Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson's Disease patients.
Gait
Gyroscope
Older adults
Parkinson
Step detection
Stroke
Turns
Walking
Wearable sensors
Journal
Journal of neuroengineering and rehabilitation
ISSN: 1743-0003
Titre abrégé: J Neuroeng Rehabil
Pays: England
ID NLM: 101232233
Informations de publication
Date de publication:
06 02 2021
06 02 2021
Historique:
received:
07
09
2020
accepted:
26
01
2021
entrez:
7
2
2021
pubmed:
8
2
2021
medline:
9
6
2021
Statut:
epublish
Résumé
Identification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson's disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions. Participants (older adults, people with Parkinson's disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories. The detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%), slalom walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%), and turning (IC: recall [Formula: see text] 85%, precision [Formula: see text] 95%, F1 score [Formula: see text]91%; FC: recall [Formula: see text] 84%, precision [Formula: see text] 95%, F1 score [Formula: see text]89%). Shank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.
Sections du résumé
BACKGROUND
Identification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson's disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions.
METHODS
Participants (older adults, people with Parkinson's disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories.
RESULTS
The detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%), slalom walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%), and turning (IC: recall [Formula: see text] 85%, precision [Formula: see text] 95%, F1 score [Formula: see text]91%; FC: recall [Formula: see text] 84%, precision [Formula: see text] 95%, F1 score [Formula: see text]89%).
CONCLUSIONS
Shank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.
Identifiants
pubmed: 33549105
doi: 10.1186/s12984-021-00828-0
pii: 10.1186/s12984-021-00828-0
pmc: PMC7866479
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
28Références
Lancet Neurol. 2020 May;19(5):462-470
pubmed: 32059811
Gait Posture. 2012 Jun;36(2):316-8
pubmed: 22465705
Arch Phys Med Rehabil. 2010 Aug;91(8):1272-7
pubmed: 20684910
Gait Posture. 2001 Jul;14(1):11-8
pubmed: 11378420
J Biomech. 2016 Feb 8;49(3):332-7
pubmed: 26768229
Eur J Appl Physiol. 2004 Jun;92(1-2):39-44
pubmed: 14985994
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:3484-7
pubmed: 22255090
Sensors (Basel). 2010;10(6):5683-702
pubmed: 22219682
Med Eng Phys. 2010 Jul;32(6):545-52
pubmed: 20435502
Front Neurol. 2017 Sep 04;8:457
pubmed: 28928711
J Am Geriatr Soc. 2005 Apr;53(4):695-9
pubmed: 15817019
Stroke Res Treat. 2018 May 2;2018:7928597
pubmed: 29854381
IEEE J Biomed Health Inform. 2016 May;20(3):838-847
pubmed: 25850097
J Biomech. 2000 Jun;33(6):783-6
pubmed: 10808002
Mem Cognit. 1982 Jul;10(4):389-95
pubmed: 7132716
Expert Rev Med Devices. 2016 Jul;13(7):641-59
pubmed: 27309490
IEEE Trans Biomed Eng. 2004 Aug;51(8):1434-43
pubmed: 15311830
J Neuroeng Rehabil. 2019 Feb 4;16(1):24
pubmed: 30717753
Brain Sci. 2019 Feb 06;9(2):
pubmed: 30736374
J Biomech. 2002 May;35(5):689-99
pubmed: 11955509
PLoS One. 2016 Mar 31;11(3):e0152616
pubmed: 27031243
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:5067-5070
pubmed: 28269407
IEEE Trans Neural Syst Rehabil Eng. 2016 Dec;24(12):1363-1372
pubmed: 26955043
IEEE Trans Biomed Eng. 2003 Jun;50(6):711-23
pubmed: 12814238
IEEE Trans Biomed Eng. 2015 Apr;62(4):1089-97
pubmed: 25389237
J Neurophysiol. 1999 Jun;81(6):2914-22
pubmed: 10368408
Med Biol Eng Comput. 1990 Jul;28(4):355-60
pubmed: 2246935
Gait Posture. 2007 Feb;25(2):289-94
pubmed: 16730441
PLoS One. 2018 May 11;13(5):e0197264
pubmed: 29750815
Eur Rev Aging Phys Act. 2019 May 3;16:6
pubmed: 31073340
Gait Posture. 2003 Oct;18(2):1-10
pubmed: 14654202
Sensors (Basel). 2019 Aug 08;19(16):
pubmed: 31398903
Arch Phys Med Rehabil. 2013 Apr;94(4):680-6
pubmed: 23187040
Gait Posture. 2005 Feb;21(2):197-211
pubmed: 15639399
Sensors (Basel). 2018 Jan 06;18(1):
pubmed: 29316636
Sensors (Basel). 2018 Jan 30;18(2):
pubmed: 29385700
Gait Posture. 2014 Sep;40(4):487-92
pubmed: 25085660
J Neuroeng Rehabil. 2014 Nov 11;11:152
pubmed: 25388296