31 research outputs found

    Development and implementation of technologies for physical telerehabilitation in Latin America:

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    La telerehabilitation ha surgido debido a la inclusión de tecnologías emergentes para la captura, transmisión, análisis y visualización de patrones de movimiento asociados a pacientes con trastornos músculo-esqueléticos. Esta estrategia permite llevar a cabo procesos de diagnóstico y tratamientos de rehabilitación a distancia. Este artículo presenta una revisión sistemática del desarrollo e implementación actual de las tecnologías de telerehabilitación en la región latinoamericana. El objetivo principal es explorar, a partir de la literatura científica reportada y fuentes divulgativas, si las tecnologías de telerehabilitación han logrado ser introducidas en esta región. Asimismo, este trabajo revela los prototipos actuales o sistemas que están en desarrollo o que ya están siendo usados. Se llevó a cabo una revisión sistemática, mediante dos búsquedas diferentes. La primera implicó una búsqueda bibliográfica rigurosa en los repositorios digitales científicos más relevantes en el área y la segunda incluyó proyectos y programas de telerehabilitación implementados en la región, encontrados a partir de una búsqueda avanzada en Google. Se encontró un total de 53 documentos de seis países (Colombia, Brasil, México, Ecuador, Chile y Argentina); la mayoría de ellos estaban enfocados en iniciativas académicas y de investigación para el desarrollo de prototipos tecnológicos para telerehabilitación de pacientes pediátricos y adultos mayores, afectados por deficiencias motoras o funcionales, parálisis cerebral, enfermedades neurocognitivas y accidente cerebrovascular. El análisis de estos documentos reveló la necesidad de un extenso enfoque integrado de salud y sistema social para aumentar la disponibilidad actual de iniciativas de telerehabilitación en la región latinoamericana.Telerehabilitation has arised by the inclusion of emerging technologies for capturing, transmitting, analyzing and visualizing movement patterns associated to musculoskeletal disorders. This therapeutic strategy enables to carry out diagnosis processes and provide rehabilitation treatments. This paper presents a systematic review of the current development and implementation of telerehabilitation technologies in Latin America. The main goal is to explore the scientific literature and dissemination sources to establish if such technologies have been introduced in this region. Likewise, this work highlights existing prototypes or systems that are to being used or that are still under development. A systematic search strategy was conducted by two different searches: the first one involves a rigorous literature search from the most relevant scientific digital repositories; the second one included telerehabilitation projects and programs retrieved by an advanced Google search. A total of 53 documents from six countries (Colombia, Brazil, Mexico, Ecuador, Chile and Argentina) were found. Most of them were focused on academic and research initiatives to develop in-home telerehabilitation technologies for pediatric and elderly populations affected by motor and functional impairment, cerebral palsy, neurocognitive disorders and stroke. The analysis of the findings revealed the need for a comprehensive approach that integrates health care and the social system to increase the current availability of telerehabilitation initiatives in Latin America

    An investigation of effects of the partial active assistance in a virtual environment based rehabilitation system

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    This thesis describes a study on a new active assistance in robotic rehabilitation in a haptic virtual environment for post-stroke patients. The novelty of this active assistance system lies in that the assistance is directly rendered on the result of a task performing. Active assistance will generally raise the confidence level of patients in performing a rehabilitation exercise. However, an overly high assistance level may induce cognitive fatigue with patients and thus decreases their motivation of performing a rehabilitation exercise. This thesis hypothesizes that a proper active assistance can improve the performance of a rehabilitation exercise, but will not reduce the motivation of patients in doing rehabilitation exercise. However, due to the difficulty in obtaining a proper number of patients for the experiment, the study turned to healthy people. Accordingly, a revised hypothesis is that active assistance on healthy people does not improve the task performance and not reduces the motivation of healthy people. In this thesis, first, a test-bed with the haptic virtual environment was designed and constructed. The test-bed included a simple task – i.e., following a predefined circle trajectory. Then, a statistical experiment was designed and an experiment was conducted on the test-bed. The experimental results test the hypothesis successfully. The main contributions of this thesis are: (1) the development of a new active assistance system for rehabilitation in a virtual environment and (2) the experimental study on the motivation of healthy people with the developed active assistance system. A care must, however, be taken that the experiment was conducted on healthy people and the conclusion drawn from the study may not be valid on patients

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

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    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

    Low-Cost Sensors and Biological Signals

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    Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

    Development of a home-based Computer Assisted Arm Rehabilitation (hCAAR) device for upper limb exercises in stroke patients

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    Home-based robotic technologies may offer the possibility of self-directed upper limb exercise after stroke as a means of increasing the intensity of rehabilitation treatment. The aim of this research project was to develop and evaluate a robotic device hCAAR that can be used independently at home by stroke survivors with upper limb weakness. The project had two stages: Stage 1, hCAAR development using a user-centred design process; Stage 2, A feasibility clinical study in the home setting. Stage 1: Nine stroke survivors with upper limb weakness and six healthcare professionals were involved in the concept and design stages of device development. hCAAR consists of a powered joystick with a computer interface, which is used to direct the movement of the upper limb to perform therapeutic movements as directed by tasks on the screen. hCAAR also provides controlled assistance when the user’s voluntary upper limb movement is insufficient to complete the prescribed task. Stage 2: In the feasibility study, 19 participants (stroke survivors with upper limb weakness) were recruited and 17 participants used hCAAR in their homes for eight weeks. No serious adverse events were reported. All 17 participants were able to use the device independently. A statistically significant improvement was observed in the kinematic and clinical outcomes. Three participants showed clinically significant improvement in all clinical outcomes. Five participants reported improvement in functional ability in daily activities. Participants, family members and therapists were satisfied with the usability of hCAAR in the home setting. This research project also demonstrated that the International Classification of Functioning, Disability and Health (ICF) Comprehensive Core Set for stroke provides a useful basis to structure interviews to gather feedback from end-users and healthcare professionals in different stages of the rehabilitation device development. In summary, hCAAR is a home-based rehabilitation robotic device that can be independently used by stroke survivors with upper limb weakness and has the potential to improve upper limb movement and function
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