909 research outputs found

    Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury

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    Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.Peer ReviewedPostprint (published version

    Human-centered Electric Prosthetic (HELP) Hand

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    Through a partnership with Indian non-profit Bhagwan Mahaveer Viklang Sahayata Samiti, we designed a functional, robust, and and low cost electrically powered prosthetic hand that communicates with unilateral, transradial, urban Indian amputees through a biointerface. The device uses compliant tendon actuation, a small linear servo, and a wearable garment outfitted with flex sensors to produce a device that, once placed inside a prosthetic glove, is anthropomorphic in both look and feel. The prosthesis was developed such that future groups can design for manufacturing and distribution in India

    Towards Natural Control of Artificial Limbs

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    The use of implantable electrodes has been long thought as the solution for a more natural control of artificial limbs, as these offer access to long-term stable and physiologically appropriate sources of control, as well as the possibility to elicit appropriate sensory feedback via neurostimulation. Although these ideas have been explored since the 1960’s, the lack of a long-term stable human-machine interface has prevented the utilization of even the simplest implanted electrodes in clinically viable limb prostheses.In this thesis, a novel human-machine interface for bidirectional communication between implanted electrodes and the artificial limb was developed and clinically implemented. The long-term stability was achieved via osseointegration, which has been shown to provide stable skeletal attachment. By enhancing this technology as a communication gateway, the longest clinical implementation of prosthetic control sourced by implanted electrodes has been achieved, as well as the first in modern times. The first recipient has used it uninterruptedly in daily and professional activities for over one year. Prosthetic control was found to improve in resolution while requiring less muscular effort, as well as to be resilient to motion artifacts, limb position, and environmental conditions.In order to support this work, the literature was reviewed in search of reliable and safe neuromuscular electrodes that could be immediately used in humans. Additional work was conducted to improve the signal-to-noise ratio and increase the amount of information retrievable from extraneural recordings. Different signal processing and pattern recognition algorithms were investigated and further developed towards real-time and simultaneous prediction of limb movements. These algorithms were used to demonstrate that higher functionality could be restored by intuitive control of distal joints, and that such control remains viable over time when using epimysial electrodes. Lastly, the long-term viability of direct nerve stimulation to produce intuitive sensory feedback was also demonstrated.The possibility to permanently and reliably access implanted electrodes, thus making them viable for prosthetic control, is potentially the main contribution of this work. Furthermore, the opportunity to chronically record and stimulate the neuromuscular system offers new venues for the prediction of complex limb motions and increased understanding of somatosensory perception. Therefore, the technology developed here, combining stable attachment with permanent and reliable human-machine communication, is considered by the author as a critical step towards more functional artificial limbs

    Current state of digital signal processing in myoelectric interfaces and related applications

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    This review discusses the critical issues and recommended practices from the perspective of myoelectric interfaces. The major benefits and challenges of myoelectric interfaces are evaluated. The article aims to fill gaps left by previous reviews and identify avenues for future research. Recommendations are given, for example, for electrode placement, sampling rate, segmentation, and classifiers. Four groups of applications where myoelectric interfaces have been adopted are identified: assistive technology, rehabilitation technology, input devices, and silent speech interfaces. The state-of-the-art applications in each of these groups are presented.Peer reviewe

    System training and assessment in simultaneous proportional myoelectric prosthesis control

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    Background Pattern recognition control of prosthetic hands take inputs from one or more myoelectric sensors and controls one or more degrees of freedom. However, most systems created allow only sequential control of one motion class at a time. Additionally, only recently have researchers demonstrated proportional myoelectric control in such systems, an option that is believed to make fine control easier for the user. Recent developments suggest improved reliability if the user follows a so-called prosthesis guided training (PGT) scheme. Methods In this study, a system for simultaneous proportional myoelectric control has been developed for a hand prosthesis with two motor functions (hand open/close, and wrist pro-/supination). The prosthesis has been used with a prosthesis socket equivalent designed for normally-limbed subjects. An extended version of PGT was developed for use with proportional control. The control system’s performance was tested for two subjects in the Clothespin Relocation Task and the Southampton Hand Assessment Procedure (SHAP). Simultaneous proportional control was compared with three other control strategies implemented on the same prosthesis: mutex proportional control (the same system but with simultaneous control disabled), mutex on-off control, and a more traditional, sequential proportional control system with co-contractions for state switching. Results The practical tests indicate that the simultaneous proportional control strategy and the two mutex-based pattern recognition strategies performed equally well, and superiorly to the more traditional sequential strategy according to the chosen outcome measures. Conclusions This is the first simultaneous proportional myoelectric control system demonstrated on a prosthesis affixed to the forearm of a subject. The study illustrates that PGT is a promising system training method for proportional control. Due to the limited number of subjects in this study, no definite conclusions can be drawn

    A quantitative taxonomy of human hand grasps

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    Background: A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and thus they are usually not quantitatively justified. Methods: This paper presents to the best of our knowledge the first quantitative taxonomy of hand grasps based on biomedical data measurements. The taxonomy is based on electromyography and kinematic data recorded from 40 healthy subjects performing 20 unique hand grasps. For each subject, a set of hierarchical trees are computed for several signal features. Afterwards, the trees are combined, first into modality-specific (i.e. muscular and kinematic) taxonomies of hand grasps and then into a general quantitative taxonomy of hand movements. The modality-specific taxonomies provide similar results despite describing different parameters of hand movements, one being muscular and the other kinematic. Results: The general taxonomy merges the kinematic and muscular description into a comprehensive hierarchical structure. The obtained results clarify what has been proposed in the literature so far and they partially confirm the qualitative parameters used to create previous taxonomies of hand grasps. According to the results, hand movements can be divided into five movement categories defined based on the overall grasp shape, finger positioning and muscular activation. Part of the results appears qualitatively in accordance with previous results describing kinematic hand grasping synergies. Conclusions: The taxonomy of hand grasps proposed in this paper clarifies with quantitative measurements what has been proposed in the field on a qualitative basis, thus having a potential impact on several scientific fields
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