Introduction
People with Duchenne muscular dystrophy (DMD) lose independent ambulation by the age of ten years, followed by the development of scoliosis and loss of upper extremity function during their teens, and develop severe cardiomyopathies and respiratory problems during their twenties [
1]. Life expectancy of people with DMD has substantially improved over the last five decades, due to improvements in care, drugs, and the introduction of home care technology, such as artificial ventilators [
2]. As a result, there is currently a considerable group of adults with DMD living with severe physical impairments and a strong dependency on care up to their 30’s [
3].
Several arm supports that compensate the weight of the arms are commercially available and have shown an increase of independence and quality of life for teenagers with DMD [
4]. However, in adults with DMD, the decrease of muscle force combined with an increase of passive joint-stiffness [
5], reduces the effectiveness of current arm supports [
6,
7]. More advanced robotic arm supports can provide extra assistance, and have the potential to enable adults with DMD to continue performing activities of daily living, increasing their independence and participation in social activities.
In order to operate robotic arm supports, the user needs to communicate his motion intention to the device through a control interface. Currently, the only control interface available for adults with DMD are hand joysticks and switches, which are used to control wheelchairs and external robotic arms. We consider that the use of control interfaces that detect the motion intention from physiological signals that are implicitly related to the supported motion can result in a more natural and intuitive interaction with the robotic arm support. In this direction, we have developed and evaluated force and surface electromyography (sEMG) based control interfaces [
8,
9].
The ability for adults with DMD to use sEMG-based control, a well-established control interface in upper-extremity prosthetics [
10], depends on the availability and quality of their sEMG signals. EMG signals have been used for decades in DMD patients for diagnosis and carrier detection [
11]. These studies are mostly based on invasive needle EMG recordings. Studies with sEMG in boys and men with Duchenne are less common and most of them report measurements of lower extremity, facial or oral muscles [
12‐
14]. From a comprehensive literature review we found that Priez et. al. [
15], Bowen et. al [
16], Kumangai and Yamada [
17], Fascarelli et al. [
18], Lobo-Prat et al. [
9], and Janssen et al. [
19] measured sEMG signals from upper extremity muscles in subjects with DMD aged between 5 to 24 years. To the best of our knowledge there are no published studies that report the measurement of upper-extremity sEMG signals in men with DMD older than 24 years, which is the period when robotic arm supports are most needed.
In a previous study [
9], we showed that both sEMG- and force-based control interfaces were feasible solutions for the control of elbow movements in adults with DMD (22-24 years-old). Force-based control was experienced as fatiguing by all participants, a fact that indicates that sEMG-based control is probably the only viable interface for adults with DMD at the last stage of the disease. However, in the biomedical engineering community there is an often raised skepticism over adults with DMD at the last stage of their disease (Brooke score 6) having sEMG signals that can be measured and used for control. As a consequence, development of assistive devices for this group of patients is getting low attention. We think that this skepticism might be based on a wrong pre-conception and that it is thus important to investigate if sEMG signals from upper-extremity muscles of men with DMD at the last stage of the disease are measurable and can be used for control.
DMD patients at the last stage of their disease are very rare and getting them involved in any study is difficult and delicate, because they easily get overwhelmed by the exercises. As a consequence, conducting tests with even just a few of these subjects is very unlikely and general conclusions will have to be drawn from a number of independent studies. We were able to get the kind collaboration of a 37 year-old man with DMD for this study to evaluate his sEMG signals from upper-extremity biceps and triceps muscles. Albeit results from only one subject are insufficient to draw general conclusions, they are relevant to be communicated because of their exceptional nature and will encourage similar studies.
While we hypothesized that the neural activation of the muscle is still measurable in men with DMD that have lost their arm function long time ago (DMD is a disease affecting the contraction of the muscle cells only), we expected their sEMG signals to have a much lower amplitude than in the case of healthy individuals: the infiltration of fatty and connective tissue in the muscle is known to increase the electrical impedance [
20]. The quality of the sEMG signals was evaluated in terms of signal-to-noise ratio (SNR) and co-activation ratio (CAR). Additionally, we evaluated the feasibility of decoding the user’s movement intention from the measured sEMG simulating a sEMG-controlled elbow orthosis.
Discussion
Our results revealed the profound deterioration of the upper-extremity muscles of the 37-year-old man with DMD. The maximum amplitudes of the sEMG signals of the participant were 100 times lower than those typical of healthy individuals (i.e. our measurements of 0.01 mV vs. the 1 mV measured in healthy individuals [
24]). These low signal amplitudes implied low SNRs. We also found profound involuntary activation of the antagonistic muscle as revealed by the measured CARs, which could be caused by the disuse of the arms. Note that arm immobilizations of 12 h are sufficient to significantly reduce motor performance in healthy subjects [
25]. Probably with practice the participant would learn to isolate better the activation of the muscles.
Despite the deterioration of the muscles, we cannot underestimate the fact that sEMG signals from the biceps and triceps muscles were still measurable in a 37-year-old man with DMD that presented considerable muscle deterioration since 20 years ago and completely lost his arm function 15 years ago. Our results also indicate that the participant was able to adjust his voluntary isometric contractions as demanded by the exercises.
The relevance of detecting measurable upper-extremity sEMG signals in adults with DMD at the late-stage of the disease extends beyond its clinical interest. sEMG signals can be used to detect the users’ motion intention and control rehabilitation or assistive devices, which have the potential to delay the disease progression and increase the quality of life for men with DMD [
26,
27]. On this regard, our simulation, which used the measured sEMG signals as input, suggests that, if the high degree of joint stiffness and contractures were not present, the participant could control an active elbow orthosis to perform flexion-extension movements with the same proportional sEMG-based control method used in our previous study [
9]. The angular velocity and displacement obtained by the simulation indicated that it is possible to detect the elbow flexion/extension movement intention of the user from the measured sEMG of the biceps and the triceps muscle. Nevertheless, these results need to be regarded with caution since we did not test the performance of the sEMG-based control using a real system.
Currently, the use of robotic elbow orthoses in adults with DMD in the last stage of the disease is not an option due to the high intrinsic stiffness and joint contractures. However, the use of arm supports, would allow people with DMD to keep using their arms and therefore contribute to the delay of their functional deterioration. We expect that in the future, boys and men with DMD will use arm supports from an early age, which would preserve the range of motion of their joints and potentially benefit from the use of sEMG-controlled arm supports until the last stage of the disease.
Conclusions
The results of the present case study indicate that sEMG signals from the biceps and triceps muscles were very deteriorated but still measurable in a 37 year-old man with DMD that lost his arm function several years ago. Also, the participant was able to adjust his muscle activation level as demanded by the SVIC tasks. To the best of our knowledge this is the first time that sEMG signals from a man with DMD at the last-stage of the disease were measured and reported. Despite the muscle deterioration, the measured signals could be successfully used as input for the control of a simulated elbow orthosis. These results offer promising perspectives to the use of sEMG as an intuitive and natural control interface for assistive devices in adults with DMD until the last stage of the disease, provided that the use of assistive devices since an early stage of the disease reduce joint stiffness and contractures.
Results from only one subject are insufficient to draw general conclusions, but the difficulties to involve participants with DMD in the last stage of the disease make the inclusion of several patients in one single study highly complicated. Thus, sufficient evidence should come by integrating independent studies performed in different laboratories. We hope that the results presented in this Short Report will start breaking the current general opinion that sEMG signals are too weak in DMD patients at the last stage of the disease to be used for control, and will encourage similar studies in other parts of the world, finally leading to better assistive devices for adults with DMD.
Acknowledgments
The authors would like to thank Prof. Peter H. Veltink and Arvid Q.L. Keemink for their support on the data analysis.