A foot drop compensation device based on surface multi-field functional electrical stimulation-Usability study in a clinical environment.

INTRODUCTION: Functional electrical stimulation applies electrical pulses to the peripheral nerves to artificially achieve a sensory/motor function. When applied for the compensation of foot drop it provides both assistive and therapeutic effects. Multi-field electrodes have shown great potential but may increase the complexity of these systems. Usability aspects should be checked to ensure their success in clinical environments. METHODS: We developed the Fesia Walk device, based on a surface multi-field electrode and an automatic calibration algorithm, and carried out a usability study to check the feasibility of integrating this device in therapeutic programs in clinical environments. The study included 4 therapists and 10 acquired brain injury subjects (8 stroke and 2 traumatic brain injury). RESULTS: Therapists and users were "very satisfied" with the device according to the Quebec User Evaluation of Satisfaction with Assistive Technology scale, with average scores of 4.1 and 4.2 out of 5, respectively. Therapists considered the Fesia Walk device as "excellent" according to the System Usability Scale with an average score of 85.6 out of 100. CONCLUSIONS: This study showed us that it is feasible to include surface multi-field technology while keeping a device simple and intuitive for successful integration in common neurorehabilitation programs.

Development of computer games for assessment and training in post-stroke arm telerehabilitation.

Stroke is the leading cause of long term disability among adults in industrialized nations. The majority of these disabilities include deficiencies in arm function, which can make independent living very difficult. Research shows that better results in rehabilitation are obtained when patients receive more intensive therapy. However this intensive therapy is currently too expensive to be provided by the public health system, and at home few patients perform the repetitive exercises recommended by their therapists. Computer games can provide an affordable, enjoyable, and effective way to intensify treatment, while keeping the patient as well as their therapists informed about their progress. This paper presents the study, design, implementation and user-testing of a set of computer games for at-home assessment and training of upper-limb motor impairment after stroke.

The effect of visual cues on the number and duration of freezing episodes in Parkinson's patients.

Freezing of gait is a phenomenon common in Parkinson's patients and significantly affects quality of life. Sensory cues have been known to improve walking performance and reduce freezing of gait. Visual cues are reported to be particularly effective for this purpose. So far, sensory cues have generally been provided continuously, even when currently not needed. However, a recent approach suggests the provision of cues just in the case that freezing actually occurs. The arguments in favor of this "on-demand" cueing are reduced intrusiveness and reduced habituation to cues. Here, we analyzed the effect of visual cues on the number and duration of freezing episodes when activated either just "on-demand" or continuously and compare it to the baseline condition where no cue is provided. For this purpose, 7 Parkinson's patients regularly suffering from freezing of gait repeatedly walked a pre-defined course and their reaction to parallel laser lines projected in front of them on the floor was analyzed. The results show that, in comparison to the baseline condition, the mean duration of freezing was reduced by 51% in continuous cueing and by 69% in "on-demand" cueing. Concerning the number of freezing episodes, 43% fewer episodes were observed for continuous cueing and 9% less episodes for "on-demand" cueing.

sEMG-based detection of poor posture: a feasibility study.

The cost of the medical treatment of low back pain (LBP) was estimated to be $24 billion in the early 90s. Also, 80% of the LBP is estimated to be due to poor or inappropriate posture. The ultimate goal of the project is to develop a surface electromyography (sEMG)-based device that could be used to prevent and treat LBP by postural re-education or simply for on-the-spot sEMG feedback. In this paper we present the results and conclusions of a feasibility study for sEMG-based poor posture classifier. The results show that a s-EMG based poor posture classifier could be possible. The sensitivity for the best linear classifier model was 72% and the specificity was 78%. The same signal feature returned very different results from one participant to another. This inter-subject variability could be due to different muscular activation patterns during posture correction.

Absolute position calculation for a desktop mobile rehabilitation robot based on three optical mouse sensors.

ArmAssist is a wireless robot for post stroke upper limb rehabilitation. Knowing the position of the arm is essential for any rehabilitation device. In this paper, we describe a method based on an artificial landmark navigation system. The navigation system uses three optical mouse sensors. This enables the building of a cheap but reliable position sensor. Two of the sensors are the data source for odometry calculations, and the third optical mouse sensor takes very low resolution pictures of a custom designed mat. These pictures are processed by an optical symbol recognition algorithm which will estimate the orientation of the robot and recognize the landmarks placed on the mat. The data fusion strategy is described to detect the misclassifications of the landmarks in order to fuse only reliable information. The orientation given by the optical symbol recognition (OSR) algorithm is used to improve significantly the odometry and the recognition of the landmarks is used to reference the odometry to a absolute coordinate system. The system was tested using a 3D motion capture system. With the actual mat configuration, in a field of motion of 710 × 450 mm, the maximum error in position estimation was 49.61 mm with an average error of 36.70 ± 22.50 mm. The average test duration was 36.5 seconds and the average path length was 4173 mm.