Optimal functional outcomes after bionic reconstruction in patients with global brachial plexus injury depend on a structured rehabilitation protocol. Surface electromyographic guided training may improve the amplitude, separation and consistency of EMG signals, which – after elective amputation of a functionless hand – control and drive a prosthetic hand.
In patients with global brachial plexus injury and lack of biological treatment alternatives, bionic reconstruction, including the elective amputation of the functionless hand and its replacement with a prosthesis, has recently been described. Optimal prosthetic function depends on a structured rehabilitation protocol, as residual muscle activity in a patient’s arm is later translated into prosthetic function. Surface electromyographic (sEMG) biofeedback has been used during rehabilitation after stroke, but has so far not been used in patients with complex peripheral nerve injuries. Here, we present our rehabilitation protocol implemented in patients with global brachial plexus injuries suitable for bionic reconstruction, starting from identification of sEMG signals to final prosthetic training. This structured rehabilitation program facilitates motor relearning, which may be a cognitively debilitating process after complex nerve root avulsion injuries, aberrant re-innervation and extra-anatomical reconstruction (as is the case with nerve transfer surgery). The rehabilitation protocol using sEMG biofeedback aids in the establishment of new motor patterns as patients are being made aware of the advancing re-innervation process of target muscles. Additionally, faint signals may also be trained and improved using sEMG biofeedback, rendering a clinically "useless" muscle (exhibiting muscle strength M1 on the British Medical Research Council [BMRC] scale) eligible for dexterous prosthetic hand control. Furthermore, functional outcome scores after successful bionic reconstruction are presented in this article.
Global brachial plexus injuries including the traumatic avulsion of nerve roots from the spinal cord represent one of the most severe nerve injuries in humans and usually affect young, otherwise healthy patients in the prime of life1,2. Depending on the number of nerve roots avulsed, complete upper limb paralysis may ensue since the nerval connection from the brain to the arm and hand is disrupted. Traditionally, the avulsion of nerve roots has been associated with poor outcomes3. With microsurgical nerve techniques gaining ground within the last decades, surgical results have been improved and useful motor function in the shoulder and elbow are usually restored4,5. The intrinsic musculature in the hand, which lies most distally, typically undergoes fatty degeneration resulting in irreversible atrophy before regenerating axons may reach it6. For such cases bionic reconstruction, which includes the elective amputation of the functionless "plexus" hand and its replacement with a mechatronic hand, has been described7,8. Residual muscle activity in a patient's forearm, which may be clinically insignificant (isometric contractions, M1 on the British Medical Research Council [BMRC] scale), is picked up from transcutaneous electrodes sensing electromyographic activity, which is then translated into various movements of a prosthetic hand9.
Enough surface electromyographic (sEMG) signals may be present upon initial consultation. In some cases, however, additional signals need to be established performing selective nerve and muscle transfers7. In either case, a structured rehabilitation protocol is needed to ensure sEMG signal consistency and subsequent optimal prosthetic function at the end of the process. A major challenge following nerve root avulsion and aberrant re-innervation as well as after nerve transfer surgery is the establishment of new motor patterns to allow volitional control over the target muscle. sEMG biofeedback methods have been widely used in the rehabilitation of stroke10. This method allows direct visualization of muscular activity that would otherwise be unnoticed due to muscular weakness and/or co-activation of antagonists. It thereby encourages patients to train their weak muscles, while providing precise feedback on the correct execution of motor tasks11.
In a recent publication we have shown for the first time that sEMG biofeedback may also be used in the rehabilitation of complex peripheral nerve injuries12. We believe that sEMG biofeedback is an extremely useful method to make a patient aware of the advancing re-innervation process after nerve transfer surgery. Also, faint muscle activity, which formerly was of no use to the patient, may be trained and strengthened for later prosthetic control using sEMG biofeedback, which allows concrete visualization of otherwise unnoticed muscle activity to both clinician and patient. The training progress may therefore be well comprehended and documented. Additionally, the use of direct feedback on muscle activity allows the clinician to correlate various motor commands with the associated signal amplitude and consistency, establishing the best motor strategies to allow robust prosthetic control in the future. In summary, the goal of this method is to facilitate the rehabilitation process by increasing a patient’s understanding, awareness and control of his/her sEMG signals, which will later drive a prosthetic hand.
The clinical implementation of this rehabilitation protocol was approved by the ethics committee of the Medical University of Vienna (ethical vote number: 1009/2014), Austria and carried out in accordance with the standards set by the Declaration of Helsinki. All patients provided written informed consent to participating in this study.
NOTE: Previous publications by Aszmann et al.7 and Hruby et al.8,13 are available describing the concept, treatment algorithm, and psychosocial prerequisites regarding bionic reconstruction in great detail. Table of Materials references all materials and equipment used in the proposed rehabilitation protocol.
1. Patient assessment upon initial consultation
2. Identification of sEMG signals
Figure 1: Screenshot of EMG signals on a computer screen.
To identify EMG activity, two or more electrodes can be placed on a patient's forearm asking him/her to attempt various movements. In this specific case, the electrode on the volar aspect of the forearm senses EMG activity as reflected by the first, red wave displayed on the computer screen, when the patient attempts to close his/her hand. Signal separation in this patient is satisfying, since the blue signal, which corresponds to the second electrode placed on the dorsal aspect of the forearm, does not reach the threshold. When the patient thinks of opening the hand, the amplitude of the blue signal exceeds the threshold, while the red signal remains almost inactive. Please click here to view a larger version of this figure.
3. sEMG-guided signal training
NOTE: The training sessions for sEMG-guided signal training should not exceed 30 min as this leads to muscle fatigue, which is hindering successful motor learning. The described steps need to be repeated over an extended period of time to ensure good neuromuscular coordination as needed later for reliable prosthetic control.
Figure 2: sEMG-guided rehabilitation for patients with bionic hand reconstruction.
(A) With direct visualization of muscle activity, various motor commands may be attempted to identify the highest EMG amplitude over a specific target muscle and different signal positions can be compared. (B) Using a table top prosthesis, the EMG activity in a patient’s arm is directly translated into prosthetic function. (C) The fitting of a hybrid prosthetic hand allows the patient to visualize and comprehend future prosthetic hand use. (D) After prosthetic reconstruction, EMG signals can be trained and optimized either with sEMG biofeedback or with the prosthetic hand itself. This figure has been modified from Sturma et al.12 and reproduced with permission from Frontiers in Neuroscience. Please click here to view a larger version of this figure.
Figure 3: Patient in front of a table top prosthesis and screenshot of his two signals on a computer screen.
On the patient's forearm, two electrodes sense EMG activity. These two signals are displayed as color-coded graphs on the computer screen (red and blue) and are simultaneously translated into prosthetic movement, allowing the patient to comprehend the relationship between signal quality and prosthetic control. Please click here to view a larger version of this figure.
4. Hybrid hand fitting and prosthetic training
5. Elective amputation and prosthetic hand replacement
Figure 4: Example of a possible prosthesis and socket design.
(A) This patient's prosthesis consists of an outer sheath made of carbon. (B) Instead of a prosthetic hand, the patient prefers to use a hook, which opens and closes, as a grasping tool. (C,D) The two electrodes are integrated in the prosthesis. The patient wears a silicone liner with two holes in it, allowing direct skin contact with the two electrodes (not shown). Please click here to view a larger version of this figure.
In six patients with severe brachial plexus injuries including multiple nerve root avulsions the presented rehabilitation protocol using sEMG biofeedback was successfully implemented. Detailed patient characteristics can be found in Table 1. Figure 2 demonstrates the various phases of the structured rehabilitation protocol and detailed explanations on its implementation.
To demonstrate improvements in hand function before and after bionic reconstruction, a standardized assessment evaluating global upper extremity function was performed at two time points: before elective amputation of the functionless "plexus" hand as well as after successful prosthetic reconstruction and rehabilitation. The Action Research Arm test (ARAT) was originally developed to assess global upper extremity motor function in patients with cognitive impairment of hand control16. The standardized approach of Yozbatiran et al.17 was used in our studies. The ARAT consists of four different sections, which include tasks close to daily living. The test is timed by the observer who also rates the task performance from 0−3, with 3 indicating normal function. A maximum of 57 points is attainable indicating unimpaired motor function16. The number of therapy sessions with sEMG biofeedback and detailed results for each patient can be found in Table 2.
Although patient satisfaction with the offered rehabilitation protocol using sEMG biofeedback was not directly measured, all six patients reported to find it extremely helpful in comprehending the re-innervation process following nerve transfer surgery and to train the contraction of muscles with very faint activity that formerly was of no clinical use to them.
Case number | Sex, age (years) | Type of accident | Type of lesion | Surgeries to improve biotechnological interface after initial reconstructions have failed to improve hand function | |
1 | m, 32 | Fall from height | Avulsion of C7−T1; traction injury of the infraclavicular plexus | Elective amputation of the forearm | |
2 | m, 32 | Motorcycle accident | Rupture of all 3 trunci of the BP | Free gracilis muscle transferred to forearm extensor compartment & neurotization of deep branch of radial nerve to obturator nerve; elective amputation of the forearm | |
3 | m, 55 | Motorcycle accident | Avulsion of C5−T1 | Elective amputation of the upper arm | |
4 | m, 38 | Motorcycle accident | Extensive damage to roots C5−C8; avulsion of T1 | Elective amputation of the forearm | |
5 | m, 27 | Motorcycle accident | Avulsion C8−T1 | Elective amputation of the forearm | |
6 | m, 43 | Motorcycle accident | Avulsion of C6−T1 | Transfer of triceps muscle to infraspinatous fossa and transfer of biceps muscle to supraclavicular fossa to improve prosthetic fitting; Elective amputation of the arm (shoulder exarticulation) |
Table 1: Patient characteristics. In all patients, bionic reconstruction was initiated due to infeasibility of biological treatment alternatives. Surgeries to establish EMG signals in the fore- and upper arm may include selective nerve and muscle transfers, which will then drive a myoelectric prosthetic hand. Elective amputation is either performed at a transradial or transhumeral level, depending on the residual muscle activity. All selective nerve transfers performed in this patient group were successful. This table has been modified from Sturma et al.12 and reproduced with permission from Frontiers in Neuroscience.
Case number | ARAT at baseline | ARAT at follow-up | Start of sEMG training | Number of therapy sessions in total (30 min each) | |
1 | 7 | 35 | Immediately after first consultation | 24 | |
2 | 0 | 15 | Training with one signal immediately after first consultation; second signal was available 9 months after free gracillis transfer + nerve transfer | 30 | |
3 | 0 | 19 | Immediately after first consultation | 16 | |
4 | 1 | 22 | Immediately after first consultation | 20 | |
5 | 9 | 42 | Immediately after decision to aim for a bionic reconstruction as biologic reconstruction failed | 20 | |
6 | 0 | 17 | Immediately after first consultation | 22 | |
Mean (± SD) | 2.83 ± 4.07 | 25.00 ± 10.94 | 22 ± 4.32 |
Table 2: ARAT scores and number of therapy sessions. In the Action Research Arm test (ARAT), patients initially showed negligible upper limb function (mean 2.83, of a maximum of 57 points attainable). Useful function was restored after bionic reconstruction (mean 25.00, of 57). This table has been modified from Sturma et al.12 and reproduced with permission from Frontiers in Neuroscience.
Biofeedback approaches have been widely used in the rehabilitation of several neuromuscular disorders, ranging from (hemi)-plegic conditions resulting from central pathologies such as brain hemorrhage and stroke18,19 to various musculoskeletal degeneration or injury and their surgical therapy20,21,22. Interestingly, the concept of structured biofeedback has not been implemented in clinical practice for peripheral nerve injuries. However, precisely in the rehabilitation of complex nerve injuries, practice, repetition, and structured training programs with appropriate biofeedback are necessary to establish correct motor patterns23.
Here, and in a previous study12, we presented a structured rehabilitation protocol using sEMG biofeedback for patients with lack of biological treatment alternatives eligible for prosthetic hand replacement, a concept today known as bionic reconstruction. The most apparent advantage of using a sEMG biofeedback set-up in the context of bionic reconstruction arises from the exact definition of sEMG hotspots, i.e., skin locations, where a relatively high amplitude of EMG activity can be measured transcutaneously. Various motor commands may be attempted alternately, as the sensors can easily be moved along the entire forearm, and – in case of missing detectable muscle function in the forearm – also in the upper arm and shoulder girdle. When a patient is asked to attempt to contract the muscles intended to perform a specific action (such as extending the wrist), an electrode can be placed, where (weak) muscle contraction is palpated by the examiner. Observing the EMG signal on the computer screen, one can easily determine whether the signal's amplitude consistently increases, when the patient attempts to contract this muscle. If the amplitude is not high enough or the signal is inconsistent, other motor commands with the same electrode position may be attempted. As oppose to needle EMG, this procedure is non-invasive, not painful and can be repeated for all muscles/muscle groups in the arm. Testing various motor commands at different muscle locations allows to identify the EMG hotspots, with the highest amplitude and reproducible activity associated with a specific motor action. After identification of the strongest EMG signals, these may be trained using sEMG biofeedback with regards to signal separation (co-activation of two or more EMG signals must not occur on the computer screen), signal strength (reflected by the EMG signal’s amplitude on the computer screen) and signal reproducibility (each attempt to contract the muscle must lead to an excursion of the respective EMG signal). At a later stage of training, EMG activity is directly translated into prosthetic function, first using a table top prosthesis (see Figure 3), which gives additional feedback to the patient allowing fine-tuning of grip strength, and then wearing the physical prosthesis.
In conventional amputees, a vast amount of literature has shown that targeted-muscle-reinnervation (TMR), i.e., the surgical transfer of residual arm nerves to alternative muscle sites in the chest and upper-arm, improves prosthetic function, since these re-innervated muscles serve as biological amplifiers of intuitive motor commands and provide physiologically appropriate EMG signals for prosthetic hand, wrist and elbow control24,25,26,27. Using pattern-recognition control systems, EMG data extracted from numerous sEMG signals placed over the skin of these re-innervated muscles can be decoded and translated to specific, reproducible motor outputs, which provides more reliable myoelectric prosthesis control28,29,30. Because the number of EMG signal sites and the myoelectric activity of the muscles in patients with brachial plexus avulsion injury are very limited, pattern recognition algorithms may not be used as is done for conventional amputees8. Still, with further research and improved technology, these systems may be able to extract more information on the existing faint muscle signals and therefore improve prosthetic function also in this peculiar patient group.
While the presented protocol is considered a guideline, details need to be adapted depending on the patient and the available equipment. Due to aberrant re-innervation occurring after such nerve injuries, motor commands do not necessarily result in the activation of anatomically “correct” muscles12. For example, the authors observed EMG activity at the forearm flexor compartment, while patients were attempting to open their hand. Therefore, various motor commands should be tested in order to identify EMG signals. Additionally, the residual muscular function (although in all cases too weak to generate useful hand movements) might largely vary across patients and cause variations in the required training time as shown in Table 2. Further, the choice of the prosthetic device and the number of electrodes used for control change the requirements for the precision of signal separation, the signal amplitude and the need of co-contraction. All of this needs to be taken into account during signal training, hybrid prosthesis training and actual prosthetic training, as it is also recommended in standard prosthetic training of amputees31. Regarding the devices used for sEMG biofeedback training, the authors consider devices suitable if they can simultaneously display the number of signals needed for prosthetic control, give real-time feedback, and can be either connected to a computer or display the signals on a screen themselves. Devices that allow adjusting the signal gain during training are preferred.
After rehabilitation, all patients were able to use their prosthesis during daily life activities and were satisfied with the decision to have their functionless hand replaced with a prosthetic device12. This functional improvement was reflected by significant increases in the mean ARAT scores from 2.83 ± 4.07 to 25.00 ± 10.94 (p = 0.028).
From our perspective, sEMG biofeedback set-ups present valuable tools to facilitate the cognitively demanding process of motor recovery associated with nerve injury and bionic reconstruction. The identification of optimal EMG electrode positioning and the testing of various motor commands with direct visualization of muscle activity is greatly simplified using sEMG biofeedback in a clinical set-up. Although sEMG biofeedback may also be used in the rehabilitation of biological upper limb function10,12, its application in the process of bionic reconstruction is considered particularly effective. Most importantly, the sEMG signals activated during training later reflect the electrode positions within the prosthetic socket, which is individually customized for each patient. Therefore, repetitive activation of these signals during training most likely increases future prosthetic handling and manual capacity. Direct visualization of this muscle activity also allows a patient to comprehend the concept of myoelectric hand control and he/she may follow the training progress more consciously.
In the future, our presented rehabilitation protocol might be extended with more advanced tools to enhance functional outcomes. This might include high density sEMG recordings to facilitate the process of electrode placement via activation heat maps32, further virtual solutions to evaluate EMG activity30,33, and serious games to enhance training motivation34. Additionally, novel technologies for prosthetic control, such as pattern recognition algorithms might also be used28,30,35. However, due to the reduced neuro-muscular interface, it is not clear whether currently commercially available systems designed for otherwise healthy amputees would significantly improve prosthetic function in this specific patient group. Future studies should evaluate the applicability and benefits of the listed novel technologies for the rehabilitation of patients with severe brachial plexus injuries. Additionally, controlled trials with higher patient numbers will also allow to demonstrate the positive effects of the current protocol using sEMG biofeedback with a higher level of evidence.
The authors have nothing to disclose.
This study was funded by the Christian Doppler Research Foundation of the Austrian Council for Research and Technology Development and the Austrian Federal Ministry of Science, Research and Economy. We are grateful to Aron Cserveny for preparation of the illustrations included in the manuscript and to Frontiers in Neuroscience for permission of reproducing the data presented in the original article12.
dry EMG electrodes | Ottobock Healthcare, Duderstadt, Germany | 13E202 = 50 | The EMG electrodes used in this study were bipolar and included a ground. They can be used both for EMG training with the Myoboy and for the control of a prosthetic device. |
Myoboy | Otto bock Healthcare, Duderstadt, Germany | Myoboy | This device that can be used as stand alone device or with a computer. It allows to display EMG activity while using the dry EMG electrodes that can also be impeded in the prosthetic socket. |
SensorHand Speed | Ottobock Healthcare, Duderstadt, Germany | All patients used this commercially available myoelectrical prosthesis as their standard prosthetic device and during functional testing. Fitting of patients undergoing this procedure is, however, not restricted to this device. | |
Standard laptop with Microsoft operating system | Usually, devices for EMG biofeedback connected to a computer do not require much computing power and thus work on any regular laptop | ||
TeleMyo 2400T G2 | Noraxon, US | A surface EMG biofeedback set-up used in our protocol, connected to TeleMyo-Software, which displays the recorded EMG activity as color-coded graphs on the computer screen | |
wet EMG electrodes | Ambu | Ambu Blue Sensor VL Adhesive Electrodes | These adhesive electrodes can be used in combination with many different EMG biofeedback devices, including the TeleMyo 2400T. While they cannot be moved easily, the wet contacts usually allow to detect very faint EMG signals as well. |