**3. Methods**

Based on the literature combined with the proposed system architecture for the recognition of ADLs in [5–7,64], the methods that should be defined for each module of the proposed system, are as follows: data acquisition, data processing, data fusion, and data classification. The data processing methods include data cleaning and feature extraction methods. Additionally, since this study only uses a single sensor, i.e., the accelerometer, the data fusion methods are not necessary.

Figure 1 represents the methodology and system architecture proposed by the authors in this paper. The data acquisition is performed using the accelerometer sensor available in commonly used, off-the-shelf mobile devices with a mobile application during running, walking, standing, and walking upstairs and walking downstairs activities. This acquired data is processed using data cleaning and feature extraction methods. After data processing, MLP and DNN methods are used for ADLs identification.

**Figure 1.** Methodology and system architecture for the recognition of activities of daily living (ADLs).
