A Brief Review of the Electronics, Control System Architecture, and Human Interface for Commercial Lower Limb Medical Exoskeletons Stabilized by Aid of Crutches Research in the field of the powered orthoses or exoskeletons has expanded tremendously over the past years. Lower limb exoskeletons are widely used in robotic rehabilitation and are showing benefits in the patients quality of life. Many engineering reviews have been published about these devices and addressed general aspects. To the best of our knowledge, no review has minutely discussed specifically the control of the most common used devices, particularly the algorithms used to define the function state of the exoskeleton, such as walking, sittostand, etc. In this contribution, the control hardware and software, as well as the integrated sensors for the feedback are thoroughly analyzed. We will also discuss the importance of userspecific state definition and customized control architecture. Although there are many prototypes developed nowadays, we chose to target medical lower limb exoskeletons that uses crutches to keep balance, and that are minimally actuated. These are the most common system that are now being commercialized and used worldwide. Therefore, the outcome of such a review helps to have a practical insight in all of: the mechatronics design, system architecture, and control technology.

ALICE: Conceptual Development of a Lower Limb Exoskeleton Robot Driven by an OnBoard Musculoskeletal Simulator Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an onboard muscle driven simulator to estimate the userxe2x80x99s kinetic parameters. Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intrasubject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute realtime information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept. Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a positionvelocity sensor in each actuator. Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies. Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.