Inertial measurement and heart-rate sensor-based dataset for geriatric fall detection using custom built wrist-worn device

Inertial measurement and heart-rate sensor-based dataset for geriatric fall detection using custom built wrist-worn device

This paper describes a dataset acquired from 41 volunteers performing 16 Activities of daily livings (ADLs) and 8 Falls repeated 5 times. This data was collected using a custom wrist-worn end device. The dataset has data collected from Inertial measurement unit (IMU) and heart-rate sensors. The end...

Full description

Saved in:
Bibliographic Details
Published in:Data in brief Vol. 52; p. 109812
Main Authors: Nandi, Purab, Anupama, K. R, Agarwal, Himanish, Patel, Kishan, Bang, Vedant, Bharat, Manan, Guru, Madhen Vyas
Format: Journal Article
Language:English
Published: Netherlands Elsevier Inc 01-02-2024
Elsevier
Subjects:
Dataset
Fall detection
Geriatric
System on Chip
Wearable
Wearable
Fall detection
Geriatric
Dataset
System on Chip
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper describes a dataset acquired from 41 volunteers performing 16 Activities of daily livings (ADLs) and 8 Falls repeated 5 times. This data was collected using a custom wrist-worn end device. The dataset has data collected from Inertial measurement unit (IMU) and heart-rate sensors. The end device is built using Qualcomm Snapdragon 820c System on Chip (SoC) interfaced to the sensors via Interconnect Integrated Circuit (I2C) protocol. The data was sampled for every activity at a rate of 20 Hz for the motion sensors and at a rate of 1 Hz for the heart-rate sensor. The motion sensor comprised of a triaxial accelerometer, triaxial gyroscope, triaxial magnetometer and a linear accelerometer. The heart-rate sensor was medical grade and all sensors were calibrated for the wrist -worn position. The dataset is available on this website https://shamanx86.github.io/fall_detection_data/ and https://doi.org/10.5281/zenodo.10013090.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2023.109812