## 2 Dataset Description
### ADLs and Falls
We do not include ADLs belonging to categories such as Housekeeping-, Cooking-, or Personal care-related (those fall in the Others category in Table 1, because we are interested in low order activities of daily living, which include simple activities such as, Standing, Sitting down, Walking,rather than high order activities of daily living, which include complex activities such as, Washing dishes, Combing hair, Preparing a sandwich. The same holds for context-related activities that are intended as high order activities. This choice was also motivated by the fact that these activities are scarcely present in the analyzed datasets (in particular, each activity belonging in the above mentioned categories is present in only one of the 24 analyzed datasets). Finally, among the ADLs related to movements, we selected the ADLs most used in literature as demonstrated by the analysis we performed, which is also confirmed by [PERSON] et al. in [47]. Regarding falls, we analized DMPSBFD, Gravity, MobiAct, tFall, and UMAFall datasets from smartphones (see Table 1), and DLR v2, EvAAL, MMsys, SISFall, UMA Fall, and UR Fall Detection datasets from wearable ad-hoc devices, since they are the only datasets that contain falls. From this set, we excluded DLR v2, EvAAL because they do not specify the type of fall. Figure 2 shows the most common falls in the resulting 9 datasets we analyzed. The \(y\) axis represents the number of datasets that include the specified fall. Likewise ADLs, falls are grouped by category. Falling backward, Falling forward, and Falling sideward include back-, front-, and side-ward falls respectively. Sliding category can be further specialized so that to include Sliding from \begin{table}
\begin{tabular}{c c c c} \hline
**Category** & **Name** & **Description** & **Label** \\ \hline Motion-related & \begin{tabular}{c} Standing up from laying \\ Lying down from standing \\ Standing up from sitting \\ Running \\ Sitting down \\ Going downstairs \\ \end{tabular} & \
\begin{tabular}{c} From laying on the bed to standing \\ From standing to lying on a bed \\ From standing to sitting on a chair \\ Sitting on a chair \\ Sitting the stairs moderately \\ Down the stairs moderately \\ Normal walking \\ \end{tabular} &
\begin{tabular}{c} StandingUpFL \\ LyingDownFS \\ StandingUpFS \\ Running \\ Stitting Down \\ Sitting Down \\ Walking \\ \end{tabular} \\ \hline Sport-related & Jumping & Continuos jumping & Jumping \\ \hline \end{tabular}
\end{table} 
Table 2: ADLs performed by the subjects In the UniMiB SHAR dataset. Figure 1: Activities of daily living (ADLs) and theirs occurrence in the publicly available datasets analysed grouped by category. a chair, Sliding form a bed, and Generic sliding that not specifies details about the type of sliding. Finally, the category Specific fall includes different type of falls that have not been further specialized. For each category, the \(x\) axis shows all the types of falls we found. The label Others includes all the falls for the corresponding category that have been included in one dataset only. The Specific fall category is an exception since it includes falls types not particularly present in the analyzed datasets. Choosing which falls to include in the dataset was driven by the following considerations: the number of falls should have been comparable to that of the other datasets, and the dataset should have included a set of representative types of falls. Thus, having four categories (not considering Sliding, which includes only one type of fall that has been considered by two datasets only), we selected two falls from each of them. In each category, we selected the first two most popular falls. The category Falling sideward is an exception since we preferred to choose the two most specific falls instead of including the too generic Generic falling sideward. Table 3 shows the 8 falls that we selected according the adopted criterion. Finally, studies on this topic confirm the falls we selected are common in real-life [29; 48; 49; 50].