Figure 1.
Four SHIMMER sensor nodes were placed on the wrist, chest, hip, and ankle.
Figure 2.
Screenshot of App used for data labeling purposes.
Figure 3.
Plate with four SHIMMER sensor nodes used for synchronization (top) and sinusoidal synchronization signal (bottom). Dashed red line depicts the synchronization start point.
Table 1.
List of studied activities, abbreviations, durations, and intensities expressed in Metabolic Equivalent of Task (MET).
Figure 4.
Linear acceleration in vertical direction of the hip sensor for six activities. A: Lying, B: Standing, C: Vacuuming, D: Sweeping, E: Walking, F: Rope jumping.
Figure 5.
Illustration of the proposed classification system.
Rectangles indicate single classification systems BASE, HOUSE, REST, WALK and BICYCLE. Circles indicate single activities VC (vacuuming), SW (sweeping), SI (sitting), LY (lying), ST (standing), WK (walking), RU (running), AS (ascending stairs), DS (descending stairs), BC 50 (bicycling, 50 watt), BC 100 (bicycling, 100 watt), RJ (rope jumping) and WD (washing dishes).
Table 2.
Overview of six state-of-the-art approaches in the literature that were implemented and compared in the present study.
Table 3.
Mean classification rates (in percent) of the five subsystems (BASE, REST, HOUSE, WALK, BICYCLE).
Table 4.
Mean class dependent classification rates (in percent) for all 13 activities and overall mean classification rates of proposed system and state-of-the-art systems [17], [19]–[21], [23], [32].
Table 5.
Confusion matrix of our proposed algorithm. Each entry represents the number of classified epochs.