FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living

Citation Author(s):
Majd
SALEH
Université de Rennes 1, LTSI, Rennes, 35000, France, and INSERM, U1099, Rennes, 35000, France
Régine
LE BOUQUIN JEANNES
Université de Rennes 1, LTSI, Rennes, 35000, France, and INSERM, U1099, Rennes, 35000, France
Submitted by:
Majd SALEH
Last updated:
Tue, 05/17/2022 - 22:21
DOI:
10.21227/bnya-mn34
Data Format:
Link to Paper:
License:
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Abstract 

Description

FallAllD is a large open dataset of human falls and activities of daily living simulated by 15 participants. FallAllD consists of 26420 files collected using three data-loggers worn on the waist, wrist and neck of the subjects. Motion signals are captured using an accelerometer, gyroscope, magnetometer and barometer with efficient configurations that suit the potential applications e.g. fall detection, fall prevention and human activity recognition.

FallAllD is described in detail in the following journal article:

M. Saleh, M. Abbas and R. L. B. Jeannès, "FallAllD: An Open Dataset of Human Falls and Activities of Daily Living for Classical and Deep Learning Applications," in IEEE Sensors Journal, doi: 10.1109/JSEN.2020.3018335.

Data Acquisition

Three identical data-loggers developed by the society RF-Track have been used. They are waist, wrist and neck-worn devices equipped with:

·         LSM9DS1: 3-axial accelerometer, 3-axial gyroscope and 3-axial magnetometer.

·         MS5607-02BA03: barometer.

Sensors configurations

·         Accelerometer: Sampling frequency = 238 Hz. Measurement range = ±8 g.

·         Gyroscope: Sampling frequency = 238 Hz. Angular rate = ± 2000 dps.

·         Magnetometer: Sampling frequency = 80 Hz. Full scale magnetic field = ±4 Gauss.

·         Barometer: Sampling frequency = 10 Hz.

Instructions: 

Data files are stored in comma-separated values (csv) format. We developed two tools for encapsulating the data. The first one, namely FallAllD_Files_to_Matlab_Struct, is a MATLAB script that converts the dataset into a MATLAB structure stored as a ”.mat” file. The structure contains 8 fields {SubjectID, ActivityID, TrialNo, Device, Acc, Gyr, Mag, Bar}. The second tool, namely FallAllD_Files_to_Python_Struct, is a Python script that converts the dataset into a Pandas dataframe stored in hdf (”.h5”) or pickle (”.pkl”) formats. The dataframe has the same fields as the MATLAB structure.

To get familiar with FallAllD, use the MATLAB script Plot_FallAllD_Register to show any register of this dataset. 

If you use this dataset, please cite the following publication:

M. Saleh, M. Abbas and R. L. B. Jeannès, "FallAllD: An Open Dataset of Human Falls and Activities of Daily Living for Classical and Deep Learning Applications," in IEEE Sensors Journal, doi: 10.1109/JSEN.2020.3018335.

Comments

This looks like a great dataset, thank you!

Submitted by Kyle Embry on Wed, 10/28/2020 - 12:59