Research Article
Recognizing Hospital Care Activities with a Coat Pocket Worn Smartphone
@INPROCEEDINGS{10.4108/icst.mobicase.2014.257777, author={Gernot Bahle and Agnes Gruenerbl and Enrico Bignotti and Mattia Zeni and Fausto Giunchiglia and Paul Lukowicz}, title={Recognizing Hospital Care Activities with a Coat Pocket Worn Smartphone}, proceedings={6th International Conference on Mobile Computing, Applications and Services}, publisher={IEEE}, proceedings_a={MOBICASE}, year={2014}, month={11}, keywords={activity recognition health care documentation real-world study}, doi={10.4108/icst.mobicase.2014.257777} }- Gernot Bahle
Agnes Gruenerbl
Enrico Bignotti
Mattia Zeni
Fausto Giunchiglia
Paul Lukowicz
Year: 2014
Recognizing Hospital Care Activities with a Coat Pocket Worn Smartphone
MOBICASE
IEEE
DOI: 10.4108/icst.mobicase.2014.257777
Abstract
In this work, we show how a smart-phone worn unobtrusively in a nurse’s coat pocket can be used to document the patient care activities performed during a regular morning routine. The main contribution is to show how, taking into account certain domain specific boundary conditions, a single sensor node worn in such an (from the sensing point of view) unfavorable location can still recognize complex, sometimes subtle activities. We evaluate our approach in a large real life dataset from day to day hospital operation. In total, 4 runs of patient care per day were collected for 14 days at a geriatric ward and annotated in high detail by following the performing nurses for the entire duration. This amounts to over 800 hours of sensor data including acceleration, gyroscope, compass, wifi and sound annotated with groundtruth at less than 1min resolution.
