Gait analysis of people with transfemoral amputation is essential to support the rehabilitation process. In particular, the kinematics of the body center of mass (bCoM), derived from the motion of segments’ centers of mass (sCoM), provide crucial information about patients’ locomotion. Magneto-Inertial Measurement Units (MIMUs) may be adopted to obtain this information in-the-field. However, MIMUs provide the 3D acceleration of the origin of the sensor’s frame.

The dataset contains the signal recording acquired on vehicle (car) drivers (ten experienced drivers and ten learner drivers) on the same 28.7 km route in the Silesian Voivodeship (in Polish województwo śląskie) in southern Poland. Experienced drivers performed the tasks in their own cars whereas the learner drivers performed the tasks under a supervison of a driving instructor in a specially marked cars (with L sign).

This dataset presents the measurements corresponding to the article "Validation of a Velostat-Based Pressure Sensitive Mat for Center of Pressure Measurements". You will find the data corresponding to an affordable commercial mat, a Velostat-based mat prototype, and a commercial force platform. The results obtained in the above-mentioned article can be reproduced with them.

Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.