The effectiveness of surfaced-EMG controlled robot-assisted therapy in hand recovery after stroke

Authors: Diana Sipos-Lascu, Oana-Maria Vanța

Keywords:  robot-assisted therapy, surface electromyography, hand recovery, stroke rehabilitation

What is the effectiveness of surfaced-EMG controlled robot-assisted therapy in hand recovery after stroke?

Neurorehabilitation is an essential element in patients` recovery after a stroke. In order to plan the best therapeutic efforts for restoring function, understanding post-stroke upper limb impairment is crucial. The upper limb impairment approach is challenging, as the impairments are not static; their type and nature may change, making it necessary to evolve the treatment to target the dysfunction at a given point in time.

Moreover, multiple impairments may coincide or layer over time, making it challenging to decide what to treat in the first place. A key consideration in therapy may be deciding which impairment contributes the most to the dysfunctional status of the patient [1]. Persistent difficulty using the upper limb significantly contributes to disability after stroke.

To lessen the severity of this disability, neurorehabilitation programs now give qualified patients high-dose, high-quality, and high-intensity upper limb rehabilitation. These programs concluded that the clinically meaningful differences in measures of activity and disability in chronic stroke patients could change. Additionally, clinical improvement persisted throughout the six-month follow-up period [2]. Moreover, according to data, a higher dose of an intervention is preferable to a smaller one [3].

Even though the number of stroke-related deaths per 100,000 population has decreased over the past 50 years, stroke continues to be a leading cause of long-term severe disability. 

In addition, there is also a need to consider the economic pressure for limiting the duration of the rehabilitation process, which leads to an increased interest in using robotic-assisted therapies (RAT) to enhance the efficiency and efficacy of post-stroke rehabilitation [4]. The most important characteristics of RAT have yet to be identified, creating a barrier to their economical design and optimization [3]. In clinical trials evaluating the RAT for upper limb rehabilitation, there were wide variations regarding:

• Protocols
• Timing
• Amount of training
• Manipulated segments [4].

The efficacy of the RAT in walking and arm rehabilitation after stroke has been proven by several studies [5]. Unfortunately, the high expenses of these robots limit their diffusion in clinical practice. The fundamental objective of RAT is to increase brain plasticity by offering the greatest possible amount of stimuli [6].

The AMADEO robot intervention

In this particular Italian pilot trial, finger flexion and extension were improved by treatment with the AMADEO robot. In order to evaluate the rehabilitation provided by this robot and enhanced by surface electromyography  (sEMG), it used a before-after study design. Ten post-stroke patients were enrolled in the study, out of which eight had ischemic strokes and two had hemorrhagic events [6]. Eight males and two females made up the group, and the following areas of the brain were damaged:

• Parietal lobe
• Posterior-right temporal bulbar tract
• Right-side spinal cord bulbs
• Lenticular nucleus
• Thalamus
• Temporo-parietal region
• Central and temporal arteries [6].

The included patients’ ages ranged from 53 to 81 years,  all already in the chronic phase [6].

Patients with either ischemic or hemorrhagic stroke at least two years prior to beginning AMADEO therapy were included. The study excluded participants with spasticity, severe injuries, retractions, motor aphasia, apraxia, malignant tumors, epilepsy,  hemianopia, or skin lesions close to the electrode placement sites [6].

RAT  described using the AMADEO and sEMG

 The novel aspect of this study is the use of surface electrodes to acquire real-time EMG signals from the finger flexors and extensor, active and assisted exercises being applied in patients with no finger movements.

Several clinical scales were implemented before and after therapy with AMADEO:

• Fugl-Meyer test for the upper limb (FM) – assesses wrist and hand functioning. coordination and movement speed
•  Box and Block test – measures two-sided manual efficiency
• Nine Hole PegTest (NHPT)– evaluates hand function and determines finger dexterity.

Patients were evaluated to determine whether they could overcome resistance caused by the fingers’ disrupted flexion and extension movements while maintaining muscle activity.

All of these patients underwent at least 15 treatment sessions of 30 minutes each, with the AMADEO robot  (Tyromotion GmbH Graz, Austria), surface electrodes being placed on the flexor digitorum profundus, extensor digitorum and extensor digiti minimi of the fingers, enabling this way the reading of the electromyographic signal from surface electrodes (sEMG) (see Figure 1).

Fig 1. The placement of the electrodes on the flexors and extensors of the right-hand fingers.Available from [6].

Description of the therapy sessions  by using  the AMADEO robot and sEMG

The time required to prepare and safeguard the patient and the robot for one therapy session with the AMADEO robot was roughly one hour. The patient was seated opposite the robot in a comfortable but correct position, and magnets were placed on the fingers and connected to the robot’s mobile units (see Figure 2).

Figure 2. Magnet placement during a therapy session, available from [6].

Firstly, the subject’s wrist was immobilized in the neutral position, and the elbow joint was flexed at 90°. The physiotherapist measured the fingers’ range of motion (ROM) at the beginning of the therapy. Depending on the changes occurring within the session, the ROM was modified, and the EMG amplifier was used to calibrate the robot.

The threshold of muscle activity was established after reading the baseline signal – an important procedure enabling the determination of the stimulation threshold, typically 30% of the greatest value attained during an intentional muscular contraction. The robot’s efficacy is determined by whether this value is exceeded, as the robot does not move until the right stimulus is generated. As a result, calibration is a vital component of therapy. Subjects without active hand movement could participate in the treatment described because of the use of sEMG ( see Figure 3) [6].

Figure 3. Extensor and flexor EMG icon calibration: sustained muscular nerve activity (green) and absence of force production (red for the Extensor and Flexor Force icons), available from [6].

• The first stage of the therapy (the warm-up phase) was aimed at patient customization with the robot. The patient did not need to exert any physical effort or attention to the movement. 
• In contrast, the patient engaged their extensors and flexors during the second stage. Even though the two stages seem comparable, the patient had to use the EMG signal to control the finger flexors in the second stage and the extensors in the first. On the other hand, the robot made passive return motions. Following that, vigorous finger flexor movements were made (flexor control). 
• Further on, during the third stage, the robot controlled the extensor muscles while passively flexing the subject’s fingers, assisting the patients in finishing the movements. At this point, regardless of whether the opposing group of muscles was also stimulated simultaneously, the production of muscular tension that exceeds the threshold to commence movement is the single factor affecting the initiation of movement. This happens to get the patient ready for later therapy phases where isolated mobility is preferred. The number of completed repetitions was automatically counted.  
• The following stage encompassed the control of both finger extensor and flexor muscle groups. Flexion and extension phases both require the patient to make independent motions. 
• Next, the protocol used EMG threshold-based control. At this step, the patient had to produce a signal that was stronger than the baseline, but in contrast to earlier phases, the robot did not start the motion after sensing just one impulse. To finish the directed motor job, there has to be constant tension in the muscles. 
• Control of the difference in electromyographic signal was the training’s last stage (EMG difference-based control). At this point, the patient was instructed to regulate the isolated flexion and extension of the fingers so that there was a minimum 10% difference in extensor activity compared to flexor activity. 

The stages show a closed-loop paradigm that starts when the patient tenses muscles while concentrating on doing a particular motor activity. The patient’s hand’s position is now altered as a result of the stimulus correctly processed by the sEMG at this time. The patient who witnesses the movement receives feedback from the movement that was initiated. Robotic hand movement gives sensory feedback directly tied to changes in the location of the upper limb’s distal end.

Through the signal intensity values displayed on the monitor, the patient may feel the change in hand position and keep track of it. The patient can better develop muscle control thanks to visual input that depicts muscle strength. With the start of a new movement and when enhanced with knowledge of earlier movements, ending the closed-loop system  [6].

The robot

The AMADEO robot (Tyromotion GmbH, Graz, Austria) is a machine that can be used as an external manipulator for exercises involving the flexion and extension of the fingers. This robot offers carefully chosen training along with frequent, repetitive exercises specifically designed to strengthen grip strength. A physiotherapist decides the training regimen and modifies the difficulty of the exercises in conjunction with the visual cues shown on the monitor. From the patient’s perspective, the AMADEO robot assists in the flexion and extension of the fingers.

It features two transverse directing movements and four longitudinally moving units (for the thumb). Each mobile robot unit is self-contained and capable of practically unlimited movement. For each patient, the AMADEO robot’s parameters can be explicitly altered.

The physiotherapist modifies the complexity of the exercises based on the severity of the injury and disability. Through the execution of an appropriate movement pattern, passive exercises enable passive movement. The patient starts the active-assisted movements, which are finished by the robot. Rehabilitation is made possible for individuals with severe injuries and motor abnormalities that severely limit hand movement by integrating the sEMG signal with the AMADEO robot.

This contemporary combination can broaden the patient population that can use this technology. In this situation, the AMADEO robot’s purpose is to enhance the electrical signal produced by contracting muscles so that it can accurately depict neuromuscular activation. This is accomplished with the aid of the surface electrodes attached to the patient’s forearm, which send pulses to the amplifier. As a result, they are processed and sent to AMADEO. With the appropriate movement, sEMG provides straightforward access to the physiological mechanism that produces compressed muscle force. 

Fortunately, it is now possible to rehabilitate patients with intact nerve activity but insufficient muscular strength because the AMADEO robot’s EMG signal enables it to record even the faintest impulses signaling muscle activity. Because the physiotherapist successfully fixes the parameters, the robot cooperates by manipulating the fingers with little to no muscle activation (flexion and extension) [6].

Efficacy of AMADEO robot assisted by sEMG

Statistically significant improvement in upper limb function was demonstrated in the FM and Box and Block test groups, while the analysis of values from the Nine Hole Peg Test did not show any statistically significant improvement in hand motor ability[6]. These results indicate improvement in the upper limb function in the three used scales, the most significant improvement observed in the Box and Block test, exceeding 15%.  

Perspectives of using robot-assisted therapy

Scientific evidence also emphasizes the importance of brain plasticity in neurorehabilitation due to the possibility of cortical reorganization. The positive influence is visible in the case of early, intensive, and repetitive therapy as an optimal rehabilitation model, minimizing motor deficits and supporting motor re-education.

Treatment using the AMADEO robot assisted by sEMG is an innovative technique, focusing solely on improving hand function. The results obtained from the study of Dzieman Katharzyna et al. [6] indicate a general improvement of upper limb function by using RAT assisted by sEMG in post-stroke patients with severe motor hand deficits rehabilitation [6]. In conclusion, this modern combination offers the possibility to expand the patient group that can employ this technology, but a comparison study with targeted physiotherapy would be of great interest in the future.

For more information about neurorehabilitation, visit:

• Robotic neurorehabilitation for the upper limb – new insights
• Efficacy of placebo in managing pain for neurological disorders
• Neurorehabilitation in dystonia – a holistic approach 

We kindly invite you to browse our Interview category: https://efnr.org/category/interviews/. You will find informative discussions with renowned specialists in the field of neurorehabilitation.

References

1. Peter Raghavan. Upper Limb Motor Impairment After Stroke. Phys Med Rehabil Clin N Am. 2015;26(4):599-610. doi: 10.1016/j.pmr.2015.06.008. 
2. Nick S Ward, Fran Brander, Kate Kelli. Intensive upper limb neurorehabilitation in chronic stroke: outcomes from the Queen Square programme. Cerebrovascular disease. 2019 DOI: 10.1136/jnnp-2018-319954
3. Pollock A, Farmer SE, Brady MC, Langhorne Pet al. Interventions for improving upper limb function after stroke. Cochrane Database Syst Rev. 2014 ;2014(11):CD010820. doi: 10.1002/14651858.CD010820.pub2. 
4. Burgar CG, Peter S Lum, AM Erika Screning, Susan L et al. Robot-assisted upper-limb therapy in acute rehabilitation setting following stroke: Department of Veterans Affairs multisite clinical trial. J Rehabil Res Dev. 2011;48(4):445-58. doi: 10.1682/jrrd.2010.04.0062. 
5. Morone Giovanni, Stefano Masiero, Cordula Werner, Steno Paolucci. Advances in neuromotor stroke rehabilitation. Biomed Res Int. 2014;2014:236043. doi: 10.1155/2014/236043. 
6. Dzieman Katharzyna, Aleksandra Kiper, Alfon Baba, Francesca Baldan, et al. The effect of robot therapy assisted by surface EMG on hand recovery in post-stroke patients. A pilot study. Med Rehabil. 2017;21(4),4-10. doi: 10.5604/01.3001.0011.7401.