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- Overview of robotic based system for rehabilitation and healthcarePublication . Chellal, Arezki Abderrahim; Lima, José; Fernandes, Florbela P.; Gonçalves, José; Pacheco, Maria F.; Monteiro, Fernando C.As in many other fields, robots are increasingly being used in the healthcare sector, particularly for hospital logistics support, surgery and rehabilitation. Rehabilitation is a concern for millions of people around the world, and because of this, there has been a constant progress over the last decade in the rehabilitation robotics field, with the use of new technologies aimed at overcoming the different challenges faced in this field. In this sense, this paper reviews the main applications developed in the last ten years of rehabilitation robotics, as well as the different challenges that still need to be addressed in order to achieve the design of a prototype that is easy to use, small, safe, less costly and brings real added value to this field. Much of the efforts of the researchers in this topics is focused on providing as many DOF and ROM as possible, and also on the designing of new robots control algorithms
- Angle assessment for upper limb rehabilitation: a novel light detection and ranging (LiDAR)-based approachPublication . Klein, Luan C.; Chellal, Arezki Abderrahim; Grilo, Vinicius F.S.B.; Braun, João; Gonçalves, José; Pacheco, Maria F.; Fernandes, Florbela P.; Monteiro, Fernando C.; Lima, JoséThe accurate measurement of joint angles during patient rehabilitation is crucial for informed decision making by physiotherapists. Presently, visual inspection stands as one of the prevalent methods for angle assessment. Although it could appear the most straightforward way to assess the angles, it presents a problem related to the high susceptibility to error in the angle estimation. In light of this, this study investigates the possibility of using a new approach to angle calculation: a hybrid approach leveraging both a camera and LiDAR technology, merging image data with point cloud information. This method employs AI-driven techniques to identify the individual and their joints, utilizing the cloud-point data for angle computation. The tests, considering different exercises with different perspectives and distances, showed a slight improvement compared to using YOLO v7 for angle calculation. However, the improvement comes with higher system costs when compared with other image-based approaches due to the necessity of equipment such as LiDAR and a loss of fluidity during the exercise performance. Therefore, the cost-benefit of the proposed approach could be questionable. Nonetheless, the results hint at a promising field for further exploration and the potential viability of using the proposed methodology.
- Robot-assisted rehabilitation architecture supported by a distributed data acquisition systemPublication . Chellal, Arezki Abderrahim; Lima, José; Gonçalves, José; Fernandes, Florbela P.; Pacheco, Maria F.; Monteiro, Fernando C.; Brito, Thadeu; Soares, SalvianoRehabilitation robotics aims to facilitate the rehabilitation procedure for patients and physical therapists. This field has a relatively long history dating back to the 1990s; however, their implementation and the standardisation of their application in the medical field does not follow the same pace, mainly due to their complexity of reproduction and the need for their approval by the authorities. This paper aims to describe architecture that can be applied to industrial robots and promote their application in healthcare ecosystems. The control of the robotic arm is performed using the software called SmartHealth, offering a 2 Degree of Autonomy (DOA). Data are gathered through electromyography (EMG) and force sensors at a frequency of 45 Hz. It also proves the capabilities of such small robots in performing such medical procedures. Four exercises focused on shoulder rehabilitation (passive, restricted active-assisted, free active-assisted and Activities of Daily Living (ADL)) were carried out and confirmed the viability of the proposed architecture and the potential of small robots (i.e., the UR3) in rehabilitation procedure accomplishment. This robot can perform the majority of the default exercises in addition to ADLs but, nevertheless, their limits were also uncovered, mainly due to their limited Range of Motion (ROM) and cost.
- Design of an embedded energy management system for li–po batteries based on a dcc-ekf approach for use in mobile robotsPublication . Chellal, Arezki Abderrahim; Gonçalves, José; Lima, José; Pinto, Vítor H.; Megnafi, HichamIn mobile robotics, since no requirements have been defined regarding accuracy for Battery Management Systems (BMS), standard approaches such as Open Circuit Voltage (OCV) and Coulomb Counting (CC) are usually applied, mostly due to the fact that employing more complicated estimation algorithms requires higher computing power; thus, the most advanced BMS algorithms reported in the literature are developed and verified by laboratory experiments using PC-based software. The objective of this paper is to describe the design of an autonomous and versatile embedded system based on an 8-bit microcontroller, where a Dual Coulomb Counting Extended Kalman Filter (DCC-EKF) algorithm for State of Charge (SOC) estimation is implemented; the developed prototype meets most of the constraints for BMSs reported in the literature, with an energy efficiency of 94% and an error of SOC accuracy that varies between 2% and 8% based on low-cost components
- Energy management of Li-Po batteries in the mobile robotics domainPublication . Chellal, Arezki Abderrahim; Lima, José; Gonçalves, José; Megnafi, HichamThe importance of energy storage continues to grow, whether in power generation, consumer electronics, aviation, or other systems. Therefore, energy management in batteries is becoming an increasingly crucial aspect of optimizing the overall system and must be done properly. Very few works have been found in the literature proposing the implementation of algorithms such as EKF to predict the SOC in small systems such as mobile robots, where computational power in some application is severely lacking. To this end, this work proposes an implementation of two algorithms mainly reported in the literature for SOC estimation, in an ATMEGA328P microcontroller-based BMS, this embedded system is designed taking into consideration the criteria already defined for such a system and adding the aspect of flexibility and ease of implementation. One of the implemented algorithms performs the prediction, while the other will be responsible for the monitoring.
- Energy Efficiency Analysis of Differential and Omnidirectional Robotic Platforms: A Comparative StudyPublication . Chellal, Arezki Abderrahim; Braun, João; Junior, Luciano Bonzatto; Faria, Milena; Kalbermatter, Rebeca B.; Gonçalves, José; Costa, Paulo Gomes da; Lima, JoséAs robots have limited power sources. Energy optimization is essential to ensure an extension for their operating periods without needing to be recharged, thus maximizing their uptime and minimizing their running costs. This paper compares the energy consumption of different mobile robotic platforms, including differential, omnidirectional 3-wheel, omnidirectional 4-wheel, and Mecanum platforms. The comparison is based on the RobotAtFactory 4.0 competition that typically takes place during the Portuguese Robotics Open. The energy consumption from the batteries for each platform is recorded and compared. The experiments were conducted in a validated simulation environment with dynamic and friction models to ensure that the platforms operated at similar speeds and accelerations and through a 5200 mAh battery simulation. Overall, this study provides valuable information on the energy consumption of different mobile robotic platforms. Among other findings, differential robots are the most energy-efficient robots, while 4-wheel omnidirectional robots may offer a good balance between energy efficiency and maneuverability.
- SmartHealth: a robotic control software for upper limb rehabilitationPublication . Chellal, Arezki Abderrahim; Lima, José; Gonçalves, José; Fernandes, Florbela P.; Pacheco, Maria F.; Monteiro, Fernando C.; Valente, AntónioThe proposed work was developed under the Smart Health project, which aims to advance the upper body rehabilitation by offering a robotic alternative to reduce the limitations of physical therapy, providing more intensive and personalized therapy sessions for patients. The use of robots allows on the one hand to relieve therapists from laborious and repetitive tasks, and on the other hand to relieve rehabilitation centers with more affordable sessions. The proposed strategy is to develop a new python-based software that controls the robot, collects the patient’s forces and muscle activity in real time and store them for future analysis, while providing visual feedback, thus allowing to optimize the sessions. These features allow the physiotherapist to have an objective perception of the patient’s performance during the exercise. This solution is implemented in robots already commercialized in the industrial field, which are generally mass-produced in production lines at a relatively low cost and with great flexibility.
- Overview of robotic based system for rehabilitation and healthcarePublication . Chellal, Arezki Abderrahim; Lima, José; Fernandes, Florbela P.; Gonçalves, José; Pacheco, Maria F.; Monteiro, Fernando C.As in many other fields, robots are increasingly being used in the healthcare sector, particularly for hospital logistics support, surgery and rehabilitation. Rehabilitation is a concern for millions of people around the world, and because of this, there has been a constant progress over the last decade in the rehabilitation robotics field, with the use of new technologies aimed at overcoming the different challenges faced in this field. In this sense, this paper reviews the main applications developed in the last ten years of rehabilitation robotics, as well as the different challenges that still need to be addressed in order to achieve the design of a prototype that is easy to use, small, safe, less costly and brings real added value to this field. Much of the efforts of the researchers in this topics is focused on providing as many DOF and ROM as possible, and also on the designing of new robots control algorithms.
- Dual coulomb counting extended kalman filter for battery SOC determinationPublication . Chellal, Arezki Abderrahim; Lima, José; Gonçalves, José; Megnafi, HichamThe importance of energy storage continues to grow, whether in power generation, consumer electronics, aviation, or other systems. Therefore, energy management in batteries is becoming an increasingly crucial aspect of optimizing the overall system and must be done properly. Very few works have been found in the literature proposing the implementation of algorithms such as Extended Kalman Filter (EKF) to predict the State of Charge (SOC) in small systems such as mobile robots, where in some applications the computational power is severely lacking. To this end, this work proposes an implementation of the two algorithms mainly reported in the literature for SOC estimation, in an ATMEGA328P microcontroller-based BMS. This embedded system is designed taking into consideration the criteria already defined for such a system and adding the aspect of flexibility and ease of implementation with an average error of 5% and an energy efficiency of 94%. One of the implemented algorithms performs the prediction while the other will be responsible for the monitoring.
- Battery management system for mobile robots based on an extended Kalman filter approchPublication . Chellal, Arezki Abderrahim; Lima, José; Gonçalves, José; Megnafi, HichamRobots are rapidly developing, due to the technology advances and the increased need for their mobility. Mobile Robots can move freely in unconstrained environments, without any external help. They are supplied by batteries as the only source of energy that they could access. Thus, the management of the energy offered by these batteries is so crucial and has to be done properly. Most advanced Battery Management System (BMS) algorithms reported in literature are developed and veri ed with laboratory-based experiments. The acquired data is then processed either online or of ine, using PC-based software. This work consists of developing an on-Chip Extended Kalman Filter based BMS, which can be directly linked in a robot without having to be connected with an external device to process the data. The proposed system is implemented in a low-cost 8 bit microcontroller and results allow to validate the proposed approach.