An artificial grasping evaluation system for the paralysed hand

Castro, Maria Cláudia Ferrari de; A, Cliquet Júnior

doi:10.1007/bf02347047

Cited by 22 publications

(18 citation statements)

References 19 publications

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“…This issue can be addressed by developing closed-loop control algorithms based on the extraction of sensory information, and its use for correcting deviations caused by unexpected changes and non-linearities. Feedback information can be gathered by using implantable [8,9] or external [10,11] artificial sensors or by processing electroneurographic (ENG) signals recorded by means of implanted interfaces with the peripheral nerves of the subject [12]. In the latter case, the choice of the electrode will make a difference on the type of processing available based on the selectivity of the electrode and its placement.…”

Section: Introductionmentioning

confidence: 99%

On the identification of sensory information from mixed nerves by using single-channel cuff electrodes

Raspopović

Carpaneto

Udina

et al. 2010

J NeuroEngineering Rehabil

102

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BackgroundSeveral groups have shown that the performance of motor neuroprostheses can be significantly improved by detecting specific sensory events related to the ongoing motor task (e.g., the slippage of an object during grasping). Algorithms have been developed to achieve this goal by processing electroneurographic (ENG) afferent signals recorded by using single-channel cuff electrodes. However, no efforts have been made so far to understand the number and type of detectable sensory events that can be differentiated from whole nerve recordings using this approach.MethodsTo this aim, ENG afferent signals, evoked by different sensory stimuli were recorded using single-channel cuff electrodes placed around the sciatic nerve of anesthetized rats. The ENG signals were digitally processed and several features were extracted and used as inputs for the classification. The work was performed on integral datasets, without eliminating any noisy parts, in order to be as close as possible to real application.ResultsThe results obtained showed that single-channel cuff electrodes are able to provide information on two to three different afferent (proprioceptive, mechanical and nociceptive) stimuli, with reasonably good discrimination ability. The classification performances are affected by the SNR of the signal, which in turn is related to the diameter of the fibers encoding a particular type of neurophysiological stimulus.ConclusionsOur findings indicate that signals of acceptable SNR and corresponding to different physiological modalities (e.g. mediated by different types of nerve fibers) may be distinguished.

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Section: Introductionmentioning

confidence: 99%

On the identification of sensory information from mixed nerves by using single-channel cuff electrodes

Raspopović

Carpaneto

Udina

et al. 2010

J NeuroEngineering Rehabil

102

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“…For individuals that suffer Spinal Cord Injury (SCI), a technique that has contributed for rehabilitation is Functional Electrical Stimulation (FES) (Castro and Cliquet Jr., 2000). FES treatment may be associated with dynamic suspension (Field-Fote, 2001).…”

Section: Gait Analysismentioning

confidence: 99%

Development of an Alternative System for Suspended Gait Analysis

Lima¹,

Cliquet²

2008

Proceedings of the First International Conference on Biomedical Electronics and Devices

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Spinal Cord Injury (SCI) may impair an individual's gait. For these cases, a rehabilitation technique that has become more popular is Functional Electrical Stimulation (FES). Gait analysis is an important technique to evaluate rehabilitation of patients undergoing FES-assisted therapy. This work proposes a system that monitors gait variables -knee joint angles, and ground reaction forces (heel and metatarsal) -and uses them as inputs for gait analysis of paraplegic patients. The methods for building the data acquisition hardware (transducers and interface) and software are described, along with the transducer calibration methods. The results show the final prototype for the gait analysis system, which allows comparison between different individuals' gaits, as well as different rehabilitation stages for the same individual. The software has a recording feature, as well as digital control outputs, which may be used in the future for training an Artificial Neural Network (ANN) and controlling the individual's FES stimulator. In the near future, the system may be of great applicability for suspended FES-assisted gait analysis and control.

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“…3 As a consequence, the study of the ability to grasp has been a permanent concern in biomechanics 4-7 and rehabilitation. [8][9][10] However, current assessment of hand function in clinical practice lacks a deep evaluation of the grasp ability. Some assessment methods are based in tests or scales that are usually validated for specific pathologies.…”

Section: Introductionmentioning

confidence: 99%

Relevance of grasp types to assess functionality for personal autonomy

Gracia-Ibáñez

Sancho-Bru

2018

Journal of Hand Therapy

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Study Design: Cross-sectional research design.Introduction: Current assessment of hand function is not focused on evaluating the real abilities required for autonomy.Purpose of the Study: To quantify the relevance of grasp types for autonomy in order to guide hand recovery and its assessment.Methods: Representative tasks of the ICF-activities in which the hands are directly involved were recorded. The videos were analysed to identify the grasps used with each hand, and their relevance for autonomy was determined weighting time with the frequency of appearance of each activity in disability and dependency scales. Relevance is provided, globally and distinguishing by hand (right-left) and bimanual function. Significant differences in relevance are also checked.Results: The most relevant grasps are pad to pad pinch (31.9%), lumbrical (15.4%), cylindrical (12%), and special pinch (7.3%) together with the non-prehensile (18.6%) use of the hand. Lumbrical grasp has higher relevance for the left hand (19.9% vs. 12%) while cylindrical grasp for the right hand (15.3% vs. 7.7%). Relevancies are also different depending on bimanual function. Discussion: Different relative importance was obtained when considering dependency versus disability scales. Pad to pad pinch and non-prehensile grasp are the most relevant for both hands, while lumbrical grasp is more relevant for the left hand and cylindrical grasp for the right one. The most significant difference in bimanual function refers to pad to pad pinch (more relevant for unimanual actions of the left hand and bimanual actions of the right).

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An artificial grasping evaluation system for the paralysed hand

Cited by 22 publications

References 19 publications

On the identification of sensory information from mixed nerves by using single-channel cuff electrodes

On the identification of sensory information from mixed nerves by using single-channel cuff electrodes

Development of an Alternative System for Suspended Gait Analysis

Relevance of grasp types to assess functionality for personal autonomy

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