The FARSEEING real-world fall repository: a large-scale collaborative database to collect and share sensor signals from real-world falls.
BACKGROUND
Real-world fall events objectively measured by body-worn sensors can improve the understanding of fall events in older people. However, these events are rare and hence challenging to capture. Therefore, the FARSEEING (FAll Repository for the design of Smart and sElf-adaptive Environments prolonging Independent livinG) consortium and associated partners started to build up a meta-database of real-world falls.


RESULTS
Between January 2012 and December 2015 more than 300 real-world fall events have been recorded. This is currently the largest collection of real-world fall data recorded with inertial sensors. A signal processing and fall verification procedure has been developed and applied to the data. Since the end of 2015, 208 verified real-world fall events are available for analyses. The fall events have been recorded within several studies, with different methods, and in different populations. All sensor signals include at least accelerometer measurements and 58 % additionally include gyroscope and magnetometer measurements. The collection of data is ongoing and open to further partners contributing with fall signals. The FARSEEING consortium also aims to share the collected real-world falls data with other researchers on request.


CONCLUSIONS
The FARSEEING meta-database will help to improve the understanding of falls and enable new approaches in fall risk assessment, fall prevention, and fall detection in both aging and disease.
Department of Clinical Gerontology, Robert Bosch Hospital, Auerbachstr. 110, Stuttgart, Germany ; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Jochen
0000-0002-5987-447X
J
Klenk
Department of Clinical Gerontology, Robert Bosch Hospital, Auerbachstr. 110, Stuttgart, Germany.
Lars
L
Schwickert
Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy.
Luca
L
Palmerini
Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy.
Sabato
S
Mellone
Department of Neuroscience, NTNU, Trondheim, Norway.
Alan
A
Bourke
Department of Neuroscience, NTNU, Trondheim, Norway.
Espen A F
EA
Ihlen
School of Population Health, University of Auckland, Auckland, New Zealand.
Ngaire
N
Kerse
Department of Geriatric Research, Bethanien-Hospital/Geriatric Center at the University of Heidelberg, Heidelberg, Germany.
Klaus
K
Hauer
Department of Human Movement Sciences, MOVE Research Institute Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Mirjam
M
Pijnappels
Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
Matthis
M
Synofzik
Department of Clinical Gerontology, Robert Bosch Hospital, Auerbachstr. 110, Stuttgart, Germany.
Karin
K
Srulijes
Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany ; German Research Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
Walter
W
Maetzler
Department of Neuroscience, NTNU, Trondheim, Norway.
Jorunn L
JL
Helbostad
Institute of Movement and Sport Gerontology, German Sport University Cologne, Cologne, Germany.
Wiebren
W
Zijlstra
Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Kamiar
K
Aminian
School of Nursing, Midwifery and Social Work, University of Manchester, Manchester, UK.
Christopher
C
Todd
Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy.
Lorenzo
L
Chiari
Department of Clinical Gerontology, Robert Bosch Hospital, Auerbachstr. 110, Stuttgart, Germany.
Clemens
C
Becker
Accelerometer; Body-worn sensors; Database; Falls; Older adults