scholarly journals Extra-Neural Signals From Severed Nerves Enable Intrinsic Hand Movements In Transhumeral Amputations

Author(s):  
Bahareh Ahkami ◽  
Enzo Mastinu ◽  
Eric Earley ◽  
Max Ortiz-Catalan

Abstract Robotic prostheses controlled by myoelectric signals can restore limited but important hand function in individuals with upper limb amputation. The lack of individual finger control highlights the yet insurmountable gap to fully replace a biologic hand. Implanted electrodes around severed nerves have been used to elicit sensations perceived as arising from the missing limb, but using such extra-neural electrodes to record motor signals that allow for the decoding of phantom movements has remained elusive. Here, we showed the feasibility of using signals from non-penetrating neural electrodes to decode intrinsic hand and finger movements in individuals with above-elbow amputations. We found that information recorded with extra-neural electrodes alone was enough to decode phantom hand and individual finger movements with high accuracy, and as expected, the addition of myoelectric signals reduced classification errors both in offline and in real-time decoding.

Author(s):  
Dimitra Blana ◽  
Antonie J. Van Den Bogert ◽  
Wendy M. Murray ◽  
Amartya Ganguly ◽  
Agamemnon Krasoulis ◽  
...  

2020 ◽  
Vol 132 (5) ◽  
pp. 1358-1366
Author(s):  
Chao-Hung Kuo ◽  
Timothy M. Blakely ◽  
Jeremiah D. Wander ◽  
Devapratim Sarma ◽  
Jing Wu ◽  
...  

OBJECTIVEThe activation of the sensorimotor cortex as measured by electrocorticographic (ECoG) signals has been correlated with contralateral hand movements in humans, as precisely as the level of individual digits. However, the relationship between individual and multiple synergistic finger movements and the neural signal as detected by ECoG has not been fully explored. The authors used intraoperative high-resolution micro-ECoG (µECoG) on the sensorimotor cortex to link neural signals to finger movements across several context-specific motor tasks.METHODSThree neurosurgical patients with cortical lesions over eloquent regions participated. During awake craniotomy, a sensorimotor cortex area of hand movement was localized by high-frequency responses measured by an 8 × 8 µECoG grid of 3-mm interelectrode spacing. Patients performed a flexion movement of the thumb or index finger, or a pinch movement of both, based on a visual cue. High-gamma (HG; 70–230 Hz) filtered µECoG was used to identify dominant electrodes associated with thumb and index movement. Hand movements were recorded by a dataglove simultaneously with µECoG recording.RESULTSIn all 3 patients, the electrodes controlling thumb and index finger movements were identifiable approximately 3–6-mm apart by the HG-filtered µECoG signal. For HG power of cortical activation measured with µECoG, the thumb and index signals in the pinch movement were similar to those observed during thumb-only and index-only movement, respectively (all p > 0.05). Index finger movements, measured by the dataglove joint angles, were similar in both the index-only and pinch movements (p > 0.05). However, despite similar activation across the conditions, markedly decreased thumb movement was observed in pinch relative to independent thumb-only movement (all p < 0.05).CONCLUSIONSHG-filtered µECoG signals effectively identify dominant regions associated with thumb and index finger movement. For pinch, the µECoG signal comprises a combination of the signals from individual thumb and index movements. However, while the relationship between the index finger joint angle and HG-filtered signal remains consistent between conditions, there is not a fixed relationship for thumb movement. Although the HG-filtered µECoG signal is similar in both thumb-only and pinch conditions, the actual thumb movement is markedly smaller in the pinch condition than in the thumb-only condition. This implies a nonlinear relationship between the cortical signal and the motor output for some, but importantly not all, movement types. This analysis provides insight into the tuning of the motor cortex toward specific types of motor behaviors.


2020 ◽  
Vol 1 ◽  
Author(s):  
Youngmok Yun ◽  
Youngjin Na ◽  
Paria Esmatloo ◽  
Sarah Dancausse ◽  
Alfredo Serrato ◽  
...  

Abstract We have developed a one-of-a-kind hand exoskeleton, called Maestro, which can power finger movements of those surviving severe disabilities to complete daily tasks using compliant joints. In this paper, we present results from an electromyography (EMG) control strategy conducted with spinal cord injury (SCI) patients (C5, C6, and C7) in which the subjects completed daily tasks controlling Maestro with EMG signals from their forearm muscles. With its compliant actuation and its degrees of freedom that match the natural finger movements, Maestro is capable of helping the subjects grasp and manipulate a variety of daily objects (more than 15 from a standardized set). To generate control commands for Maestro, an artificial neural network algorithm was implemented along with a probabilistic control approach to classify and deliver four hand poses robustly with three EMG signals measured from the forearm and palm. Increase in the scores of a standardized test, called the Sollerman hand function test, and enhancement in different aspects of grasping such as strength shows feasibility that Maestro can be capable of improving the hand function of SCI subjects.


Author(s):  
Arthur Prochazka

About 2% of people have weak or paralysed upper limbs (ULs) due to stroke or spinal cord injury (SCI). Physiotherapy involving exercise can improve motor function in many such cases, but the time and resources required are often unavailable. Adherence to repeated intensive exercise tends to decline, especially after participants leave the clinical environment. There is a need for technology that can restore neuromuscular control and improve motivation by making exercise therapy enjoyable, and that extends the therapy into the home with the use of remote communication (e.g. ‘tele-coaching’). Over the last 20 years many devices have been developed and tested. Neuroprostheses (NPs) that activate UL muscles with functional electrical stimulation (FES) either via surface or implanted electrodes are now commercially available or in clinical trials. The use of robotic devices to enhance exercise therapy has been an active area of research and development. Recent studies indicate that improvements in motor function depend largely on the efforts made by the participant. This chapter reviews conventional exercise therapy, FES, and robotic and passive exercise devices that improve motor function and enhance engagement in UL rehabilitation. It is suggested that important developments in the next few years will include the widespread availability of affordable FES and in-home exercise devices, and the gradual adoption of tele-coaching over the internet.


2020 ◽  
Vol 58 ◽  
pp. 101834 ◽  
Author(s):  
Maria V. Arteaga ◽  
Jenny C. Castiblanco ◽  
Ivan F. Mondragon ◽  
Julian D. Colorado ◽  
Catalina Alvarado-Rojas

Author(s):  
Siddhartha Sikdar ◽  
Huzefa Rangwala ◽  
Emily B. Eastlake ◽  
Ira A. Hunt ◽  
Andrew J. Nelson ◽  
...  

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6170
Author(s):  
Weichen Wei ◽  
Xuejiao Wang

The neural electrode technique is a powerful tool for monitoring and regulating neural activity, which has a wide range of applications in basic neuroscience and the treatment of neurological diseases. Constructing a high-performance electrode–nerve interface is required for the long-term stable detection of neural signals by electrodes. However, conventional neural electrodes are mainly fabricated from rigid materials that do not match the mechanical properties of soft neural tissues, thus limiting the high-quality recording of neuroelectric signals. Meanwhile, graphene-based nanomaterials can form stable electrode–nerve interfaces due to their high conductivity, excellent flexibility, and biocompatibility. In this literature review, we describe various graphene-based electrodes and their potential application in neural activity detection. We also discuss the biological safety of graphene neural electrodes, related challenges, and their prospects.


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