Surface electomyography signal processing algorithm and movement control algorithm fo mechatronic-assisted rehabilition of anterior cruciate ligament injuries

The knee is the most complex and largest joint in the human body, and it depends on four primary ligaments. One of the main ligaments is the Anterior Cruciate Ligament (ACL). A direct blow to the knee is one of the ways to injure the ACL, for example during football or a traffic accident. Nevertheless, most ACL injuries happen even without any contact with another object. There are many traditional methods and devices to assist treatment. Nevertheless, robot-assisted therapy (RAT) rehabilitation, simulating normal walking to examine the effects of long-term interventions on functional activity levels after ACL reconstruction, improves the walking ability, the balance ability, and the extensor strength after ACL reconstruction. However, ACL injuries require various rehabilitation phases. Therefore, there is the need to perform RAT or mechatronic-assisted rehabilitation of ACL Injuries during other phases of the rehabilitation before attempting an advanced exercise such as walking, e.g., when the subject tries to make a knee movement and is not able to execute it, due to the pain caused by the injury. In this rehabilitation phase, an active-assisted rehabilitation exercise must be conducted. The specific problem addressed in this thesis is to detect the motion intention and control a mechatronic rehabilitation system to assist the knee movement, i.e., such as in active-assisted extension exercises but using an exoskeleton.