Despite the possibilities of the current neuroprosthetic devices, the majority of end users are not yet satisfied with their grasp neuroprostheses. Possible reasons for this dissatisfaction are that the systems put a high workload on the user and do not allow a stable and adaptive motor control. This is particularly critical for fine grasp and execution of reaching movements.
To overcome these limitations, the MoreGrasp project will develop a closed-loop control system, allowing a more intuitive and semi-autonomous control. For this closed-loop control, MoreGrasp will integrate the brain signals (BCI) with with information from sensors placed in the environment and on the arm sleeve. Furthermore, the system will provide real-time feedback to the user and allow several levels of control.
Intelligent Environment and arm sleeve
To obtain detailed information of the interaction between the user and the environment, several sensors will be used (e.g.: position, orientation, force sensors). As an example, these sensors could be used to automatically adapt the grasp type to the object, without the need of user-input. We believe that relatively simple integrated actuation of the environment could dramatically increase the capabilities of the user.
The control loop will also integrate feedback about the current status of the neuroprosthesis. This feedback can be haptic, visual or auditory. The feedback has the potential of creating an engaging and efficient interaction which supports the user throughout training but also final control of the neuroprostheses.
Levels of control
Control at multiple levels of engagement will be possible. Practically speaking, this means that the users will be able to vary the amount of effort they want to apply, depending on the situation. As an example, the user can decide if he wants to exclusively rely on the BCI or if he prefers to control the neuroprostheses with both BCI and shoulder joystick
The control loop will be personalized to the user, being flexible to enhance the enjoyment and utility of the system and, most importantly, we aim to develop the user interaction to produce and efficient and comfortable shared control of the neuroprostheses.