ADL Classification Based on Autocorrelation Function of Inertial Signals

Privacy-Preserving Human Action Recognition with a Many-Objective Evolutionary Algorithm

“…Human action recognition, and ADL recognition particularly, is an active field of research [6,[8][9][10][11]. For instance, Gomaa et al [8] take data from a smartwatch, compute the autocorrelation function up to a certain lag, then feed these features to a 'random forest'based classifier for training.…”

“…Human action recognition, and ADL recognition particularly, is an active field of research [6,[8][9][10][11]. For instance, Gomaa et al [8] take data from a smartwatch, compute the autocorrelation function up to a certain lag, then feed these features to a 'random forest'based classifier for training. For their experiments, they use a dataset with 14 different class labels, consisting of a mixture of motion primitives (e.g., walk, lie in bed, stand from sitting), as well as more complex activities (ADLs).…”

Dataset of acceleration signals recorded while performing activities of daily living

“… [7] 2014 8 19 MPs (sport) Mobifall [8] 2014 24 9 MPs + 4 falls SAR [9] 2014 10 7 MPs mHealth [10] 2015 10 12 MPs (sport) Stisen et al. [11] 2015 9 6 MPs JSI+FoS [12] 2016 15 10 MPs ADLs dataset [13] 2017 – 14 ADLs ASTRI [14] 2019 11 5 MPs Intelligent Fall [15] 2019 6/11 16 ADLs + 5 falls IM-WSHA [16] 2020 10 11 ADLs Fioretti et al. [17] 2021 36 6 ADLs Proposed: PAAL ADL v1.0 [18] 2021 33 24 ADLs Proposed: PAAL ADL v2.0 2021 52 24 ADLs The data can be used simply for recognition of human activities from accelerometer data, or, as proposed by the authors, to also minimise leakage of identity.…”