TY - JOUR
T1 - A multi-sensory dataset for the activities of daily living
AU - Ruzzon, Marco
AU - Carfì, Alessandro
AU - Ishikawa, Takahiro
AU - Mastrogiovanni, Fulvio
AU - Murakami, Toshiyuki
N1 - Funding Information:
M. Ruzzon was also supported by the University of Genoa with a mobility scholarship to conduct research activities at Keio University, Tokyo, Japan.
Funding Information:
This work was supported by the European Union Erasmus+ Programme via the European Master on Advanced Robotics Plus (EMARO+) project.
Publisher Copyright:
© 2020 The Authors
PY - 2020/10
Y1 - 2020/10
N2 - The article describes a multi-sensory dataset related to the Activities of Daily Living (ADL). These are the activities that contribute to an assessment of the overall status of elderly or people with special needs, possibly suffering from mild cognitive impairments. Typical basic ADLs include walking, such postural transitions as getting up or sitting down, as well as behaviours related to feeding, such as drinking or eating with knife and fork, or personal hygiene, e.g., teeth brushing. The collection process adopted for building this dataset considers nine ADL-related activities, which have been performed in different locations and involving the usage of both left and right arms. The dataset acquisition involved 10 volunteers performing 186 ADL instances, for a grand total of over 1860 examples. The dataset contains data from six 9-axis Inertial Measurement Units (IMUs), worn by each volunteer (two for each arm, one on the back and one on the right thigh). The dataset features an accurate data labelling done via manual annotation performed thanks to videos recorded by an RGB camera. The videos recorded during the experiments have been used only for labelling purposes, and they are not published.
AB - The article describes a multi-sensory dataset related to the Activities of Daily Living (ADL). These are the activities that contribute to an assessment of the overall status of elderly or people with special needs, possibly suffering from mild cognitive impairments. Typical basic ADLs include walking, such postural transitions as getting up or sitting down, as well as behaviours related to feeding, such as drinking or eating with knife and fork, or personal hygiene, e.g., teeth brushing. The collection process adopted for building this dataset considers nine ADL-related activities, which have been performed in different locations and involving the usage of both left and right arms. The dataset acquisition involved 10 volunteers performing 186 ADL instances, for a grand total of over 1860 examples. The dataset contains data from six 9-axis Inertial Measurement Units (IMUs), worn by each volunteer (two for each arm, one on the back and one on the right thigh). The dataset features an accurate data labelling done via manual annotation performed thanks to videos recorded by an RGB camera. The videos recorded during the experiments have been used only for labelling purposes, and they are not published.
KW - Accelerometer
KW - Activities of daily living
KW - Human activity recognition
KW - Human locomotion
KW - Inertial measurement unit
KW - Smart home
KW - Wearable sensing
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U2 - 10.1016/j.dib.2020.106122
DO - 10.1016/j.dib.2020.106122
M3 - Article
AN - SCOPUS:85089343986
SN - 2352-3409
VL - 32
JO - Data in Brief
JF - Data in Brief
M1 - 106122
ER -