scholarly journals Comparison of Gait Parameters during Forward Walking under Different Visual Conditions Using Inertial Motion Sensors

2022 ◽  
Vol 63 (1) ◽  
pp. 82
Author(s):  
Eun Jin Son ◽  
Ji Hyung Kim ◽  
Hye Eun Noh ◽  
Inon Kim ◽  
Joo Ae Lim ◽  
...  
Keyword(s):  
Motion Sensors ◽  
Inertial Motion ◽  
Gait Parameters ◽  
Visual Conditions

Fusion of Inertial Motion Sensors and Electroencephalogram for Activity Detection

2019 ◽  
pp. 319-326 ◽  
Author(s):  
Ibai Baglietto Araquistain ◽  
Xabier Garmendia ◽  
Manuel Graña ◽  
Javier de Lope Asiain
Keyword(s):  
Motion Sensors ◽  
Activity Detection ◽  
Inertial Motion

Accuracy of Inertial Motion Sensors in Static, Quasistatic, and Complex Dynamic Motion

2009 ◽  
Vol 131 (11) ◽  
Author(s):  
Alison Godwin ◽  
Michael Agnew ◽  
Joan Stevenson
Keyword(s):  
Human Motion ◽  
Three Dimensions ◽  
Motion Sensors ◽  
Inertial Motion ◽  
Dynamic Motion ◽  
Technical Specifications ◽  
Rms Error ◽  
Arm Motion ◽  
Roll Axis ◽  
Better Than

Inertial motion sensors (IMSs) combine three sensors to produce a reportedly stable and accurate orientation estimate in three dimensions. Although accuracy has been reported within the range of 2 deg of error by manufacturers, the sensors are rarely tested in the challenging motion present in human motion. Their accuracy was tested in static, quasistatic, and dynamic situations against gold-standard Vicon camera data. It was found that static and quasistatic rms error was even less than manufacturers’ technical specifications. Quasistatic rms error was minimal at 0.3 deg (±0.15 deg SD) on the roll axis, 0.29 deg (±0.20 deg SD) on the pitch axis, and 0.73 deg (±0.81 deg SD) on the yaw axis. The dynamic rms error was between 1.9 deg and 3.5 deg on the main axes of motion but it increased considerably on off-axis during planar pendulum motion. Complex arm motion in the forward reaching plane proved to be a greater challenge for the sensors to track but results are arguably better than previously reported studies considering the large range of motion used.

Consistent accuracy in whole-body joint kinetics during gait using wearable inertial motion sensors and in-shoe pressure sensors

2015 ◽  
Vol 42 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Tsolmonbaatar Khurelbaatar ◽  
Kyungsoo Kim ◽  
SuKyoung Lee ◽  
Yoon Hyuk Kim
Keyword(s):  
Pressure Sensors ◽  
Whole Body ◽  
Motion Sensors ◽  
Inertial Motion ◽  
Joint Kinetics ◽  
Body Joint

scholarly journals Wearable motion sensors and digital biomarkers in stroke rehabilitation

2020 ◽  
Vol 6 (3) ◽  
pp. 229-232
Author(s):  
Adrian Derungs ◽  
Corina Schuster-Amft ◽  
Oliver Amft
Keyword(s):  
Performance Monitoring ◽  
Motion Sensors ◽  
Observation Study ◽  
Free Living ◽  
Daily Routines ◽  
Arm Reaching ◽  
Gait Parameters ◽  
Stride Duration ◽  
Wearable Motion Sensors ◽  
Digital Biomarkers

AbstractWe propose three novel digital biomarkers for the longitudinal performance monitoring and movement evaluation of hemiparetic patients, e.g. after stroke. We devised convergence points (CP) for the bilateral walking analysis based on gait parameters, e.g. stride duration using regression- modelling to estimate similarity between body sides. The physical activity (PA) was devised to evaluate the energy expenditure of all extremities during training and free-living. The functional range of motion (fROM) is a digital biomarker to quantify the upper arm reaching ability, represented in 3D visualisations. In this work, we detail CP, PA, and fROM to derive rehabilitation insights for personalising therapies. We evaluated the proposed digital biomarkers in a clinical observation study with 11 patients after stroke during their rehabilitation including therapy and self-paced daily routines.

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