Activity recognition via correlation coefficients based graph with nodes updated by multi-aggregator approach

•This paper proposes a graph theory approach to perform the human activity recognition.•This paper proposes the correlation coefficient based method for generating the graph using the signals in the UCI-HAR dataset.•The predefined thresholds are used for determining whether the nodes are connected or not.•The features are updated according to the activities via the multi-aggregation fusion approach.•The random forest is used to classify these activities.