Evaluating the Mindwave Headset for Automatic Upper Body Motion Classification

2017 ◽  
Author(s):  
Edisson Naula ◽  
Andres F. Garcia ◽  
Kenneth Palacio-Baus ◽  
Luis I. Minchala ◽  
Andres Vazquez-Rodas ◽  
...  
Keyword(s):  
Body Motion ◽  
Upper Body ◽  
Motion Classification

scholarly journals Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ramon J. Boekesteijn ◽  
José M. H. Smolders ◽  
Vincent J. J. F. Busch ◽  
Alexander C. H. Geurts ◽  
Katrijn Smulders
Keyword(s):  
Dual Task ◽  
Wearable Sensors ◽  
Body Motion ◽  
Effect Sizes ◽  
Upper Body ◽  
Healthy Controls ◽  
Gait Parameters ◽  
Dual Task Cost ◽  
Dual Task Performance ◽  
Spatiotemporal Parameters

Abstract Background Although it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors. Methods Gait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA. Results Four independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA. Conclusions Besides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.

scholarly journals Collection and Analysis of Human Upper Limbs Motion Features for Collaborative Robotic Applications

Robotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 33
Author(s):  
Elisa Digo ◽  
Mattia Antonelli ◽  
Valerio Cornagliotto ◽  
Stefano Pastorelli ◽  
Laura Gastaldi
Keyword(s):  
Human Motion ◽  
Body Motion ◽  
Upper Body ◽  
Prediction Algorithm ◽  
Future Perspective ◽  
Motion Prediction ◽  
Upper Limbs ◽  
Human Motion Prediction ◽  
Pick And Place ◽  
Robotic Applications

(1) Background: The technologies of Industry 4.0 are increasingly promoting an operation of human motion prediction for improvement of the collaboration between workers and robots. The purposes of this study were to fuse the spatial and inertial data of human upper limbs for typical industrial pick and place movements and to analyze the collected features from the future perspective of collaborative robotic applications and human motion prediction algorithms. (2) Methods: Inertial Measurement Units and a stereophotogrammetric system were adopted to track the upper body motion of 10 healthy young subjects performing pick and place operations at three different heights. From the obtained database, 10 features were selected and used to distinguish among pick and place gestures at different heights. Classification performances were evaluated by estimating confusion matrices and F1-scores. (3) Results: Values on matrices diagonals were definitely greater than those in other positions. Furthermore, F1-scores were very high in most cases. (4) Conclusions: Upper arm longitudinal acceleration and markers coordinates of wrists and elbows could be considered representative features of pick and place gestures at different heights, and they are consequently suitable for the definition of a human motion prediction algorithm to be adopted in effective collaborative robotics industrial applications.

scholarly journals Capturing Upper Body Motion in Conversation

2014 ◽  
Author(s):  
Alvaro Marcos-Ramiro ◽  
Daniel Pizarro-Perez ◽  
Marta Marron-Romera ◽  
Daniel Gatica-Perez
Keyword(s):  
Body Motion ◽  
Upper Body

scholarly journals Visual perturbation of balance suggests impaired neuromuscular stability but intact visuo-motor control in Parkinson's disease

2021 ◽  
Author(s):  
David Engel ◽  
Justus Student ◽  
Jakob C.B. Schwenk ◽  
Adam P. Morris ◽  
Josefine Waldthaler ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Visual Motion ◽  
Phase Locking ◽  
Healthy Adults ◽  
The Body ◽  
Body Motion ◽  
Upper Body ◽  
Control Group ◽  
Visual Perturbation

Postural instability marks one of the most disabling features of Parkinson's disease (PD), but only reveals itself after affected brain areas have already been significantly damaged. Thus, there is a need to detect deviations in balance and postural control before visible symptoms occur. In this study, we visually perturbed balance in the anterior-posterior direction using sinusoidal oscillations of a moving room in virtual reality at different frequencies. We tested three groups: individuals with PD under dopaminergic medication, an age-matched control group, and a group of young healthy adults. We tracked their centre of pressure and their full-body motion. We investigated sway amplitudes and applied newly introduced phase-locking analyses to investigate responses across participants' bodies. Patients exhibited significantly higher sway amplitudes as compared to the control subjects. However, their sway was phase-locked to the visual motion like that of age-matched and young healthy adults. Furthermore, all groups successfully compensated for the visual perturbation by - most likely reflexively - phase-locking their sway to the stimulus. As frequency of the perturbation increased, distribution of phase-locking (PL) across the body revealed a shift of the highest PL-values from the upper body towards the hip-region for young healthy adults, which could not be observed in patients and elderly healthy adults. Our findings suggest an impaired neuromuscular stability, but intact visuomotor processing in early stages of PD, while less flexibility to adapt postural strategy to different perturbations revealed to be an effect of age rather than disease.

Validity of the Perception Neuron inertial motion capture system for upper body motion analysis

Measurement ◽  
2020 ◽  
Vol 149 ◽  
pp. 107024 ◽  
Author(s):  
Ryan Sers ◽  
Steph Forrester ◽  
Esther Moss ◽  
Stephen Ward ◽  
Jianjia Ma ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Motion Capture ◽  
Body Motion ◽  
Upper Body ◽  
Motion Capture System ◽  
Inertial Motion
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