This chapter presents the software development for the H2 robotic exoskeleton, as well as the integration of the device with a neural interface. The software was developed with an architecture of layers, with three different levels. This approach makes easy the development of new therapies or control strategies without rewriting all the code. The chapter begins with the description of the software implemented to control each H2 joint actuator. Following is the description of the middle layer of software implemented to synchronize the movement of all joints and provide close loop control based on position, torque or stiffness. Each joint can be independently controlled by the high level control layer, where the therapies are implemented. The
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HAL, the overground exoskeleton with more studies in rehabilitation of post-stroke patients [160–162, 212], uses sEMG signals for adjusting the joints’ torque. However, the use of sEMG signals have a number of problems, such as availability and quality of sEMG signals varying across different users, fragility and installation requirements of electrodes being restrictive outside the laboratory. Another problem is that stroke affects the normal function of the brain and the EMG signal, which is a further downstream in the neurological pathway, gets affected as well. Therefore, sEMG to torque conversion method will be a more challenging task that may need a long time for adaptation and adjustments …show more content…
This approach modulates the robot assistance according to parameters measured during task execution. It seems to be suitable for hemiplegic post- stroke patients because the emphasis is more on guidance towards a correct pattern than on a simple rigid repetition.
The H2 control approach implements an assist-as-needed algorithm based on a force field control, where the joint torque is generated based on the trajectory deviation, resulting in a corrective proportional force that correct guides patient’s limb. This algorithm concept has the benefit that the controller will always generate enough torque to stabilize both, the affected and unaffected leg, without the need of any model of the exoskeleton or the user.
The assist-as-needed control of the H2, together with the overground capability, is in- tended to create a highly motivated environment for patients, leading to a faster recovery and higher gains in motor functions. Moreover, the use of this robotic tool will facili- tate the work carried out by physical therapists, allowing a more intensive training for patients without fatiguing
HAL, the overground exoskeleton with more studies in rehabilitation of post-stroke patients [160–162, 212], uses sEMG signals for adjusting the joints’ torque. However, the use of sEMG signals have a number of problems, such as availability and quality of sEMG signals varying across different users, fragility and installation requirements of electrodes being restrictive outside the laboratory. Another problem is that stroke affects the normal function of the brain and the EMG signal, which is a further downstream in the neurological pathway, gets affected as well. Therefore, sEMG to torque conversion method will be a more challenging task that may need a long time for adaptation and adjustments …show more content…
This approach modulates the robot assistance according to parameters measured during task execution. It seems to be suitable for hemiplegic post- stroke patients because the emphasis is more on guidance towards a correct pattern than on a simple rigid repetition.
The H2 control approach implements an assist-as-needed algorithm based on a force field control, where the joint torque is generated based on the trajectory deviation, resulting in a corrective proportional force that correct guides patient’s limb. This algorithm concept has the benefit that the controller will always generate enough torque to stabilize both, the affected and unaffected leg, without the need of any model of the exoskeleton or the user.
The assist-as-needed control of the H2, together with the overground capability, is in- tended to create a highly motivated environment for patients, leading to a faster recovery and higher gains in motor functions. Moreover, the use of this robotic tool will facili- tate the work carried out by physical therapists, allowing a more intensive training for patients without fatiguing