Hisao Setoguchi

Human Activity Recognizer for Mobile Devices with Multiple Sensors

This paper presents a novel human activity recognizer used to estimate a users activities with sensors on a widespread consumer mobile device. Our recognizer can estimate a users means of migration by using a combination of an acceleration sensor and a GPS. We evaluate the accuracy rate of the estimation with cellular phones carried freely and the result is 90.6 percent even in the case of intermittent working mode for lower power consumption.

An online human activity recognizer for mobile phones with accelerometer

We propose a novel human activity recognizer for an application for mobile phones. Since such applications should not consume too much electric power, our method should have not only high accuracy but also low electric power consumption by using just a single three-axis accelerometer. In feature extraction with the wavelet transform, we employ the Haar mother wavelet that allows low computational complexity. In addition, we reduce dimensions of features by using the singular value decomposition. In spite of the complexity reduction, we discriminate a users status into walking, running, standing still and being in a moving train with an accuracy of over 90%.

Acceleration Noise Correction for Transfer Inference Using Accelerometers on Mobile Devices

The acceleration noise generated in the ordinary usage of mobile devices (e.g. when “taking out” the devices or operating them) interferes with estimation of the means of migration using accelerometers on the devices. We developed a correction method for the noise generated when users take out devices, change their posture, and operate the devices. The method uses the changes of acceleration and the operation events acquired from the operating systems of the mobile devices to detect the period of noises. The result of evaluation shows that the method using the acceleration changes improves the precision of the context inference approximately 5 %, and the method using the operation events corrects the inference mistaking resting for boarding.