Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …

Wearable inertial measurement unit (IMU) sensors are powerful enablers for acquisition of
motion data. Specifically, in human activity recognition (HAR), IMU sensor data collected …

Rapid growth of the aged population has caused an immense increase in the demand for
healthcare services. Generally, the elderly are more prone to health problems compared to …

Signal segmentation is a crucial stage in the activity recognition process; however, this has
been rarely and vaguely characterized so far. Windowing approaches are normally used for …

Traditional methods of human activity recognition usually require a large amount of strictly
labeled data for training classifiers. However, it is hard for one to keep a fixed activity when …

Wearable sensors are currently being used to manage fatigue in professional athletics,
transportation and mining industries. In manufacturing, physical fatigue is a challenging …

This article describes an investigation to determine the optimal placement of accelerometers
for the purpose of detecting a range of everyday activities. The paper investigates the effect …

Smartphone pedometry offers the possibility of ubiquitous health monitoring, context
awareness and indoor location tracking through Pedestrian Dead Reckoning (PDR) …

This study provides a comparative assessment on the different techniques of classifying
human activities performed while wearing inertial and magnetic sensor units on the chest …