Controlling a robotic hip exoskeleton with noncontact capacitive sensors

For partial lower-limb exoskeletons, an accurate real-time estimation of the gait phase is paramount to provide timely and well-tailored assistance during gait. To this end, dedicated wearable sensors separate from the exoskeletons mechanical structure may be preferable because they are typically isolated from movement artifacts that often result from the transient dynamics of the physical human-robot interaction. Moreover, wearable sensors that do not require time-consuming calibration procedures are more easily acceptable by users. In this study a robotic hip orthosis was controlled using capacitive sensors placed in orthopedic cuffs on the shanks. The capacitive signals are zeroed after donning the cuffs and do not require any further calibration. The capacitive sensing-based controller was designed to perform online estimation of the gait cycle phase via adaptive oscillators, and to provide a phase-locked assistive torque. Two experimental activities were carried out to validate the effectiveness of the proposed control strategy. Experiments conducted with seven healthy subjects walking on a treadmill at different speeds demonstrated that the controller can estimate the gait phase with an average error of 4%, while also providing hip flexion assistance. Moreover, experiments carried out with four healthy subjects showed that the capacitive sensing-based controller could reduce the metabolic expenditure of subjects compared to the unassisted condition (mean ± SEM, -3.2% ± 1.1)

FPGA-based gait control system for passive bipedal robot

In this paper, we present a Field Programmable Gate Array (FPGA) based high-performance gait control system for passive bipedal robots with complex mechanical structures and multiple degrees of freedoms in body and limbs. The system utilizes the hardware and software reconfigurable feature of the advanced FPGA device to achieve intelligent bipedal gait control. We implement central processing unit, sensor data processing module, gait control module, pulse width modulation module and data transmission module inside the FPGA chip. All the modules can be duplicated and reconfigured to control as many motors as needed. In addition, we design a gait control strategy with the method of phase transfer map. To estimate the control system, we create bipedal robots with passive dynamic gaits. Satisfactory experimental results demonstrate that the FPGA-based gait control system is a flexible, high-performance solution for the locomotion control of passive bipedal robots. ? 2008 IEEE.EI

Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles

The muscles of the lower limbs directly influence leg motion, therefore, lower limb muscle exercise is important for persons living with lower limb disabilities. This paper presents a medical assistive robot with leg exoskeletons for locomotion and leg muscle exercises. It also presents a novel pedal-cycling actuation method with a crank-rocker mechanism. The mechanism is driven by a single motor with a mechanical structure that ensures user safety. A control system is designed based on a master-slave control with sensor fusion method. Here, the intended motion of the user is detected by pedal-based force sensors and is then used in combination with joystick movements as control signals for leg-exoskeleton and wheelchair motions. Experimental data is presented and then analyzed to determine robotic motion characteristics as well as the assistance efficiency with attached electromyogram (EMG) sensors. A typical muscle EMG signal analysis shows that the exercise efficiency for EMG activated amplitudes of the gluteus medius muscles approximates a walking at speed of 3 m/s when cycling at different speeds (i.e., from 16 to 80 r/min) in a wheelchair. As such, the present wheelchair robot is a good candidate for enabling effective gluteus medius muscle exercises for persons living with gluteus medius muscle disabilities