Image-Based Mobility Assessment in Elderly People from Low-Cost Systems of Cameras: A Skeletal Dataset for Experimental Evaluations

Abstract

In recent years, the scientific community has found increasing interest in technological systems for the evaluation of the mobility performance of the elderly population. The reduced quantity of dataset for gait and balance analysis of elderly people is a serious issue in studying the link between cognitive impairment and motor dysfunction, particularly in people suffering from neurodegenerative diseases. In this context, this work aims to provide a dataset with skeletal information of people aged 60 years and older, while they perform well-established tests for stability assessment. 27 healthy people and 20 patients affected by neurodegenerative diseases, housed at two different nursing institutes, have been selected for the stability analysis. Subjects have been observed and evaluated by clinical therapists while executing three motion tests, namely balance, sit-to-stand and walking. The stability postural and gait control of each subject has been analyzed using a video-based system, made of three low-cost cameras, without the need for wearable and invasive sensors. The dataset provided in this work contains the skeletal information and highly-discriminant features of the balance, sit-to-stand and walking tests performed by each subject. To evaluate the efficiency of the balance dataset, the estimated risk of fall of the subjects has been processed considering the extracted features, and compared with the expected one. Final results have proven a good estimation of the risk of fall of the people under analysis, underlining the effectiveness of the dataset.