Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by
the user as belonging to their own body. Robotic limbs can convey information about the …

Locomotion assistive devices equipped with a microprocessor can potentially automatically
adapt their behavior when the user is transitioning from one locomotion mode to another …

Algorithms for locomotion mode recognition (LMR) based on surface electromyography and
mechanical sensors have recently been developed and could be used for the neural control …

The lower-limb robotic prostheses can provide assistance for amputees' daily activities by
restoring the biomechanical functions of missing limb (s). To set proper control strategies …

Many people struggle with mobility impairments due to lower limb amputations. To
participate in society, they need to be able to walk on a wide variety of terrains, such as …

Myoelectric pattern recognition is a useful tool for identifying the user's intended motion.
However, the inherent nonstationary properties of Electromyography (EMG) signals usually …

Goal: The purpose of this study was to provide an initial examination of the utility of the Beta
Process-Auto Regressive-Hidden Markov Model (BP-AR-HMM) for the prior identification of …

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 …

Gait-type recognition is important for robotic exoskeletons and walking-assistance devices to
adjust their output according to the users' needs. However, the growing trend of using …

The miniaturization of sensors and their availability for biomechanical analysis outside of the
laboratory has opened whole new areas of research. Wearable sensors have been …