Abstract
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.
Highlights
Over the 40 years, the percentage of people aged 60 and older is expected to rise from 10% to 22% of the total population [1]
The plot shows the average error in m/s for the gait speed estimation for each smartwatch, for each beacon model, and for several beacons ranging from 2 to 10
The first conclusion we draw from the results is that using raw data to estimate the gait speed provides a very uniform average error, which is independent of the number of beacons considered
Summary
Over the 40 years, the percentage of people aged 60 and older is expected to rise from 10% to 22% of the total population [1] This issue will pose a challenge for health care systems, especially considering that older people have more health-related issues and long-term care needs than the rest of society. In this context, cognitive decline and dementia are predicted to double their number of cases every 20 years globally. Several studies have confirmed an association linking gait speed with many significant health-related outcomes, including hospitalization, falls, nursing home placement, mobility disability, and cognitive diseases
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