J Neuroeng Rehabil
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Recent smartphones, such as the iPhone, are often equipped with an accelerometer and magnetometer, which, through software applications, can perform various inclinometric functions. Although these applications are intended for recreational use, they have the potential to measure and quantify range of motion. The purpose of this study was to estimate the intra and inter-rater reliability as well as the criterion validity of the clinometer and compass applications of the iPhone in the assessment cervical range of motion in healthy participants. ⋯ We found good intra-rater reliability and lower inter-rater reliability. When compared to the gold standard, these applications showed moderate to good validity. However, before using the iPhone as an outcome measure in clinical settings, studies should be done on patients presenting with cervical problems.
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Robot-assisted gait training and treadmill training can complement conventional physical therapy in children with neuro-orthopedic movement disorders. The aim of this study was to investigate surface electromyography (sEMG) activity patterns during robot-assisted gait training (with and without motivating instructions from a therapist) and unassisted treadmill walking and to compare these with physiological sEMG patterns. ⋯ Our results suggest that robotic-assisted gait training with therapeutic encouragement could appropriately increase muscle activity. Robotic-assisted gait training in general could induce physiological muscle activation patterns, which might indicate that this training exploits restorative rather than compensatory mechanisms.
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Stimulation of the spinal cord has been shown to have great potential for improving function after motor deficits caused by injury or pathological conditions. Using a wide range of animal models, many studies have shown that stimulation applied to the neural networks intrinsic to the spinal cord can result in a dramatic improvement of motor ability, even allowing an animal to step and stand after a complete spinal cord transection. Clinical use of this technology, however, has been slow to develop due to the invasive nature of the implantation procedures, the lack of versatility in conventional stimulation technology, and the difficulty of ascertaining specific sites of stimulation that would provide optimal amelioration of the motor deficits. Moreover, the development of tools available to control precise stimulation chronically via biocompatible electrodes has been limited. In this paper, we outline the development of this technology and its use in the spinal rat model, demonstrating the ability to identify and stimulate specific sites of the spinal cord to produce discrete motor behaviors in spinal rats using this array. ⋯ Therefore the high density electrode array allows high spatial resolution and the ability to selectively activate different neural pathways within the lumbosacral region of the spinal cord to facilitate standing and stepping in adult spinal rats and provides the capability to evoke motor potentials and thus a means for assessing connectivity between sensory circuits and specific motor pools and muscles.
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Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. ⋯ The performance of EMG pattern-recognition based method in classifying movements strongly depends on arm positions. This dependency is a little stronger in intact arm than in amputated arm, which suggests that the investigations associated with practical use of a myoelectric prosthesis should use the limb amputees as subjects instead of using able-body subjects. The two-stage cascade classifier mode with ACC-MMG for limb position identification and EMG for limb motion classification may be a promising way to reduce the effect of limb position variation on classification performance.
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Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance cognitive engagement for more effective gait rehabilitation and greater transfer to over ground walking. For this purpose, we developed an individualized treadmill controller with a novel speed estimation scheme using swing foot velocity, which can enable user-driven treadmill walking (UDW) to more closely simulate over ground walking (OGW) during treadmill training. OGW involves a cyclic acceleration-deceleration profile of pelvic velocity that contrasts with typical treadmill-driven walking (TDW), which constrains a person to walk at a preset constant speed. In this study, we investigated the effects of the proposed speed adaptation controller by analyzing the gait kinematics of UDW and TDW, which were compared to those of OGW at three pre-determined velocities. ⋯ Our treadmill control scheme implements similar gait biomechanics of TDW, which has been used for repetitive gait training in a small and constrained space as well as controlled and safe environments. These results reveal that users can walk as stably during UDW as TDW and employ similar strategies to maintain walking speed in both UDW and TDW. Furthermore, since UDW can allow a user to actively participate in the virtual reality (VR) applications with variable walking velocity, it can induce more cognitive activities during the training with VR, which may enhance motor learning effects.