Development of portable robotic orthosis and biomechanical validation in people with limited upper limb function after stroke

Abstract

Stroke has a considerable incidence in the world population and would cause sequelae in the upper limbs. One way to increase the efficiency in the rehabilitation process of patients with these sequelae is through robot-assisted therapy. The present study developed a portable robotic orthosis called Pinotti Portable Robotic Exoskeleton (PPRE) and validated its functioning in clinical tests. The static and dynamic parts of the device modules are described. Design issues, such as heavyweight and engine positioning, have been optimized. The implementation of control was through a smartphone application that communicates with a microcontroller to perform desired movements. Four individuals with motor impairment of the upper limbs due to stroke performed clinical tests to validate the device. Participants did not mention pain, discomfort, tingling, and paresthesia. The robotic device showed the ability to perform the flexion and extension movements of the fingers and elbow. The PPRE was confirmed to be adequate and functional at different levels of motor impairment assessed. The orthosis presented advantages over the currently existing devices, concerning its biomechanical functioning, portability, comfort, and versatility. Thus, the apparatus has the great innovative potential to become a device for home use, serving as an aid to the therapist and facilitating the rehabilitation of patients after an injury. In a larger sample, future studies are needed to assess the effect of a robotic orthosis on the level of rehabilitation in individuals with upper limb impairment.

A Light-Weight Artificial Neural Network for Recognition of Activities of Daily Living

“…Known time-and frequency-domain features were investigated, and training trials were conducted using different combinations of features, based on which, the optimal set of features was selected. For each window, the following nine features were extracted: (1) mean, (2) median, (3) standard deviation, (4) minimum, (5) maximum, (6) initial value, (7) final value, (8) mean absolute value (MAV) and ( 9) waveform length (WL), as follows:…”

“…Even though sensing technology and computational intelligence have shown rapid progress in recent years, HAR still faces various challenges including critical accuracy demands, since recognition errors could result in faulty assistance. Moreover, real-time constraints of the associated control systems demand a high-speed inference, which is further challenged by the scarce computational resources of portable low-weight devices [7].…”

Design and Analysis of VARONE a Novel Passive Upper-Limb Exercising Device

“…They are affordable, compact, and easy to operate without professional supervision. The adaptability of passive devices enables stroke survivors to continue rehabilitation independently in their homes, promoting long-term engagement and improving functional recovery and quality of life, such as reported in [17] for posture rehabilitation.…”