Ok

By continuing your visit to this site, you accept the use of cookies. These ensure the smooth running of our services. Learn more.

Oct 23, 2010

Potential for new technologies in clinical practice

Potential for new technologies in clinical practice.

Curr Opin Neurol. 2010 Oct 18;

Authors: Burridge JH, Hughes AM

PURPOSE OF REVIEW: Cost-effective neurorehabilitation is essential owing to financial constraints on healthcare resources. Technologies have the potential to contribute but without strong clinical evidence are unlikely to be widely reimbursed. This review presents evidence of new technologies since 2008 and identifies barriers to translation of technologies into clinical practice. RECENT FINDINGS: Technology has not been shown to be superior to intensively matched existing therapies. Research has been undertaken into the development and preliminary clinical testing of novel technologies including robotics, electrical stimulation, constraint-induced movement therapy, assistive orthoses, noninvasive brain stimulation, virtual reality and gaming devices. Translation of the research into clinical practice has been impeded by a lack of robust evidence of clinical effectiveness and usability. Underlying mechanisms associated with recovery are beginning to be explored, which may lead to more targeted interventions. Improvements in function have been demonstrated beyond the normal recovery period, but few trials demonstrate lasting effects. SUMMARY: Technologies, alone or combined, may offer a cost-effective way to deliver intensive neurorehabilitation therapy in clinical and community environments, and have the potential to empower patients to take more responsibility for their rehabilitation and continue with long-term exercise.

Jul 30, 2010

Sniff-activated sensor may return active lifestyles to paralyzed and disabled

Disabled persons, quadriplegics and others suffering from paralysis may be able to regain movement with a sniff-activated sensor, according to a study by Israeli researchers.

The technology works by translating changes in nasal air pressure into electrical signals that are passed to a computer. Patients can sniff in certain patterns to select letters or numbers to compose text, or on the computer, to control the mouse. For getting around, sniffing controls the direction of the wheelchair, Bloomberg reports.

Quadriplegic patients were able to use the device to navigate wheelchairs as well as healthy people. Two participants who were completely paralyzed but with intact mental function used the technology to communicate by choosing letters on a computer screen to write. The study appears in the Proceedings of the National Academy of Sciences.

Full Story

Dec 08, 2009

Avatar - A multi-sensory system for real time body position monitoring

Avatar - A multi-sensory system for real time body position monitoring.

Conf Proc IEEE Eng Med Biol Soc. 2009;1:2462-5

Authors: Jovanov E, Hanish N, Courson V, Stidham J, Stinson H, Webb C, Denny K

Virtual reality and computer assisted physical rehabilitation applications require an unobtrusive and inexpensive real time monitoring systems. Existing systems are usually complex and expensive and based on infrared monitoring. In this paper we propose Avatar, a hybrid system consisting of off-the-shelf components and sensors. Absolute positioning of a few reference points is determined using infrared diode on subject's body and a set of Wii((c)) Remotes as optical sensors. Individual body segments are monitored by intelligent inertial sensor nodes iSense. A network of inertial nodes is controlled by a master node that serves as a gateway for communication with a capture device. Each sensor features a 3D accelerometer and a 2 axis gyroscope. Avatar system is used for control of avatars in Virtual Reality applications, but could be used in a variety of augmented reality, gaming, and computer assisted physical rehabilitation applications.

Jun 24, 2009

Neurofeedback-based motor imagery training for brain-computer interface

Neurofeedback-based motor imagery training for brain-computer interface (BCI).

J Neurosci Methods. 2009 Apr 30;179(1):150-6

Authors: Hwang HJ, Kwon K, Im CH

In the present study, we propose a neurofeedback-based motor imagery training system for EEG-based brain-computer interface (BCI). The proposed system can help individuals get the feel of motor imagery by presenting them with real-time brain activation maps on their cortex. Ten healthy participants took part in our experiment, half of whom were trained by the suggested training system and the others did not use any training. All participants in the trained group succeeded in performing motor imagery after a series of trials to activate their motor cortex without any physical movements of their limbs. To confirm the effect of the suggested system, we recorded EEG signals for the trained group around sensorimotor cortex while they were imagining either left or right hand movements according to our experimental design, before and after the motor imagery training. For the control group, we also recorded EEG signals twice without any training sessions. The participants' intentions were then classified using a time-frequency analysis technique, and the results of the trained group showed significant differences in the sensorimotor rhythms between the signals recorded before and after training. Classification accuracy was also enhanced considerably in all participants after motor imagery training, compared to the accuracy before training. On the other hand, the analysis results for the control EEG data set did not show consistent increment in both the number of meaningful time-frequency combinations and the classification accuracy, demonstrating that the suggested system can be used as a tool for training motor imagery tasks in BCI applications. Further, we expect that the motor imagery training system will be useful not only for BCI applications, but for functional brain mapping studies that utilize motor imagery tasks as well.

Effect of Motor Imagery in the Rehabilitation of Burn Patients

Effect of Motor Imagery in the Rehabilitation of Burn Patients.

J Burn Care Res. 2009 Jun 5;

Authors: Guillot A, Lebon F, Vernay M, Girbon JP, Doyon J, Collet C

Although there is ample evidence that motor imagery (MI) improves motor performance after CNS injury, it is still unknown whether MI may enhance motor recovery after peripheral injury and most especially in the rehabilitation of burn patients. This study aimed to investigate the effects of a 2-week MI training program combined with conventional rehabilitation on the recovery of motor functions in handed burn patients. Fourteen patients admitted to the Medical Burn Center were requested to take part in the study and were randomly assigned to the imagery or the control group. Behavioral data related to the ability to perform each successive step of three manual motor sequences were collected at five intervals during the medical procedure. The results provided evidence that MI may facilitate motor recovery, and the belief in the effectiveness of MI was strong in all patients. MI may substantially contribute to improve the efficacy of conventional rehabilitation programs. Hence, this technique should be considered as a reliable alternative method to help burn patients to recover motor functions.

Nov 04, 2007

The use of videotape feedback after stroke

Motor learning and the use of videotape feedback after stroke.

Top Stroke Rehabil. 2007 Sep-Oct;14(5):28-36

Authors: Gilmore PE, Spaulding SJ

BACKGROUND: Efforts have been made to apply motor learning theories to the rehabilitation of individuals following stroke. Motor learning poststroke has not been well investigated in the literature. This research attempted to fill the gap regarding motor learning applied to practice. PURPOSE: This two-group research study attempted to determine the effectiveness of an experimental therapy combining videotape feedback with occupational therapy compared to only occupational therapy in learning the motor skill of donning socks and shoes after stroke. METHOD: Ten participants were randomly assigned to one of the two groups and all participants were videotaped during pretest and up to 10 treatment sessions aimed at donning socks and shoes. Only one group viewed their videotape replay. The acquisition of donning socks and shoes was measured using the socks and shoes subtests of the Klein-Bell Activities of Daily Living Scale and their scores on the Canadian Occupational Performance Measure. RESULTS: There was no significant difference between the two groups and both groups improved. However, the group that received videotape feedback thought they performed better and were more satisfied with their ability to don shoes, lending support for the use of videotape feedback poststroke to improve satisfaction with performance.

Jan 24, 2007

Biofeedback for robotic gait rehabilitation

Biofeedback for robotic gait rehabilitation

Journal of NeuroEngineering and Rehabilitation

By Lars Lunenburger, Gery Colombo and Robert Riener

Background: Development and increasing acceptance of rehabilitation robots as well as advances in technology allow new forms of therapy for patients with neurological disorders. Robot-assisted gait therapy can increase the training duration and the intensity for the patients while reducing the physical strain for the therapist. Optimal training effects during gait therapy generally depend on appropriate feedback about performance. Compared to manual treadmill therapy, there is a loss of physical interaction between therapist and patient with robotic gait retraining. Thus, it is difficult for the therapist to assess the necessary feedback and instructions. The aim of this study was to define a biofeedback system for a gait training robot and test its usability in subjects without neurological disorders. Methods: To provide an overview of biofeedback and motivation methods applied in gait rehabilitation, previous publications and results from our own research are reviewed. A biofeedback method is presented showing how a rehabilitation robot can assess the patients' performance and deliver augmented feedback. For validation, three subjects without neurological disorders walked in a rehabilitation robot for treadmill training. Several training parameters, such as body weight support and treadmill speed, were varied to assess the robustness of the biofeedback calculation to confounding factors. Results: The biofeedback values correlated well with the different activity levels of the subjects. Changes in body weight support and treadmill velocity had a minor effect on the biofeedback values. The synchronization of the robot and the treadmill affected the biofeedback values describing the stance phase. Conclusions: Robot-aided assessment and feedback can extend and improve robot-aided training devices. The presented method estimates the patients' gait performance with the use of the robot's existing sensors, and displays the resulting biofeedback values to the patients and therapists. The therapists can adapt the therapy and give further instructions to the patients. The feedback might help the patients to adapt their movement patterns and to improve their motivation. While it is assumed that these novel methods also improve training efficacy, the proof will only be possible with future in-depth clinical studies.