Application of wearable sensors in actuation and control of powered ankle exoskeletons: a Comprehensive Review

Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided

A Novel Design of a Cable-driven Active Leg Exoskeleton (C-ALEX) and Gait Training with Human Subjects

Exoskeletons for gait training commonly use a rigid-linked "skeleton" which makes them heavy and bulky. Cable-driven exoskeletons eliminate the rigid-linked skeleton structure, therefore creating a lighter and more transparent design. Current cable-driven leg exoskeletons are limited to gait assistance use. This thesis presented the Cable-driven Active Leg Exoskeleton (C-ALEX) designed for gait retraining and rehabilitation. Benefited from the cable-driven design, C-ALEX has minimal weight and inertia (4.7 kg) and allows all the degrees-of-freedom (DoF) of the leg of the user. C-ALEX uses an assist-as-needed (AAN) controller to train the user to walk in a new gait pattern. A preliminary design of C-ALEX was first presented, and an experiment was done with this preliminary design to study the effectiveness of the AAN controller. The result on six healthy subjects showed that the subjects were able to follow a new gait pattern significantly more accurately with the help of the AAN controller. After this experiment, C-ALEX was redesigned to improve its functionality. The improved design of C-ALEX is lighter, has more DoFs and larger range-of-motion. The controller of the improved design improved the continuity of the generated cable tensions and added the function to estimate the phase of the gait of the user in real-time. With the improved design of C-ALEX, an experiment was performed to study the effect of the weight and inertia of an exoskeleton on the gait of the user. C-ALEX was used to simulate exoskeletons with different levels of weight and inertia by adding extra mass and change the weight compensation level. The result on ten subjects showed that adding extra mass increased step length and reduced knee flexion. Compensating the weight of the mass partially restored the knee flexion but not the step length, implying that the inertia of the mass is responsible for the change. This study showed the distinctive effect of weight and inertia on gait and demonstrated the benefit of a lightweight exoskeleton. C-ALEX was designed for gait training and rehabilitation, and its training effectiveness was studied in nine healthy subjects and a stroke patient. The healthy subjects trained with C-ALEX to walk in a new gait pattern with 30% increase in step height for 40 min. After the training, the subjects were able to closely repeat the trained gait pattern without C-ALEX, and the step height of the subjects increased significantly. A stroke patient also tested C-ALEX for 40 minutes and showed short-term improvements in step length, step height, and knee flexion after training. The result showed the effectiveness of C-ALEX in gait training and its potential to be used in stroke rehabilitation