Citation

Nadeem A, Mehmood A, Rizwan K. Data Brief 2019; 27: e104717.

Affiliation

Department of Computer Science, Federal Urdu University of Arts, Science & Technology, Pakistan.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.dib.2019.104717

PMID

31886332

PMCID

PMC6920471

Abstract

This paper defines two major data sets 1) from wearable inertial measurement sensors and 2) wearable ECG SHIMMER™ sensors. The first dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal inertial measurement wearable SHIMMER™ sensors unit during research studies "Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data" [2] and "A novel fall detection algorithm for elderly using SHIMMER wearable sensors" [3]. The SHIMMER inertial sensor is a lightweight sensing device, incorporated with tri-axial accelerometer, a tri-axial gyroscope and tri-axial magnetometer, mounted on the waist of the subjects. The second dataset is developed to assess the feasibility of using SHIMMER™ wearable third generation ECG sensors for identification of basic heart anomalies by remote ECG analysis. The experimental protocol was carried out according to the Timed Up and Go (TUG) test [1], which is mainly used in fall detection and fall risk assessment systems specially designed for elderly. Three daily life activities such as standing still, walking and sitting on chair and getup were performed along with fall activity in controlled environment. This dataset is available on Data in Brief Dataverse [4] and a data repository [5].

© 2019 The Author(s).

Language: en

Keywords

Daily life activities; ECG analysis; ECG sensor; Fall detection systems; Inertial sensors; SHIMMERTM; TUG test