Using wearable robots is an effective means of rehabilitation for stroke survivors, and effective recognition of human motion intentions is a key premise in controlling wearable robots. In this paper, we propose an inertial measurement unit (IMU)-based gait phase detection system. The system consists of two IMUs that are tied on the thigh and on the shank, respectively, for collecting acceleration and angular velocity. Features were extracted using a sliding window of 150 ms in length, which was then fed into a quadratic discriminant analysis (QDA) classifier for classification. We recruited five stroke survivors to test our system. They walked at their own preferred speed on the level ground. Experimental results show that our proposed system has the ability of recognizing the gait phase of stroke survivors. All recognition accuracy results are above 96.5%, and detections are about 5–15 ms in advance of time. In addition, using only one IMU can also give reliable recognition results. This paper proposes an idea about the further research on human–computer interaction for the control of wearable robots.

This paper presents a novel three-degree of freedom (DOF) sensorized remote-center-of-motion (RCM) ankle module for a military-purpose lower-limb exoskeleton. A military-purpose exoskeleton should assist and follow the fast and dexterous motion of a soldier in rough terrain environments. Among the lower-limb joints, the ankle joint plays an important role in stabilizing walking motion during the stance phase. Thus, aligning the rotation center of the ankle module with the center of the wearer’s ankle is very important to reduce potential risks and fatigue of a soldier. To this end, the ankle exoskeleton was designed using two spherical chains. The two spherical chains were designed such that the intersection of all revolute pairs, which consist of the spherical chains, is located close to the rotation center of the wearer’s ankle. In addition, three encoders are attached to each of the three revolute pairs of a spherical chain to measure the three-DOF orientation of the ankle mechanism. For the design, the required range of motion is analyzed via gait analysis in three environment conditions. Forward and inverse kinematic relations are derived, and the workspace of the ankle is analyzed. For the prototype ankle mechanism, the range of motion and measurement performance are verified by a static experiment. In addition, comparative studies between the proposed RCM ankle and an ankle mechanism with offset rotation center are performed for three walking conditions: level walking, ascending and descending stairs, and a vertical slope. Via comparative study, it is confirmed that, compared to the ankle mechanism with offset center of rotation, the proposed RCM ankle is advantageous for sensing wearer’s ankle motion and reducing mechanical interference to wearer’s natural ankle motion.