Standard
SCAUT : using patient-generated data to improve remote monitoring of cardiac device patients. / Andersen, Tariq O.; Moll, Jonas.
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. red. / Nuria Oliver; Mary Czerwinski; Aleksandar Matic. Association for Computing Machinery, 2017. s. 444-447.
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Andersen, TO & Moll, J 2017,
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. i N Oliver, M Czerwinski & A Matic (red),
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery, s. 444-447, 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, Barcelona, Spanien,
23/05/2017.
https://doi.org/10.1145/3154862.3154922
APA
Andersen, T. O., & Moll, J. (2017).
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. I N. Oliver, M. Czerwinski, & A. Matic (red.),
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare (s. 444-447). Association for Computing Machinery.
https://doi.org/10.1145/3154862.3154922
Vancouver
Andersen TO, Moll J.
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. I Oliver N, Czerwinski M, Matic A, red., Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery. 2017. s. 444-447
https://doi.org/10.1145/3154862.3154922
Author
Andersen, Tariq O. ; Moll, Jonas. / SCAUT : using patient-generated data to improve remote monitoring of cardiac device patients. Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. red. / Nuria Oliver ; Mary Czerwinski ; Aleksandar Matic. Association for Computing Machinery, 2017. s. 444-447
Bibtex
@inproceedings{02122239c9fe49b1948bdb8cec68aa28,
title = "SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients",
abstract = "The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously. ",
author = "Andersen, {Tariq O.} and Jonas Moll",
year = "2017",
doi = "10.1145/3154862.3154922",
language = "English",
isbn = "978-1-4503-6363-1",
pages = "444--447",
editor = "Nuria Oliver and Mary Czerwinski and Aleksandar Matic",
booktitle = "Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare",
publisher = "Association for Computing Machinery",
note = "the 11th EAI International Conference ; Conference date: 23-05-2017 Through 26-05-2017",
}
RIS
TY - GEN
T1 - SCAUT
T2 - the 11th EAI International Conference
AU - Andersen, Tariq O.
AU - Moll, Jonas
PY - 2017
Y1 - 2017
N2 - The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously.
AB - The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously.
U2 - 10.1145/3154862.3154922
DO - 10.1145/3154862.3154922
M3 - Article in proceedings
SN - 978-1-4503-6363-1
SP - 444
EP - 447
BT - Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
A2 - Oliver, Nuria
A2 - Czerwinski, Mary
A2 - Matic, Aleksandar
PB - Association for Computing Machinery
Y2 - 23 May 2017 through 26 May 2017
ER -
