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Pattern recognition algorithms have been used to control powered lower limb prostheses because they are capable of identifying the intent of the amputee user and therefore can provide a method for seamlessly transitioning between the different locomotion modes of the prosthesis. However, one major limitation of current algorithms is that they require subject-specific data from the individual user...
Powered prosthetic legs are capable of improving the gait of lower limb amputees. Pattern recognition systems for these devices allow amputees to transition between different locomotion modes in a way that is seamless and transparent to the user. However, the potential of these systems is diminished because they require large amounts of training data that is burdensome to collect. To reduce the effort...
Powered knee and ankle prostheses have the potential to improve the mobility of individuals with a lower limb amputation. As the number of different ambulation modes the prosthesis can be configured for increases, so too does the challenge of how to best transition the prosthesis between these modes. Pattern recognition systems have been suggested as a means to provide seamless and natural transitions,...
Recently developed motorized lower limb prostheses which provide joint power at the knee and/or ankle have been shown to assist users in performing a variety of ambulation tasks. Control of these devices, specifically creating seamless, natural, and accurate mode transitions, is challenging. The control system also needs to allow users the flexibility to perform these tasks with a wide range of variability...
Real-time simultaneous pattern recognition (PR) control of multiple degrees of freedom (DOF) has been demonstrated using a set of parallel linear discriminant analysis (LDA) classifiers trained with both discrete (1-DOF) and simultaneous (2-DOF) motion data. However, this training method presents a clinical challenge, requiring large amounts of data necessary to re-train the system. This study presents...
Powered lower limb prostheses can improve amputees' ability to traverse stairs and ramps by providing positive mechanical work at the knee and ankle joint. EMG signals have been proposed as one way of providing seamless mode transitions by using them in combination with embedded mechanical sensors as inputs to a pattern recognition system that predicts the user's desired locomotion mode. In this study,...
Recently developed powered prostheses are capable of producing near-physiological joint torque at the knee and/or ankle joints. Based on previous studies of biological joint impedance and the mechanics of able-bodied gait, an impedance-based controller has been developed for a powered knee and ankle prosthesis that integrates knee swing initiation and powered plantar flexion in late stance with increasing...
Falls are a large concern for individuals with lower limb amputations. Advanced powered prosthetic devices have the potential to quickly intervene after perturbations and help avoid a fall, but active balance recovery mechanisms have yet to be implemented. We investigated the feasibility of a realtime pattern recognition system for identification of trip recovery strategies. We tripped able-bodied...
Intent recognition systems using pattern recognition technology to control powered lower-limb prostheses are promising for seamlessly changing between locomotion modes — such as transitioning from level walking to stair ascent. These transitions can be accomplished by training an algorithm to recognize the patterns of mechanical and/or myoelectric signals an amputee generates during and between different...
Lower limb prostheses that can generate near physiological joint power have the potential to improve the way amputees go about their activities of daily living. Amputees who have lost both their knee and ankle would also benefit from a system that allowed them to easily perform sit-to-stand and stand-to-sit movements, reposition their prosthesis using neural control, and intuitively transition between...
Pattern recognition myoelectric control shows great promise as an alternative to conventional amplitude based control to control multiple degree of freedom prosthetic limbs. Many studies have reported pattern recognition classification error performances of less than 10% during offline tests; however, it remains unclear how this translates to real-time control performance. In this contribution, we...
Recently developed powered lower limb prostheses allow users to more closely mimic the kinematics and kinetics of non-amputee gait. However, configuring such a device, in particular a combined powered knee and ankle, for individuals with a transfemoral amputation is challenging. Previous attempts have relied on empirical tuning of all control parameters. This paper describes modified stance phase...
Pattern recognition can provide intuitive control of myoelectric prostheses. Currently, screen-guided training (SGT), in which individuals perform specific muscle contractions in sync with prompts displayed on a screen, is the common method of collecting the electromyography (EMG) data necessary to train a pattern recognition classifier. Prosthesis-guided training (PGT) is a new data collection method...
In control subjects, trips during the early and late swing phase of walking elicit elevating and lowering strategies, respectively. However, the transition between these recovery strategies during mid-swing is unclear. A better understanding of this transition would provide insight into what factors cause individuals to choose one strategy over another. Three control subjects walked on a treadmill...
Movement misclassifications often occur during real-time pattern recognition control. Majority vote and a decision-based velocity ramp are two different post-processing methods that have been suggested to improve real-time control. With majority vote, spurious misclassifications are removed at the expense of an additional controller delay. With a decision-based velocity ramp, the effect of misclassifications...
Few studies have focused on proportional control with multi-channel electromyographic (EMG) pattern recognition systems. In a simple proportional control algorithm, movement speed is often calculated by averaging the mean absolute values of all EMG channels. The aim of our study was to compare the performance of two types of pattern recognition control (simple proportional and binary on/off) to direct...
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