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MYOELECTRIC INTERFACING WITH SENSORY-MOTOR INTEGRATION

Final Report Summary - MYOSENS (MYOELECTRIC INTERFACING WITH SENSORY-MOTOR INTEGRATION)

Biological signals recorded from the human body can be translated into actions of external devices. This determines a so-called man-machine interaction. This concept has strong implications in technologies that aim at reducing or eliminating movement impairments in patients. For example, man-machine interaction can be used for controlling prosthetic limbs that substitute missing limbs in amputees or robotic systems that mobilize paralyzed limbs in stroke patients with a therapeutic aim. Biosignals for man-machine interaction can be recorded from the brain, nerves, or muscles. Among these choices, muscle electrical signals, called electromyographic (EMG) signals, are the only that allow applications in routine clinical use within a commercially reasonable time horizon. Myoelectric interaction has the unique and little exploited feature of provoking changes in the neural circuits that are active during the interaction, that is, of artificially inducing brain plasticity. However, current commercially viable myoelectric interfaces do not implement sensory-motor integration (decoding intentions and at the same time providing a sensory feedback to the patient), which conversely is the basis of plasticity of the central nervous system. This limit reflects the gap between academic research and the clinical and commercial needs.
With a consortium of internationally regarded European academic teams and industries, MYOSENS aimed at implementing sensory-motor interaction into commercially viable myoelectric devices in two key clinical applications: 1) training for the active control of hand prostheses; and 2) rehabilitation of stroke patients with robotics. These two areas have a large social impact, given the large number of patients that may benefit from the developed technology. For example, stroke leads to permanent neurological impairment in at least 12.6 million people worldwide, and age is one of the most significant stroke risk factors (two-thirds of strokes occur in individuals over 65), which makes this a priority area considering the progressive ageing of the population. The two outlined areas (prosthetics and robotics) require a similar technological ground for sensory-motor integration and for artificial induction of neural plasticity, necessary to (re)learn motor tasks.

The aim of MYOSENS in the prosthetic area was to develop clinical systems that allow transmitting information to the prosthetic user on the status of the controlled artificial limb (e.g. on the force exerted), in order to close the control loop. MYOSENS addressed this problem in a systematic way by analyzing all parts of the problem, from the definition of the best feedback variables to the way in which these variables could be communicated to the users, and to clinical tests that indicated how feedback was used by patients. The main outcomes of this work are published in xx journal papers written by the consortium during the four years of the project. In summary, the main achievements are the following:
- A standardized modular tool for testing sensory-motor interaction with the possibility of varying the quality of the control and of the feedback. This test bench is ready for its distribution to the scientific community as an effort of standardizing human tests of sensory-motor integration.
- A conceptual and simulation model of the learning process consequent to sensory-motor interaction when the uncertainties of the feedback and of the feed-forward control interfaces vary. This model allows to predict the learning effect in the use of prostheses with sensory feedback.
- The MYOSENS closed-loop prosthetic system comprising EMG as feedback variable (that is, the feedback variable is not related to the prosthesis actions but to the commands that determine these actions) and spatial coding for delivering this variable to the user. Spatial coding was obtained by electrodes or vibrators distributed over the skin of the stump that were activated in patterns consistent with the activated degrees of freedom.
- The MYOSENS training system for phantom limb pain, consisting of multichannel EMG recordings and multi-site cutaneous stimulation with associated software for visual feedback. The system was fully tested clinically and its efficacy was demonstrated.
The above items are objective project achievements in the form of products (software or hardware) that have a direct impact in the prosthetic field.

The aim of MYOSENS in the area of rehabilitation robotic was the development of clinical systems that allow assisting the patient movement based on the residual muscular activity. This aim was achieved with two rehabilitation robotic devices, RehaArm and Amadeo, which are produced by two partners of the MYOSENS consortium. The RehaArm is dedicated to shoulder rehabilitation and the Amadeo Robot to hand/finger rehabilitation. The main outcomes of the work in robotics were published in 11 journal papers by the consortium. In summary, the main achievements are the following:
- Development of a simple control system, based on EMG amplitude from multiple muscles, that could be used in a clinical environment, during the regular patient therapy, and operated exclusively by medical staff without technical support. This achievement was reached for both the shoulder and hand rehabilitation robotics and allowed to run clinical trials with strong relevance for the potential commercialization of the proposed systems.
- Comparison of the proposed EMG control system with a classic force control system in a large number of patients with different degrees of severity in their movement impairments. These tests indicated a large proportion of patients who can use the proposed EMG-control system but not the classic force control. These patients are the most severe. The result was a strong indicator for the potential social and economic impact of the MYOSENS systems.
- Longitudinal clinical trials proving the effectiveness of the robotic treatment with EMG control.
The above results have been so relevant that one of the two MYOSENS robotic systems (Amadeo for hand rehabilitation) has now been equipped with the MYOSENS EMG control for a new upgraded commercial version.

In conclusion, MYOSENS systematically analyzed the inclusion of sensory-motor interaction in two key technologies for rehabilitation, prosthetics and robotics. It made it with a strong view to the clinical needs as well as to the commercial viability of the developed systems. The results in both areas have been substantial and have allowed to improve the capabilities of commercial systems with ideas from academia. These improvements have been tested clinically and proved to be relevant for the recovery of the patients. This has the potential to result in a strong social and economic impact in the near future since the companies involved in the project are already starting to commercially exploit the developed systems.

Project Website: http://myosens.bccn.uni-goettingen.de/