ERSP: An Energy-Efficient Real-Time Smartphone Pedometer

Smart devices such as Apple´s iPod nano (5th generation), Nike+, and existing smartphone applications can provide the functions of a pedometer using the accelerometer. To achieve a high accuracy the devices must be worn on specific on-body locations such as on an armband or in footwear. Generally people carry smart devices such as smartphones in different positions, thus making it impractical to use these devices due to the reduced accuracy. Using the embedded smartphone accelerometer in a low-power mode we present an algorithm named Energy-efficient Real-time Smartphone Pedometer (ERSP), which accurately and energy-efficiently infers the real-time human step count within 2 seconds using the smartphone accelerometer. Our method involves extracting 5 features (4 novel and 1 derived) from the smartphone 3D accelerometer without the need for noise filtering or specific smartphone on-body placement and orientation, ERSP classification accuracy is approximately 94% when validated using data collected from 17 volunteers.