Anomaly Detection in the Artificial Pancreas
- Autores
- Avila, Luis; Martínez, Ernesto
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The integration of subcutaneous sensing and insulin delivery technologies with novel control strategies has brought closer the development of the Artificial Pancreas. Nevertheless, thought recent developments are aimed at preventing chronic complications and less patient discomfort, few works have addressed the critical issue of performance monitoring of the artificial pancreas as well as detection of abnormal functioning in any of its components. This work presents an anomaly detection monitoring tool using the widely known Clarke Error-Grid to identify functional degradation in the artificial pancreas components and guarantee safetycritical control of blood glucose levels. The effect of imperfect calibration of glucose sensors, time lag between blood glucose concentration and interstitial glucose readings, and excessive variability in glucose levels are evaluated against an expected behavior of the glucose regulation loop achieved through an optimal control policy. Results obtained evidence the feasibility of this novel use of the Clarke error grid as a comprehensive monitoring tool for the artificial pancreas.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
Artificial pancreas
Glucose Monitoring
Clarke EGA
Performance Degradation
Diabetes Management - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/93599
Ver los metadatos del registro completo
| id |
SEDICI_e131751f5b33900826f3c4976870120e |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/93599 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
Anomaly Detection in the Artificial PancreasAvila, LuisMartínez, ErnestoCiencias InformáticasArtificial pancreasGlucose MonitoringClarke EGAPerformance DegradationDiabetes ManagementThe integration of subcutaneous sensing and insulin delivery technologies with novel control strategies has brought closer the development of the Artificial Pancreas. Nevertheless, thought recent developments are aimed at preventing chronic complications and less patient discomfort, few works have addressed the critical issue of performance monitoring of the artificial pancreas as well as detection of abnormal functioning in any of its components. This work presents an anomaly detection monitoring tool using the widely known Clarke Error-Grid to identify functional degradation in the artificial pancreas components and guarantee safetycritical control of blood glucose levels. The effect of imperfect calibration of glucose sensors, time lag between blood glucose concentration and interstitial glucose readings, and excessive variability in glucose levels are evaluated against an expected behavior of the glucose regulation loop achieved through an optimal control policy. Results obtained evidence the feasibility of this novel use of the Clarke error grid as a comprehensive monitoring tool for the artificial pancreas.Sociedad Argentina de Informática e Investigación Operativa2013-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf22-30http://sedici.unlp.edu.ar/handle/10915/93599enginfo:eu-repo/semantics/altIdentifier/issn/1853-1881info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2026-02-12T16:01:31Zoai:sedici.unlp.edu.ar:10915/93599Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-02-12 16:01:31.441SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Anomaly Detection in the Artificial Pancreas |
| title |
Anomaly Detection in the Artificial Pancreas |
| spellingShingle |
Anomaly Detection in the Artificial Pancreas Avila, Luis Ciencias Informáticas Artificial pancreas Glucose Monitoring Clarke EGA Performance Degradation Diabetes Management |
| title_short |
Anomaly Detection in the Artificial Pancreas |
| title_full |
Anomaly Detection in the Artificial Pancreas |
| title_fullStr |
Anomaly Detection in the Artificial Pancreas |
| title_full_unstemmed |
Anomaly Detection in the Artificial Pancreas |
| title_sort |
Anomaly Detection in the Artificial Pancreas |
| dc.creator.none.fl_str_mv |
Avila, Luis Martínez, Ernesto |
| author |
Avila, Luis |
| author_facet |
Avila, Luis Martínez, Ernesto |
| author_role |
author |
| author2 |
Martínez, Ernesto |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Artificial pancreas Glucose Monitoring Clarke EGA Performance Degradation Diabetes Management |
| topic |
Ciencias Informáticas Artificial pancreas Glucose Monitoring Clarke EGA Performance Degradation Diabetes Management |
| dc.description.none.fl_txt_mv |
The integration of subcutaneous sensing and insulin delivery technologies with novel control strategies has brought closer the development of the Artificial Pancreas. Nevertheless, thought recent developments are aimed at preventing chronic complications and less patient discomfort, few works have addressed the critical issue of performance monitoring of the artificial pancreas as well as detection of abnormal functioning in any of its components. This work presents an anomaly detection monitoring tool using the widely known Clarke Error-Grid to identify functional degradation in the artificial pancreas components and guarantee safetycritical control of blood glucose levels. The effect of imperfect calibration of glucose sensors, time lag between blood glucose concentration and interstitial glucose readings, and excessive variability in glucose levels are evaluated against an expected behavior of the glucose regulation loop achieved through an optimal control policy. Results obtained evidence the feasibility of this novel use of the Clarke error grid as a comprehensive monitoring tool for the artificial pancreas. Sociedad Argentina de Informática e Investigación Operativa |
| description |
The integration of subcutaneous sensing and insulin delivery technologies with novel control strategies has brought closer the development of the Artificial Pancreas. Nevertheless, thought recent developments are aimed at preventing chronic complications and less patient discomfort, few works have addressed the critical issue of performance monitoring of the artificial pancreas as well as detection of abnormal functioning in any of its components. This work presents an anomaly detection monitoring tool using the widely known Clarke Error-Grid to identify functional degradation in the artificial pancreas components and guarantee safetycritical control of blood glucose levels. The effect of imperfect calibration of glucose sensors, time lag between blood glucose concentration and interstitial glucose readings, and excessive variability in glucose levels are evaluated against an expected behavior of the glucose regulation loop achieved through an optimal control policy. Results obtained evidence the feasibility of this novel use of the Clarke error grid as a comprehensive monitoring tool for the artificial pancreas. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013-09 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
| format |
conferenceObject |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/93599 |
| url |
http://sedici.unlp.edu.ar/handle/10915/93599 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1853-1881 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| dc.format.none.fl_str_mv |
application/pdf 22-30 |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1857016622745649152 |
| score |
12.930639 |