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

Autor:	Nandi P; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Anupama KR; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Agarwal H; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Patel K; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Bang V; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Bharat M; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India., Guru MV; BITS Pilani, K K Birla, Goa Campus, Goa 403726, India.
Jazyk:	angličtina
Zdroj:	Data in brief [Data Brief] 2023 Nov 18; Vol. 52, pp. 109812. Date of Electronic Publication: 2023 Nov 18 (Print Publication: 2024).
DOI:	10.1016/j.dib.2023.109812
Abstrakt:	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. (© 2023 The Author(s).)
Databáze:	MEDLINE
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