RESUMEN
Robotic exoskeletons that induce leg movement have proven effective for lower body rehabilitation, but current solutions offer limited gait patterns, lack stabilization, and do not properly stimulate the proprioceptive and balance systems (since the patient remains in place). Partial body weight support (PBWS) systems unload part of the patient's body weight during rehabilitation, improving the locomotive capabilities and minimizing the muscular effort. HYBRID is a complete system that combines a 6DoF lower body exoskeleton (H1) with a PBWS system (REMOVI) to produce a solution apt for clinical practice that offers improves on existing devices, moves with the patient, offers a gait cycle extracted from the kinematic analysis of healthy users, records the session data, and can easily transfer the patient from a wheelchair to standing position. This system was developed with input from therapists, and its response times have been measured to ensure it works swiftly and without a perceptible delay.
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Peso Corporal , Dispositivo Exoesqueleto , Marcha/fisiología , Movimiento/fisiología , Robótica , Humanos , Articulaciones/fisiología , Rango del Movimiento Articular , Interfaz Usuario-ComputadorRESUMEN
This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed interface is based on inertial sensors in order to characterize involuntary motion in terms of time, frequency and range of motion. This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction. This paper presents a robust Kalman filter (RKF) design to facilitate fine motor control based on the previous characterization. The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten. The interface is validated with CP users who were unable to control the computer using other interfaces. The interface ENLAZA and the RKF enabled them to use the computer.
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Parálisis Cerebral/fisiopatología , Adulto , Algoritmos , Humanos , Programas Informáticos , Interfaz Usuario-ComputadorRESUMEN
BACKGROUND: The advances in technology make possible the incorporation of sensors and actuators in rollators, building safer robots and extending the use of walkers to a more diverse population. This paper presents a new method for the extraction of navigation related components from upper-body force interaction data in walker assisted gait. A filtering architecture is designed to cancel: (i) the high-frequency noise caused by vibrations on the walker's structure due to irregularities on the terrain or walker's wheels and (ii) the cadence related force components caused by user's trunk oscillations during gait. As a result, a third component related to user's navigation commands is distinguished. RESULTS: For the cancelation of high-frequency noise, a Benedict-Bordner g-h filter was designed presenting very low values for Kinematic Tracking Error ((2.035 +/- 0.358).10(-2) kgf) and delay ((1.897 +/- 0.3697).10(1)ms). A Fourier Linear Combiner filtering architecture was implemented for the adaptive attenuation of about 80% of the cadence related components' energy from force data. This was done without compromising the information contained in the frequencies close to such notch filters. CONCLUSIONS: The presented methodology offers an effective cancelation of the undesired components from force data, allowing the system to extract in real-time voluntary user's navigation commands. Based on this real-time identification of voluntary user's commands, a classical approach to the control architecture of the robotic walker is being developed, in order to obtain stable and safe user assisted locomotion.
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Marcha , Robótica/métodos , Andadores , Algoritmos , Fenómenos Biomecánicos , Reproducibilidad de los Resultados , Interfaz Usuario-ComputadorRESUMEN
There is a need to conceptualize and improve the investigation and developments in assistive devices, focusing on the design and effectiveness of walkers in the user's rehabilitation process and functional compensation. This review surveys the importance of smart walkers in maintaining mobility and discusses their potential in rehabilitation and their demands as assistive devices. It also presents related research in addressing and quantifying the smart walker's efficiency and influence on gait. Besides, it discusses smart walkers focusing on studies related to the concept of autonomous and shared-control and manual guidance, the use of smart walkers as personal helpers to sit-to-stand and diagnostic tools for patients' rehabilitation through the evaluation of their gait.
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Computadores , Andadores , Humanos , Trastornos del Movimiento/diagnóstico , Trastornos del Movimiento/rehabilitaciónRESUMEN
Traveling wave ultrasonic motors (TWUM) are a promising type of piezoelectric transducers, which are based on the friction transmission of mechanical propagating waves. These waves are excited on the stator by using high Q piezoelectric ceramics. This article presents a modeling strategy, which allows for a quick and precise modal and forced analysis of the stator of TWUM. First-order shear deformation laminated plate theory is applied to annular subdomains (super-elements) of the stator. In addition to shear deformations, the model takes into account the effect of rotary inertia, the stiffness contribution of the teeth, and the linear varying thickness of the stator. Moreover, the formulation considers a more realistic function for the electric field inside the piezoelectric ceramic, i.e., a linear function, instead of the generally assumed constant electric field. The Ritz method is used to find an approximated solution for the dynamic equations. Finally, the modal response is obtained and compared against the results from classical simplified models and the finite element method. Thus, the high accuracy and short computation times of the novel strategy were demonstrated.
RESUMEN
Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach.
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Algoritmos , Deambulación Dependiente/fisiología , Marcha/fisiología , Máquina de Vectores de Soporte , Andadores , Adulto , Fenómenos Biomecánicos , Biología Computacional , Deambulación Dependiente/estadística & datos numéricos , Humanos , Modelos Biológicos , Rehabilitación/instrumentación , Rehabilitación/estadística & datos numéricos , Grabación en Video , Adulto JovenRESUMEN
A neurobot (NR) is a mechatronic wearable robot that can be applied to drive a paralyzed limb. Through the application of controllable forces, a NR can assist, replace, or retrain a certain motor function. Robotic intervention in rehabilitation of motor disorders has a potential to improve traditional therapeutic interventions. Because of its flexibility, repeatability and quantifiability, NRs have been more and more applied in neurorehabilitation. Furthermore, combination of NRs with functional electrical stimulation/therapy constitutes a trend to overcome a number of practical limitations to widespread the application of NRs in clinical settings and motor control studies. In this review, we examine the motor learning principles, robotic control approaches and novel developments from studies with NRs and hybrid systems, with a focus on rehabilitation of the lower limbs.
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Extremidad Inferior/fisiopatología , Paresia/rehabilitación , Robótica/métodos , Biorretroalimentación Psicológica/métodos , Marcha/fisiología , Humanos , Enfermedades del Sistema Nervioso/complicaciones , Enfermedades del Sistema Nervioso/rehabilitación , Paresia/etiología , Paresia/fisiopatología , Modalidades de Fisioterapia/instrumentación , Robótica/instrumentaciónAsunto(s)
Inteligencia Artificial , Personas con Discapacidad/rehabilitación , Trastornos del Movimiento/rehabilitación , Robótica/instrumentación , Terapia Asistida por Computador/instrumentación , Interfaz Usuario-Computador , Silla de Ruedas , Niño , Diseño de Equipo , Análisis de Falla de Equipo , Humanos , Robótica/métodos , Terapia Asistida por Computador/métodosRESUMEN
INTRODUCTION:This study investigates a gait research protocol to assess the impact of a walker model with forearm supports on the kinematic parameters of the lower limb during locomotion. METHODS: Thirteen healthy participants without any history of gait dysfunction were enrolled in the experimental procedure. Spatiotemporal and kinematic gait parameters were calculated by using wireless inertial sensors and analyzed with Principal Component Analysis (PCA). The PCA method was selected to achieve dimension reduction and evaluate the main effects in gait performance during walker-assisted gait. Additionally, the interaction among the variables included in each Principal Component (PCs) derived from PCA is exposed to expand the understanding of the main differences between walker-assisted and unassisted gait conditions. RESULTS:The results of the statistical analysis identified four PCs that retained 65% of the data variability. These components were associated with spatiotemporal information, knee joint, hip joint and ankle joint motion, respectively. CONCLUSION: Assisted gait by a walker model with forearm supports was characterized by slower gait, shorter steps, larger double support phase and lower body vertical acceleration when compared with normal, unassisted walking.