To estimate the user gait speed can be crucial in many topics, such as health care systems,
since the presence of difficulties in walking is a core indicator of health and function in aging and
disease. Methods for non-invasive and continuous assessment of the gait speed may be key to
enable early detection of cognitive diseases such as dementia or Alzheimer’s disease. Wearable
technologies can provide innovative solutions for healthcare problems. Bluetooth Low Energy (BLE)
technology is excellent for wearables because it is very energy efficient, secure, and inexpensive.
In this paper, the BLE-GSpeed database is presented. The dataset is composed of several BLE RSSI
measurements obtained while users were walking at a constant speed along a corridor. Moreover,
a set of experiments using a baseline algorithm to estimate the gait speed are also presented to
provide baseline results to the research community
