Wearable Sensing

Activities of Daily Living


Recognition of human activities is one of the most promising research areas in artificial intelligence. This has come along with the technological advancement in sensing technologies as well as the high demand for applications that are mobile, context-aware, and real-time. We have used a smart watch (Apple iWatch) to collect sensory data for 14 ADL activities (Activities of Daily Living). 

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Dataset Details

Citation Author(s):
Submitted by:
Walid Gomaa
Last updated:
Wed, 11/22/2017 - 09:06
DOI:
10.21227/H2PS74
Data Format:
 
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[1] , "Activities of Daily Living", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2PS74. Accessed: Dec. 13, 2017.
@data{h2ps74-17,
doi = {10.21227/H2PS74},
url = {http://dx.doi.org/10.21227/H2PS74},
author = { },
publisher = {IEEE Dataport},
title = {Activities of Daily Living},
year = {2017} }
TY - DATA
T1 - Activities of Daily Living
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2PS74
ER -
. (2017). Activities of Daily Living. IEEE Dataport. http://dx.doi.org/10.21227/H2PS74
, 2017. Activities of Daily Living. Available at: http://dx.doi.org/10.21227/H2PS74.
. (2017). "Activities of Daily Living." Web.
1. . Activities of Daily Living [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2PS74
. "Activities of Daily Living." doi: 10.21227/H2PS74

TST Footwear-Based dataset for Fall Detection (TST FB4FD)


The TST FB4FD dataset contains data acquired through a pair of smart shoes. The smart shoes are specifically designed for fall detection purposes and are equipped respectively with 3 Force Sensing Resistors (FSRs) and an inertial unit.  More specifically, the dataset consists of 32 different falls and 8 activities of daily living (ADLs) performed by 17 healthy subjects aged between 21 and 55 years, for a total of 544 falls and 136 ADLs sequences .

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Dataset Details

Citation Author(s):
Submitted by:
Laura Montanini
Last updated:
Tue, 04/11/2017 - 11:11
DOI:
10.21227/H2W01S
Data Format:
Links:
 
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[1] , "TST Footwear-Based dataset for Fall Detection (TST FB4FD)", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2W01S. Accessed: Dec. 13, 2017.
@data{h2w01s-17,
doi = {10.21227/H2W01S},
url = {http://dx.doi.org/10.21227/H2W01S},
author = { },
publisher = {IEEE Dataport},
title = {TST Footwear-Based dataset for Fall Detection (TST FB4FD)},
year = {2017} }
TY - DATA
T1 - TST Footwear-Based dataset for Fall Detection (TST FB4FD)
AU -
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2W01S
ER -
. (2017). TST Footwear-Based dataset for Fall Detection (TST FB4FD). IEEE Dataport. http://dx.doi.org/10.21227/H2W01S
, 2017. TST Footwear-Based dataset for Fall Detection (TST FB4FD). Available at: http://dx.doi.org/10.21227/H2W01S.
. (2017). "TST Footwear-Based dataset for Fall Detection (TST FB4FD)." Web.
1. . TST Footwear-Based dataset for Fall Detection (TST FB4FD) [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2W01S
. "TST Footwear-Based dataset for Fall Detection (TST FB4FD)." doi: 10.21227/H2W01S