Studying Upper-Limb Kinematics Using Inertial Sensors Embedded in Mobile Phones

The purposes of this study were to examine the consistency of wheelchair athletes’ upper-limb kinematics in consecutive propulsive cycles and to investigate the relationship between the maximum angular velocities of the upper arm and forearm and the consistency of the upper-limb kinematical pattern. Eleven elite international wheelchair racers propelled their own chairs on a roller while performing maximum speeds during wheelchair propulsion. A Qualisys motion analysis system was used to film the wheelchair propulsive cycles. Six reflective markers placed on the right shoulder, elbow, wrist joints, metacarpal, wheel axis, and wheel were automatically digitized. The deviations in cycle time, upper-arm and forearm angles, and angular velocities among these propulsive cycles were analyzed. The results demonstrated that in the consecutive cycles of wheelchair propulsion the increased maximum angular velocity may lead to increased variability in the upper-limb angular kinematics. It is speculated that this increased variability may be important for the distribution of load on different upper-extremity muscles to avoid the fatigue during wheelchair racing.

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Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs

F1000Research ◽

10.12688/f1000research.2-282.v1 ◽

2013 ◽

Vol 2 ◽

pp. 282 ◽

Cited By ~ 2

Author(s):

Giuliana Grimaldi ◽

Mario Manto ◽

Yassin Jdaoudi

Keyword(s):

Upper Limb ◽

Functional Disability ◽

Inertial Sensors ◽

Brain Computer Interface ◽

Quality Parameters ◽

Computer Interface ◽

Upper Limbs ◽

Original Algorithm ◽

Daily Life Activities ◽

New Treatment

Tremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is often required. Surgery is considered when the response to medications is not sufficient. However, about one third of patients are refractory to current treatments. New bioengineering therapies are emerging as possible alternatives. Our study was carried out in the framework of the European project “Tremor” (ICT-2007-224051). The main purpose of this challenging project was to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES; which has been shown to reduce upper limb tremor) with a brain-computer interface (BCI). A BCI-driven detection of voluntary movement is used to trigger FES in a closed-loop approach. Neurological tremor is detected using a matrix of EMG electrodes and inertial sensors embedded in a wearable textile. The identification of the intentionality of movement is a critical aspect to optimize this complex system. We propose a multimodal detection of the intentionality of movement by fusing signals from EEG, EMG and kinematic sensors (gyroscopes and accelerometry). Parameters of prediction of movement are extracted in order to provide global prediction plots and trigger FES properly. In particular, quality parameters (QPs) for the EEG signals, corticomuscular coherence and event-related desynchronization/synchronization (ERD/ERS) parameters are combined in an original algorithm which takes into account the refractoriness/responsiveness of tremor. A simulation study of the relationship between the threshold of ERD/ERS of artificial EEG traces and the QPs is also provided. Very interestingly, values of QPs were much greater than those obtained for the corticomuscular module alone.

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