The loss of a hand implies loss of motor functions and potential psychological disturbance of self-image. In
order to restore some of the lost functions and help patients to overcome their trauma, great research efforts
have been spent on the development of hand replacement prostheses. Despite these efforts, electrically
powered prostheses available to patients remain of unnatural use and very limited dexterity, due to the
limitations of the control methods available. Myoelectric control has been shown as an efficient way to
control powered prostheses, however intuitive and reliable control of multiple degrees of freedom remains to
be achieved.
The aim of this PhD thesis is to investigate the limitations of current myoelectric control strategies and
provide alternative solutions towards a more functional control method.
In order to achieve this goal, the project was divided in three studies. In the first study, current myoelectric
control systems showed to be able to operate on dynamic situations with satisfying performance, but at the
cost of training requirements to maintain reliability. Based on these results, an alternative control system
using a state-based approach was developed to overcome some of these limitations. In study 2, the proposed
system showed promising offline performance and high reliability compared to a traditional myoelectric
control system. Then the system was further improved by including proportional control, and its online
performance was investigated in study 3 with virtual feedback. The results showed that the proposed system
allowed precise target reaching and force control during grasp, with very short training. In conclusion, this
PhD project investigated the limitations of available myoelectric control systems, and developed an
alternative control system to overcome these limitations. The proposed system showed promising
performance during both offline and online analyses, and could have the potential to provide myoelectric
users with a more intuitive, yet reliable control system.