An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach.

The utilization of robotic systems in upper limb rehabilitation has shown promising results in aiding individuals with motor impairments. This research introduces an innovative approach to enhance the efficiency and adaptability of upper limb exoskeleton robot-assisted rehabilitation through the development of an optimized stimulation control system (OSCS). The proposed OSCS integrates a fuzzy logic-based pain detection approach designed to accurately assess and respond to the patient's pain threshold during rehabilitation sessions. By employing fuzzy logic algorithms, the system dynamically adjusts the stimulation levels and control parameters of the exoskeleton, ensuring personalized and optimized rehabilitation protocols. This research conducts comprehensive evaluations, including simulation studies and clinical trials, to validate the OSCS's efficacy in improving rehabilitation outcomes while prioritizing patient comfort and safety. The findings demonstrate the potential of the OSCS to revolutionize upper limb exoskeleton-assisted rehabilitation by offering a customizable and adaptive framework tailored to individual patient needs, thereby advancing the field of robotic-assisted rehabilitation.

Robust tracking control for a quadrotor subjected to disturbances using new hyperplane-based fast Terminal Sliding Mode.

This paper presents a finite-time approach for tracking control of a quadrotor system subjected to external disturbances and model uncertainties. The proposed approach offers a preassigned performance guarantee. Firstly, integral terminal sliding manifolds and nonsingular terminal sliding manifolds are considered to produce the new hyperplane sliding variables for both position and attitude of a quadrotor. The designed hyperplane sliding variables guaranteed a finite-time convergence. The objective is to develop a finite-time control scheme for a disturbed quadrotor to follow a predefined trajectory based on a nonlinear sliding mode controller. The main contribution of this paper is to design a hyperplane-based nonlinear sliding mode control strategy for a quadrotor subjected to disturbances. A concept of robust controllers for a quadrotor is presented based on Lyapunov theory, which proves finite-time stability of the proposed control technique. Numerical simulations with two different scenarios verify the accuracy of the proposed hyperplane-based sliding mode control approach. The simulations study also included a comparison with another nonlinear controller. Results demonstrated overperformance of the proposed control strategy.

A New Wrist-Forearm Rehabilitation Protocol Integrating Human Biomechanics and SVM-Based Machine Learning for Muscle Fatigue Estimation.

In this research, a new remote rehabilitation system was developed that integrates an IoT-based connected robot intended for wrist and forearm rehabilitation. In fact, the mathematical model of the wrist and forearm joints was developed and integrated into the main controller. The proposed new rehabilitation protocol consists of three main sessions: the first is dedicated to the extraction of the passive components of the dynamic model of wrist-forearm biomechanics while the active components are extracted in the second session. The third session consists of performing continuous exercises using the determined dynamic model of the forearm-wrist joints, taking into account the torque generated by muscle fatigue. The main objective of this protocol is to determine the state level of the affected wrist and above all to provide a dynamic model in which the torque generated by the robot and the torque supplied by the patient are combined, taking into account the constraints of fatigue. A Support Vector Machine (SVM) classifier is designed for the estimation of muscle fatigue based on the features extracted from the electromyography (EMG) signal acquired from the patient. The results show that the developed rehabilitation system allows a good progression of the joint's range of motion as well as the resistive-active torques.

Design and Development of a Smart IoT-Based Robotic Solution for Wrist Rehabilitation.

In this study, we present an IoT-based robot for wrist rehabilitation with a new protocol for determining the state of injured muscles as well as providing dynamic model parameters. In this model, the torque produced by the robot and the torque provided by the patient are determined and updated taking into consideration the constraints of fatigue. Indeed, in the proposed control architecture based on the EMG signal extraction, a fuzzy classifier was designed and implemented to estimate muscle fatigue. Based on this estimation, the patient's torque is updated during the rehabilitation session. The first step of this protocol consists of calculating the subject-related parameters. This concerns axis offset, inertial parameters, passive stiffness, and passive damping. The second step is to determine the remaining component of the wrist model, including the interaction torque. The subject must perform the desired movements providing the torque necessary to move the robot in the desired direction. In this case, the robot applies a resistive torque to calculate the torque produced by the patient. After that, the protocol considers the patient and the robot as active and all exercises are performed accordingly. The developed robotics-based solution, including the proposed protocol, was tested on three subjects and showed promising results.

Design and Development of a Wearable Assistive Device Integrating a Fuzzy Decision Support System for Blind and Visually Impaired People.

In this article, a new design of a wearable navigation support system for blind and visually impaired people (BVIP) is proposed. The proposed navigation system relies primarily on sensors, real-time processing boards, a fuzzy logic-based decision support system, and a user interface. It uses sensor data as inputs and provides the desired safety orientation to the BVIP. The user is informed about the decision based on a mixed voice-haptic interface. The navigation aid system contains two wearable obstacle detection systems managed by an embedded controller. The control system adopts the Robot Operating System (ROS) architecture supported by the Beagle Bone Black master board that meets the real-time constraints. The data acquisition and obstacle avoidance are carried out by several nodes managed by the ROS to finally deliver a mixed haptic-voice message for guidance of the BVIP. A fuzzy logic-based decision support system was implemented to help BVIP to choose a safe direction. The system has been applied to blindfolded persons and visually impaired persons. Both types of users found the system promising and pointed out its potential to become a good navigation aid in the future.

Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality.

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human-robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called 'u-Rob' that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer's interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot.