Automatic Identification of Solid-Phase Medication Intake Using
Wireless Wearable Accelerometers

D 2014

Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers

WANG, Rui, Zdeňka SITOVÁ, Xiaoqing JIA, Xiang HE, Tobi ABRAMSON et. al.

Základní údaje

Originální název

Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers

Autoři

WANG, Rui (156 Čína), Zdeňka SITOVÁ (203 Česká republika, garant, domácí), Xiaoqing JIA (156 Čína), Xiang HE (156 Čína), Tobi ABRAMSON (840 Spojené státy), Paolo GASTI (840 Spojené státy), Kiran S. BALAGANI (840 Spojené státy) a Aydin FARAJIDAVAR (840 Spojené státy)

Vydání

New York, 36th Annual International IEEE Engineering in Medicine and Biology Society Conference (EMBS), 2014, od s. 4168-4171, 4 s. 2014

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Kód RIV

RIV/00216224:14330/14:00076289

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4244-7929-0

ISSN

DOI

http://dx.doi.org/10.1109/EMBC.2014.6944542

UT WoS

000350044704041

Klíčová slova anglicky

ADHERENCE; DRUG

Štítky

firank_B

Změněno: 27. 8. 2019 11:50, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

We have proposed a novel solution to a fundamental problem encountered in implementing non-ingestion based medical adherence monitoring systems, namely, how to reliably identify pill medication intake. We show how wireless wearable devices with tri-axial accelerometer can be used to detect and classify hand gestures of users during solid-phase medication intake. Two devices were worn on the wrists of each user. Users were asked to perform two activities in the way that is natural and most comfortable to them: (1) taking empty gelatin capsules with water, and (2) drinking water and wiping mouth. 25 users participated in this study. The signals obtained from the devices were filtered and the patterns were identified using dynamic time warping algorithm. Using hand gesture signals, we achieved 84.17 percent true positive rate and 13.33 percent false alarm rate, thus demonstrating that the hand gestures could be used to effectively identify pill taking activity.

Citovat

WANG, Rui, Zdeňka SITOVÁ, Xiaoqing JIA, Xiang HE, Tobi ABRAMSON, Paolo GASTI, Kiran S. BALAGANI a Aydin FARAJIDAVAR. Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers. In 36th Annual International IEEE Engineering in Medicine and Biology Society Conference (EMBS), 2014. New York: IEEE, 2014, s. 4168-4171. ISBN 978-1-4244-7929-0. Dostupné z: https://dx.doi.org/10.1109/EMBC.2014.6944542.

@inproceedings{1196531,
   author = {Wang, Rui and Sitová, Zdeňka and Jia, Xiaoqing and He, Xiang and Abramson, Tobi and Gasti, Paolo and Balagani, Kiran S. and Farajidavar, Aydin},
   address = {New York},
   booktitle = {36th Annual International IEEE Engineering in Medicine and Biology Society Conference (EMBS), 2014},
   doi = {http://dx.doi.org/10.1109/EMBC.2014.6944542},
   keywords = {ADHERENCE; DRUG},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {New York},
   isbn = {978-1-4244-7929-0},
   pages = {4168-4171},
   publisher = {IEEE},
   title = {Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers},
   url = {http://tweetleveluat.edelman.com/event/embc-2014/paper-details?pdID=1527},
   year = {2014}
}

TY  - JOUR
ID  - 1196531
AU  - Wang, Rui - Sitová, Zdeňka - Jia, Xiaoqing - He, Xiang - Abramson, Tobi - Gasti, Paolo - Balagani, Kiran S. - Farajidavar, Aydin
PY  - 2014
TI  - Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers
PB  - IEEE
CY  - New York
SN  - 9781424479290
KW  - ADHERENCE
KW  - DRUG
UR  - http://tweetleveluat.edelman.com/event/embc-2014/paper-details?pdID=1527
N2  - We have proposed a novel solution to a fundamental problem encountered in implementing non-ingestion based medical adherence monitoring systems, namely, how to reliably identify pill medication intake. We show how wireless wearable devices with tri-axial accelerometer can be used to detect and classify hand gestures of users during solid-phase medication intake. Two devices were worn on the wrists of each user. Users were asked to perform two activities in the way that is natural and most comfortable to them: (1) taking empty gelatin capsules with water, and (2) drinking water and wiping mouth. 25 users participated in this study. The signals obtained from the devices were filtered and the patterns were identified using dynamic time warping algorithm. Using hand gesture signals, we achieved 84.17 percent true positive rate and 13.33 percent false alarm rate, thus demonstrating that the hand gestures could be used to effectively identify pill taking activity.
ER  -

WANG, Rui, Zdeňka SITOVÁ, Xiaoqing JIA, Xiang HE, Tobi ABRAMSON, Paolo GASTI, Kiran S. BALAGANI a Aydin FARAJIDAVAR. Automatic Identification of Solid-Phase Medication Intake Using Wireless Wearable Accelerometers. In \textit{36th Annual International IEEE Engineering in Medicine and Biology Society Conference (EMBS), 2014}. New York: IEEE, 2014, s.~4168-4171. ISBN~978-1-4244-7929-0. Dostupné z: https://dx.doi.org/10.1109/EMBC.2014.6944542.

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