This paper presents the double chain–integrator finite-time convergence in a closed loop with a second-order bang–bang sliding control. The direct Lyapunov method carried out the stability analysis and the reaching time estimation using a suitable non-smooth strong Lyapunov function. That is, the proposed energy function is strictly positive definite, with a strictly definite negative time derivative. Additionally, the proposed function estimates the reaching time in the presence of matching bounded perturbations. Numerical comparisons with well-known approaches were performed to assess the proposed strategy’s effectiveness.

The objective of this study was to design of an output based impedance adaptive controller for a special class of cervical orthoses, a class of biomedical devices for the rehabilitation of neck illnesses. The controller used the adaptive sliding mode theory to enforce the tracking of the reference trajectory if the patient was not resistant to the therapy. If the patient rejects the orthosis activity, a second impedance-based controller governs the orthosis movement allowing the patient to take the leading role in the orthosis sequence of movements. The proposed controller considers a weighted controller combining the tracking and the impedance controls in a single structure. The monitoring of the external force was evaluated on a novel weighting function defining on-line the role of each controller. The proposed orthosis was motivated by the prevalence of whiplash, which is a syndrome that is produced by forced hyperextension and hyperflexion of the neck. This study included the development of a technological prototype of the orthotic type to support the recovery of patients diagnosed with whiplash. The sections that make up the orthotic device are two independent systems that move the patient’s head in the sagittal and frontal planes. For this purpose, the mechanical structure of the cervical orthosis was made up of 7 pieces printed in 3D with polylactic acid (PLA). The operation of the cervical orthosis was evaluated in two sections: (a) using a simulation system, which consists of a spring with an artificial head and the development of a graphic interface in Matlab, and (b) evaluating the controller on the proposed orthosis. With these elements, the follow-up of the trajectory proposed by the actuators was evaluated, as well as its performance in the face of the opposition that a patient generates. The superiority of the proposed controller was confirmed by comparing the tracking efficiency with proportional-integral-derivative and first-order sliding variants.

No abstract

This work proposes a robust sliding mode controller to enforce the tracking trajectory of a cervical orthotic device subjected to asymmetric box constraints. The convergence analysis employs an asymmetric barrier Lyapunov function (ABLF), whose argument is a restricted sliding surface. The stability analysis demonstrates the finite-time convergence of the states towards the sliding surface and, therefore, the exponential stability of the system trajectories. The controller ensures the fulfillment of the restrictions imposed on the sliding surface and consequently over the states. Numerical simulations exhibit the performance of the proposed controller ensuring restricted movements for flexion and extension of a virtual orthotic cervical device. The restricted movements obey asymmetric constraints according to the therapies proposed by medical specialists.

This work provides a complete dataset containing surface electromyography (sEMG) signals acquired from the forearm with a sampling frequency of 1000 Hz. The dataset is named WyoFlex sEMG Hand Gesture and recorded the data of 28 participants between 18 and 37 years old without neuromuscular diseases or cardiovascular problems. The test protocol consisted of sEMG signals acquisition corresponding to ten wrist and grasping movements (extension, flexion, ulnar deviation, radial deviation, hook grip, power grip, spherical grip, precision grip, lateral grip, and pinch grip), considering three repetitions for each gesture. Also, the dataset contains general information such as anthropometric measures of the upper limb, gender, age, laterally of the person, and physical condition. Likewise, the implemented acquisition system consists of a portable armband with four sEMG channels distributed equidistantly for each forearm. The database could be used for the recognition of hand gestures, evaluation of the evolution of patients in rehabilitation processes, control of upper limb orthoses or prostheses, and biomechanical analysis of the forearm.