Wearable Sensing

Wearable Inertial Measurement Units (IMU) measuring acceleration, earth magnetic field and gyroscopic measurements can be considered for capturing human skeletal postures in real time. This dataset contains IMU readings (accelerometer, magnetometer and gyroscope) for common shoulder exercises: extension- flexion and abduction-adduction and simultaneously measures VICON readings and Kinect readings.

This dataset is a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users.

The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London.

The electronic system has been design to know the position human body. Of this way the system use a three axis accelerometer to detect five common positions (i) ventral decubitus, (ii) right lateral decubitus, (iii) left lateral decubitus, (iv) supine decubitus and (v) seated.  The sensor data was acquire with ten diferrents persons, their each positions was  how they felt confortable. The accelerometer acquire data from  3 axis possible (X,Y,Z)

Previous neuroimaging research has been traditionally confined to strict laboratory environments due to the limits of technology. Only recently have more studies emerged exploring the use of mobile brain imaging outside the laboratory. This study uses electroencephalography (EEG) and signal processing techniques to provide new opportunities for studying mobile subjects moving outside of the laboratory and in real world settings. The purpose of this study was to document the current viability of using high density EEG for mobile brain imaging both indoors and outdoors.