Features Extraction

Ravi et al. extracted features from raw data using a window size of 256 samples with 128 overlapping between consecutive windows. Sampling rate used is 50Hz which equivalent to 5.12s for each window. The calculated features are mean, standard deviation, energy and correlation. A single triaxial accelerometer was worn near the pelvic region in the…

Body Area Sensor Networks: Requirements, Operations, and Challenges

B. Johny and A. Anpalagan suggested health-care monitoring challenges can be tackled by interfacing sensors and actuators which form body area networks (BANs) with the human body together with the support of wireless technology and mobile and cloud computing [1]. Three stages of health-care monitoring system have been defined, which are sensors, data hub and…

KCAR: A knowledge-driven approach for concurrent activity recognition

Ye et al. proposed a concurrent activity recognition technique by analyzing real-time input sensor events to determine their semantic dissimilarity to segment a continuous sensor sequence into fragments, which a fragment corresponds to one ongoing activity [1]. Sensor events is defined as a function with three parameters, each of which refers to reported time of…

Feature Selection and Activity Recognition System Using a Single Tri-Axial Accelerometer

Gupta and Dallas have proposed feature selection and activity recognition system using a single tri-axial accelerometer in 2014 [1]. The physical activities recognized in this study are walking, running, jumping, sit-to-stand/stand-to-sit, stand-to-kneel-tostand and being stationary (sitting and standing at one place). The data are sampled at 126Hz during the experiments. The acceleration data are segmented…

Context-aware activity recognition through a combination of ontological and statistical reasoning

Riboni and Bettini have proposed a techinique for human activity recognition using ontologies and ontological reasoning combined with statistical inferencing [1]. The technique does not relies on large amount of training data which is difficult to obtain in applications such as rehabilitation systems, chronic disease management or monitoring of the elderly. [1] Riboni, Daniele, and…