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Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Issue 1 • Date March 2002

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Displaying Results 1 - 8 of 8
  • The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities

    Page(s): 1 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (319 KB)  

    The "Camera Mouse" system has been developed to provide computer access for people with severe disabilities. The system tracks the computer user's movements with a video camera and translates them into the movements of the mouse pointer on the screen. Body features such as the tip of the user's nose or finger can be tracked. The visual tracking algorithm is based on cropping an online template of the tracked feature from the current image frame and testing where this template correlates in the subsequent frame. The location of the highest correlation is interpreted as the new location of the feature in the subsequent frame. Various body features are examined for tracking robustness and user convenience. A group of 20 people without disabilities tested the Camera Mouse and quickly learned how to use it to spell out messages or play games. Twelve people with severe cerebral palsy or traumatic brain injury have tried the system, nine of whom have shown success. They interacted with their environment by spelling out messages and exploring the Internet. View full abstract»

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  • Ultrasound imaging in lower limb prosthetics

    Page(s): 11 - 21
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (299 KB) |  | HTML iconHTML  

    The biomechanical interaction between the residual limb and the prosthetic socket determines the quality of fit of the socket in lower limb prosthetics. An understanding of this interaction and the development of quantitative measures to predict the quality of fit of the socket are important for optimal socket design. Finite-element modeling is used widely for biomechanical modeling of the limb/socket interaction and requires information on the internal and external geometry of the residual limb. Volumetric imaging methods such as X-ray computed tomography, magnetic resonance imaging, and ultrasound have been used to obtain residual limb shape information. Of these modalities, ultrasound has been introduced most recently and its development for visualization in prosthetics is the least mature. This paper reviews ultrasound image acquisition and processing methods as they have been applied in lower limb prosthetics. View full abstract»

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  • Evaluation of force-sensing resistors for gait event detection to trigger electrical stimulation to improve walking in the child with cerebral palsy

    Page(s): 22 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB)  

    Force-sensing resistors (FSRs) were used to detect the transitions between five main phases of gait for the control of electrical stimulation (ES) while walking with seven children with spastic diplegia, cerebral palsy. The FSR positions within each child's insoles were customized based on plantar pressure profiles determined using a pressure-sensitive membrane array (Tekscan Inc., Boston, MA). The FSRs were placed in the insoles so that pressure transitions coincided with an ipsilateral or contralateral gait event. The transitions between the following gait phases were determined: loading response, mid- and terminal stance, and pre- and initial swing. Following several months of walking on a regular basis with FSR-triggered intramuscular ES to the hip and knee extensors, hip abductors, and ankle dorsi and plantar flexors, the accuracy and reliability of the FSRs to detect gait phase transitions were evaluated. Accuracy was evaluated with four of the subjects by synchronizing the output of the FSR detection scheme with a VICON (Oxford Metrics, U.K.) motion analysis system, which was used as the gait event reference. While mean differences between each FSR-detected gait event and that of the standard (VICON) ranged from +35 ms (indicating that the FSR detection scheme recognized the event before it actually happened) to -55 ms (indicating that the FSR scheme recognized the event after it occurred), the difference data was widely distributed, which appeared to be due in part to both intrasubject (step-to-step) and intersubject variability. Terminal stance exhibited the largest mean difference and standard deviation, while initial swing exhibited the smallest deviation and preswing the smallest mean difference. To determine step-to-step reliability, all seven children walked on a level walkway for at least 50 steps. Of 642 steps, there were no detection errors in 94.5% of the steps. Of the steps that contained a detection error, 80% were due to the failure of the FSR - - signal to reach the programmed threshold level during the transition to loading response. Recovery from an error always occurred one to three steps later. View full abstract»

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  • Prediction of joint moments using a neural network model of muscle activations from EMG signals

    Page(s): 30 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (254 KB)  

    Because the relationship between electromyographic (EMG) signals and muscle activations remains unpredictable, a new way to determine muscle activations from EMG signals by using a neural network is proposed and realized. Using a neural network to predict the muscle activations from EMG signals avoids establishing a complex mathematical model to express the muscle activation dynamics. The feed-forward neural network model of muscle activations applied here is composed of four layers and uses an adjusted back-propagation training algorithm. In this study, the basic back-propagation algorithm was not applicable, because muscle activation could not be measured, and hence the error between predicted activation and the real activation was not available. Thus, an adjusted back-propagation algorithm was developed. Joint torque at the elbow was calculated from the EMG signals of ten flexor and extensor muscles, using the neural network result of estimated activation of the muscles. Once muscle activations were obtained, Hill-type models were used to estimate muscle force. A musculoskeletal geometry model was then used to obtain moment arms, from which joint moments were determined and compared with measured values. The results show that this neural network model can be used to represent the relationship between EMG signals and joint moments well. View full abstract»

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  • Changes in the surface EMG signal and the biomechanics of motion during a repetitive lifting task

    Page(s): 38 - 47
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (281 KB)  

    The analysis of surface electromyographic (EMG) data recorded from the muscles of the back during isometric constant-force contractions has been a useful tool for assessing muscle deficits in patients with lower back pain (LBP). Until recently, extending the technique to dynamic tasks, such as lifting, has not been possible due to the nonstationarity of the EMG signals. Recent developments in time-frequency analysis procedures to compute the instantaneous median frequency (IMDF) were utilized in this study to overcome these limitations. Healthy control subjects with no history of LBP (n=9; mean age 26.3±6.7) were instrumented for acquisition of surface EMG data from six electrodes on the thoraco-lumbar region and whole-body kinematic data from a stereo-photogrammetric system. Data were recorded during a standardized repetitive lifting task (load=15% body mass; 12 lifts/min; 5-min duration). The task resulted in significant decreases in IMDF for six of the nine subjects, with a symmetrical pattern of fatigue among contralateral muscles and greater decrements in the lower lumbar region. For those subjects with a significant decrease in IMDF, a lower limb and/or upper limb biomechanical adaptation to fatigue was observed during the task. Increases in the peak box acceleration were documented. In two subjects, the acceleration doubled its value from the beginning to the end of the exercise, which lead to a significant increase in the torque at L4/L5. This observation suggests an association between muscle fatigue at the lumbar region and the way the subject manipulates the box during the exercise. Fatigue-related biomechanical adaptations are discussed as a possible supplement to functional capacity assessments among patients with LBP. View full abstract»

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  • A predictive fatigue model. I. Predicting the effect of stimulation frequency and pattern on fatigue

    Page(s): 48 - 58
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (409 KB) |  | HTML iconHTML  

    Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation. View full abstract»

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  • A predictive fatigue model. II. Predicting the effect of resting times on fatigue

    Page(s): 59 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (442 KB) |  | HTML iconHTML  

    For pt. I see ibid., vol. 10, no. 1, p. 48-58 (2002). We have recently developed a force- and fatigue-model system that accurately predicted the effect of stimulation frequency on muscle fatigue (see pt. I). The data used to test the model were produced by stimulation trains with resting times of 500 ms. Because the resting times between stimulation trains affect muscle fatigue, this study tested the model's ability to predict the effect of resting times on fatigue. In addition, because this study included different subjects than those used to develop the model, the validity of the model could be tested. Data were collected from human quadriceps femoris muscles using fatigue protocols that included resting times of 500, 750, or 1000 ms. Our results showed that the model predicted fatigue as being a decreasing function of resting time, which was consistent with experimental data. Reliability tests between the experimental data and predictions showed interclass correlation coefficients of 0.97, 0.95, and 0.81 for the initial, final, and percentage decline in peak forces, respectively, suggesting strong agreement between the experimental data and the predictions by the model. The success of our current force- and fatigue-model system helps to validate the model and suggests its potential use in identifying the optimal activation pattern during clinical application of functional electrical stimulation. View full abstract»

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  • Intraspinal micro stimulation generates locomotor-like and feedback-controlled movements

    Page(s): 68 - 81
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (608 KB) |  | HTML iconHTML  

    Intraspinal microstimulation (ISMS) may provide a means for improving motor function in people suffering from spinal cord injuries, head trauma, or stroke. The goal of this study was to determine whether microstimulation of the mammalian spinal cord could generate locomotor-like stepping and feedback-controlled movements of the hindlimbs. Under pentobarbital anesthesia, 24 insulated microwires were implanted in the lumbosacral cord of three adult cats. The cats were placed in a sling leaving all limbs pendent. Bilateral alternating stepping of the hindlimbs was achieved by stimulating through as few as two electrodes in each side of the spinal cord. Typical stride lengths were 23.5 cm, and ample foot clearance was achieved during swing. Mean ground reaction force during stance was 36.4 N, sufficient for load-bearing. Feedback-controlled movements of the cat's foot were achieved by reciprocally modulating the amplitude of stimuli delivered through two intraspinal electrodes generating ankle flexion and extension such that the distance between a sensor on the cat's foot and a free sensor moved back and forth by the investigators was minimized.. The foot tracked the displacements of the target sensor through its normal range of motion. Stimulation through electrodes with tips in or near lamina IX elicited movements most suitable for locomotion. In chronically implanted awake cats, stimulation through dorsally located electrodes generated paw shakes and flexion-withdrawals consistent with sensory perception but no weight-bearing extensor movements. These locations would not be suitable for ISMS in incomplete spinal cord injuries. Despite the complexity of the spinal neuronal networks, our results demonstrate that by stimulating through a few intraspinal microwires, near-normal bipedal locomotor-like stepping and feedback-controlled movements could be achieved. View full abstract»

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IEEE Transactions on Neural Systems and Rehabilitation Engineering focuses on the rehabilitative and neural aspects of biomedical engineering.

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Editor-in-Chief
Paul Sajda
Columbia University