390/s17050988
identifier_str_mv Lemos Duque, J. D., Hernández Valdivieso, A. M., & Soto-Romero, G. (2017). An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education. Sensors, 17(5), 2-26. https://doi.org/10.3390/s17050988
1424-8220
10.3390/s17050988
url http://hdl.handle.net/10495/12828
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationendpage.spa.fl_str_mv 26
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dc.relation.ispartofjournal.spa.fl_str_mv Sensors
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spelling Hernández Valdivieso, Alher MauricioSoto Romero, GeorgesGrupo de Investigación en Bioinstrumentación e Ingeniería Clínica (GIBIC)2020-01-05T01:04:37Z2020-01-05T01:04:37Z2017Lemos Duque, J. D., Hernández Valdivieso, A. M., & Soto-Romero, G. (2017). An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education. Sensors, 17(5), 2-26. https://doi.org/10.3390/s170509881424-8220http://hdl.handle.net/10495/1282810.3390/s17050988ABSTRACT: The traditional neurosurgical apprenticeship scheme includes the assessment of trainee’s manual skills carried out by experienced surgeons. However, the introduction of surgical simulation technology presents a new paradigm where residents can refine surgical techniques on a simulator before putting them into practice in real patients. Unfortunately, in this new scheme, an experienced surgeon will not always be available to evaluate trainee’s performance. For this reason, it is necessary to develop automatic mechanisms to estimate metrics for assessing manual dexterity in a quantitative way. Authors have proposed some hardware-software approaches to evaluate manual dexterity on surgical simulators. This paper presents IGlove, a wearable device that uses inertial sensors embedded on an elastic glove to capture hand movements. Metrics to assess manual dexterity are estimated from sensors signals using data processing and information analysis algorithms. It has been designed to be used with a neurosurgical simulator called Daubara NS Trainer, but can be easily adapted to another benchtop- and manikin-based medical simulators. The system was tested with a sample of 14 volunteers who performed a test that was designed to simultaneously evaluate their fine motor skills and the IGlove’s functionalities. 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