Rehabilitative Robotic Glove

Stroke affects 600,000 people annually who are left with weakened limbs and hands. Repetitive hand movement is often used as a rehabilitation technique in order to regain hand movement and strength. In order to facilitate recovery, a robotic glove was designed to aid in the movement and coordination of grip exercises. This glove uses a cable system to open and close a patient’s hand,actuated by servomotors mounted in a 13lbs backpack. The glove can be controlled in terms of finger position and grip force through switch interface, software program, or myoelectric signal. This project developed a working prototype of the rehabilitative robotic glove which actuates the fingers over a full range of motion across one degrees-of-freedom, and is capable of generating a maximum 15N grip force

A human computer interface drived rehabilitation system for upper limb motion recovery

Rehabilitation for recovering the nerve motor system of patients with neuromuscular damage, such as those due to spinal cord injury and spasm, has been based on extremely labour intensive physiotherapy procedures. A potential solution for helping patients to expedite their recovery from neurological disorders and improve their ability in performing activities of daily living would be by using mechatronic-assistive devices that can be controlled by the patients themselves. The inclusion of modern input devices such as Head Mouse or brain-computer interface technology with neurological stimulation to help neural modulation has been advocated by others in the related research community. This paper introduces a power-assisted exoskeleton prototype system for producing elbow flexion-extension motion by using a Head Mouse as an input of control commands by the patient. Experiments were conducted to evaluate the effectiveness (Position, Velocity, Acceleration, and Torque) of the exoskeleton. Results demonstrate that the device would be a useful rehabilitation tool for patients with neuromuscular disorder. © 2012 IEEE.published_or_final_versio

Design, Fabrication, and Control of an Upper Arm Exoskeleton Assistive Robot

Stroke is the primary cause of permanent impairment and neurological damage in the United States and Europe. Annually, about fifteen million individuals worldwide suffer from stroke, which kills about one third of them. For many years, it was believed that major recovery can be achieved only in the first six months after a stroke. More recent research has demonstrated that even many years after a stroke, significant improvement is not out of reach. However, economic pressures, the aging population, and lack of specialists and available human resources can interrupt therapy, which impedes full recovery of patients after being discharged from hospital following initial rehabilitation. Robotic devices, and in particular portable robots that provide rehabilitation therapy at home and in clinics, are a novel way not only to optimize the cost of therapy but also to let more patients benefit from rehabilitation for a longer time. Robots used for such purposes should be smaller, lighter and more affordable than the robots currently used in clinics and hospitals. The common human-machine interaction design criteria such as work envelopes, safety, comfort, adaptability, space limitations, and weight-to-force ratio must still be taken into consideration.;In this work a light, wearable, affordable assistive robot was designed and a controller to assist with an activity of daily life (ADL) was developed. The mechanical design targeted the most vulnerable group of the society to stroke, based on the average size and age of the patients, with adjustability to accommodate a variety of individuals. The novel mechanical design avoids motion singularities and provides a large workspace for various ADLs. Unlike similar exoskeleton robots, the actuators are placed on the patient\u27s torso and the force is transmitted through a Bowden cable mechanism. Since the actuators\u27 mass does not affect the motion of the upper extremities, the robot can be more agile and more powerful. A compact novel actuation method with high power-to-weight ratio called the twisted string actuation method was used. Part of the research involved selection and testing of several string compositions and configurations to compare their suitability and to characterize their performance. Feedback sensor count and type have been carefully considered to keep the cost of the system as low as possible. A master-slave controller was designed and its performance in tracking the targeted ADL trajectory was evaluated for one degree of freedom (DOF). An outline for proposed future research will be presented

Sistemas de rehabilitación para la muñeca: una revisión centrada en el traumatismo de la articulación cúbito-radio

In the performance of repetitive tasks or excessive use of electronic devices frequent conditions of the main nerves of the hand occur. At this article highlights the results obtained from a documentary research that establishes a state of the art of wrist rehabilitation systems, focused on injuries or traumas of the cubic-radius joint. After categorizing and subcategorizing the topic, different databases are used to determine the indexed sources of information that at the Latin American and Colombian levels have explained it in the last decade. Based on the above and the corresponding interpretation, we propose a metacarpal rehabilitation system -for the Colombian context- which allows to carry out exercises, store relevant information about the use of the device and consult the records both in a cellular application and on a computer. It is shown that the system has adequate performance, but that, however, it needs to be clinically validated.En la realización de tareas repetitivas o uso excesivo de dispositivos electrónicos se presentan frecuentes afecciones de los nervios principales de la mano. En el presente artículo se evidencian los resultados obtenidos de una investigación documental que establece un estado del arte de los sistemas de rehabilitación para la muñeca, enfocados a lesiones o traumas de la articulación cúbito-radio. Luego de categorizar y subcategorizar la temática, se utilizan diferentes bases de datos para determinar las fuentes indexadas de información que a nivel latinoamericano y colombiano la han explicado en la última década. Con base en lo anterior y en la correspondiente interpretación, se propone un sistema de rehabilitación metacarpiana -para el contexto colombiano- el cual permite llevar a cabo ejercicios, almacenar información relevante del uso del dispositivo y consultar los registros tanto en una aplicación de celular como en un computador. Se muestra que el sistema tiene un desempeño adecuado, pero que, sin embargo, requiere ser validado clínicamente

A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control