Estimation of ground reaction forces and moments during gait using only inertial motion capture

Angelos Karatsidis, Giovanni Bellusci, H. Martin Schepers, Mark de Zee, Michael S. Andersen, Petrus H. Veltink

Research output: Contribution to journalArticleAcademicpeer-review

40 Citations (Scopus)
86 Downloads (Pure)

Abstract

Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (Ͽ = 0.992, rRMSE = 5.3%), anterior (Ͽ = 0.965, rRMSE = 9.4%) and sagittal (Ͽ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (Ͽ = 0.862, rRMSE = 13.1%), frontal (Ͽ = 0.710, rRMSE = 29.6%), and transverse GRF&M (Ͽ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.
Original languageEnglish
Article number75
Number of pages22
JournalSensors (Switserland)
Volume17
Issue number1
DOIs
Publication statusPublished - Jan 2017

Fingerprint

gait
Gait
walking
Kinematics
moments
Myeloma Proteins
Kinetics
Cutoff frequency
Sensitivity analysis
Equations of motion
kinematics
Biomechanical Phenomena
Walking
Monitoring
Musculoskeletal Diseases
kinetics
sensitivity analysis
estimates
equations of motion
cut-off

Keywords

  • inertial motion capture
  • ground reaction force and moment
  • EC Grant Agreement nr.: FP7/607510
  • IR-103176
  • BSS-Biomechatronics and rehabilitation technology
  • Gait analysis
  • Inverse dynamics
  • EWI-27555

Cite this

Karatsidis, Angelos ; Bellusci, Giovanni ; Schepers, H. Martin ; de Zee, Mark ; Andersen, Michael S. ; Veltink, Petrus H. / Estimation of ground reaction forces and moments during gait using only inertial motion capture. In: Sensors (Switserland). 2017 ; Vol. 17, No. 1.
@article{34bc9dc523d64a11bec634aba8168833,
title = "Estimation of ground reaction forces and moments during gait using only inertial motion capture",
abstract = "Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (Ͽ = 0.992, rRMSE = 5.3{\%}), anterior (Ͽ = 0.965, rRMSE = 9.4{\%}) and sagittal (Ͽ = 0.933, rRMSE = 12.4{\%}) GRF&M components and as strong for the lateral (Ͽ = 0.862, rRMSE = 13.1{\%}), frontal (Ͽ = 0.710, rRMSE = 29.6{\%}), and transverse GRF&M (Ͽ = 0.826, rRMSE = 18.2{\%}). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.",
keywords = "inertial motion capture, ground reaction force and moment, EC Grant Agreement nr.: FP7/607510, IR-103176, BSS-Biomechatronics and rehabilitation technology, Gait analysis, Inverse dynamics, EWI-27555",
author = "Angelos Karatsidis and Giovanni Bellusci and Schepers, {H. Martin} and {de Zee}, Mark and Andersen, {Michael S.} and Veltink, {Petrus H.}",
year = "2017",
month = "1",
doi = "10.3390/s17010075",
language = "English",
volume = "17",
journal = "Sensors (Switserland)",
issn = "1424-8220",
publisher = "Multidisciplinary Digital Publishing Institute",
number = "1",

}

Estimation of ground reaction forces and moments during gait using only inertial motion capture. / Karatsidis, Angelos; Bellusci, Giovanni; Schepers, H. Martin; de Zee, Mark; Andersen, Michael S.; Veltink, Petrus H.

In: Sensors (Switserland), Vol. 17, No. 1, 75, 01.2017.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Estimation of ground reaction forces and moments during gait using only inertial motion capture

AU - Karatsidis, Angelos

AU - Bellusci, Giovanni

AU - Schepers, H. Martin

AU - de Zee, Mark

AU - Andersen, Michael S.

AU - Veltink, Petrus H.

PY - 2017/1

Y1 - 2017/1

N2 - Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (Ͽ = 0.992, rRMSE = 5.3%), anterior (Ͽ = 0.965, rRMSE = 9.4%) and sagittal (Ͽ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (Ͽ = 0.862, rRMSE = 13.1%), frontal (Ͽ = 0.710, rRMSE = 29.6%), and transverse GRF&M (Ͽ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.

AB - Ground reaction forces and moments (GRF&M) are important measures used as input in biomechanical analysis to estimate joint kinetics, which often are used to infer information for many musculoskeletal diseases. Their assessment is conventionally achieved using laboratory-based equipment that cannot be applied in daily life monitoring. In this study, we propose a method to predict GRF&M during walking, using exclusively kinematic information from fully-ambulatory inertial motion capture (IMC). From the equations of motion, we derive the total external forces and moments. Then, we solve the indeterminacy problem during double stance using a distribution algorithm based on a smooth transition assumption. The agreement between the IMC-predicted and reference GRF&M was categorized over normal walking speed as excellent for the vertical (Ͽ = 0.992, rRMSE = 5.3%), anterior (Ͽ = 0.965, rRMSE = 9.4%) and sagittal (Ͽ = 0.933, rRMSE = 12.4%) GRF&M components and as strong for the lateral (Ͽ = 0.862, rRMSE = 13.1%), frontal (Ͽ = 0.710, rRMSE = 29.6%), and transverse GRF&M (Ͽ = 0.826, rRMSE = 18.2%). Sensitivity analysis was performed on the effect of the cut-off frequency used in the filtering of the input kinematics, as well as the threshold velocities for the gait event detection algorithm. This study was the first to use only inertial motion capture to estimate 3D GRF&M during gait, providing comparable accuracy with optical motion capture prediction. This approach enables applications that require estimation of the kinetics during walking outside the gait laboratory.

KW - inertial motion capture

KW - ground reaction force and moment

KW - EC Grant Agreement nr.: FP7/607510

KW - IR-103176

KW - BSS-Biomechatronics and rehabilitation technology

KW - Gait analysis

KW - Inverse dynamics

KW - EWI-27555

U2 - 10.3390/s17010075

DO - 10.3390/s17010075

M3 - Article

VL - 17

JO - Sensors (Switserland)

JF - Sensors (Switserland)

SN - 1424-8220

IS - 1

M1 - 75

ER -