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.

Dataset Files

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[1] Majd SALEH, Régine LE BOUQUIN JEANNES, "FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living", IEEE Dataport, 2020. [Online]. Available: http://dx.doi.org/10.21227/bnya-mn34. Accessed: Apr. 17, 2024.
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doi = {10.21227/bnya-mn34},
url = {http://dx.doi.org/10.21227/bnya-mn34},
author = {Majd SALEH; Régine LE BOUQUIN JEANNES },
publisher = {IEEE Dataport},
title = {FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living},
year = {2020} }
TY - DATA
T1 - FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living
AU - Majd SALEH; Régine LE BOUQUIN JEANNES
PY - 2020
PB - IEEE Dataport
UR - 10.21227/bnya-mn34
ER -
Majd SALEH, Régine LE BOUQUIN JEANNES. (2020). FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living. IEEE Dataport. http://dx.doi.org/10.21227/bnya-mn34
Majd SALEH, Régine LE BOUQUIN JEANNES, 2020. FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living. Available at: http://dx.doi.org/10.21227/bnya-mn34.
Majd SALEH, Régine LE BOUQUIN JEANNES. (2020). "FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living." Web.
1. Majd SALEH, Régine LE BOUQUIN JEANNES. FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living [Internet]. IEEE Dataport; 2020. Available from : http://dx.doi.org/10.21227/bnya-mn34
Majd SALEH, Régine LE BOUQUIN JEANNES. "FallAllD: A Comprehensive Dataset of Human Falls and Activities of Daily Living." doi: 10.21227/bnya-mn34