Acceleration data for activity recognition typically are collected on battery-powered devices,
leading to a trade-off between high-accuracy recognition and energy-efficient operation. We …

Driven by real-world applications such as fitness, wellbeing and healthcare, accelerometry-
based activity recognition has been widely studied to provide context-awareness to future …

Sensors embedded in smartphones are an essential component for activity recognition.
Even though the accelerometer is the most widely used sensor, the highest recognition …

Wearables are being widely utilized in health and wellness applications, primarily due to the
recent advances in sensor and wireless communication, which enhance the promise of …

Our vision is a smartphone service that accurately tracks users' physical activities and
transportation modes using accelerometer-based activity recognition carried out on the …

This paper presents an energy-aware method for recognizing time series acceleration data
containing both activities and gestures using a wearable device coupled with a smartphone …

Human physical activity recognition from sensor data is a growing area of research due to
the widespread adoption of sensor-rich wearable and smart devices. The growing interest …

Energy storage is quickly becoming the limiting factor in mobile pervasive technology. We
introduce a novel method for activity recognition which leverages the predictability of human …

Wearable devices have become increasingly popular in recent years, and they offer a great
opportunity for sensor-based continuous human activity recognition in real-world scenarios …

In activity recognition techniques, existing wearable sensors have a problem performing the
recognition process. Because existing wearable sensors perform recognition process by …