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Biomechanics And Motor Control Of Human Movement

An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Intelligent Automated Assistant

A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

Using context information to facilitate processing of commands in a virtual assistant

Among other things, techniques and systems are disclosed for implementing contextual voice commands. On a device, a data item in a first context is displayed. On the device, a physical input selecting the displayed data item in the first context is received. On the device, a voice input that relates the selected data item to an operation in a second context is received. The operation is performed on the selected data item in the second context.

Contextual voice commands

An electronic device may capture a voice command from a user. The electronic device may store contextual information about the state of the electronic device when the voice command is received. The electronic device may transmit the voice command and the contextual information to computing equipment such as a desktop computer or a remote server. The computing equipment may perform a speech recognition operation on the voice command and may process the contextual information. The computing equipment may respond to the voice command. The computing equipment may also transmit information to the electronic device that allows the electronic device to respond to the voice command.

Electronic Devices with Voice Command and Contextual Data Processing Capabilities

A dialogue system and a method for the same are disclosed. The dialogue system includes a multimodal input unit receiving speech and non-speech information of a user, a domain reasoner, which stores a plurality of pre-stored situations, each of which is formed by a combination one or more speech and non-speech information, calculating each adaptability of the pre-stored situations on the basis of a generated situation based on the speech and the non-speech information received from the multimodal input unit, and determining a current domain according to the calculated adaptability, a dialogue manager to select a response corresponding to the current domain, and a multimodal output unit to output the response. The dialogue system performs domain reasoning using a situation including information combinations reflected in the domain reasoning process, current information, and a speech recognition result, and reduces the size of a dialogue search space while increasing domain reasoning accuracy.

Dialogue system and dialogue method thereof

An interactive robot may audibly communicate with a user, determine whether reasoning is performed according to a reasoning weight of a schedule if there is a schedule to be recommended by the interactive robot during conversation between the interactive robot and the user, perform reasoning using information collected in a database if reasoning is necessary, and provide schedule information to the user.

Schedule management system using interactive robot and method and computer-readable medium thereof

In this paper, we propose a novel online gait task recognition algorithm for hip exoskeleton. The proposed algorithm provides an automatic and prompt recognition result in just one step based on the relations between both hip joint angles at the moment of foot contact. Gait task recognition is one of the challenges that walking assist devices must address to offer adaptable and reliable assistance to users. However gait task recognition in hip exoskeleton is challenging because the sensors are very limited and fast gait task recognition is required to prevent inadequate assistance and reduce fall risk. Although in general foot contact event can be considered as crucial information during walking, it has not received attention in hip exoskeletons with no sensors corresponding foot force or pressure. In this study, we exploit foot contact event as a critical point to perform gait task recognition in hip exoskeleton. The proposed algorithm suggests a foot contact estimation method without using any foot force or pressure sensors and a rule-based inference system to recognize a new gait task in real time. Results presented from experiments will demonstrate the validity and performance of the proposed algorithm.

Online gait task recognition algorithm for hip exoskeleton

In this paper, we propose a new and simple control strategy for gait assistance with a hip exoskeleton robot. This controller is based on the time delayed, self-feedback known for stabilizing oscillatory systems under certain conditions. In this controller, there are no separate estimators for the gait phase nor the environment, yet the controller can be generalized to operate under various walking conditions (e.g., stair and ramp walking). We first define a state variable representing the current leg's movement with hip joint angles. A simple assistance control can be described in closed-loop form with the delayed state feedback. By assigning the appropriate time-delay and self-feedback gain, we can generate assistive torques stably under the interaction between human and exoskeleton. The controller provides immediate and smooth assistance to user movement by reflecting the change of leg motion at every control period. The proposed joint-angle-based delayed-feedback assistance controller can operate under various walking speeds and environmental changes (e.g., stairs and ramps) without the need for additional sensors, computational processing, and parameter adjustment. Using a simple leg swing model, we perform a stability analysis under a simplified condition to provide insights into the effects of the time-delayed feedback in oscillatory systems. Then, we experimentally validate the efficacy of the proposed assistance controller by measuring the metabolic energy expenditure for level treadmill walking. We also test and analyze the generated assistive torques and power under the different walking conditions to show the generalizability of the controller.

Delayed Output Feedback Control for Gait Assistance With a Robotic Hip Exoskeleton

There are many important factors in developing an exoskeleton for assisting human locomotion. For example, the weight should be sufficiently light, the assist torque should be high enough to assist joint motion, and the assistance timing should be just right. Understanding how these design parameters affect overall performance of a complex human-machine system is critical for the development of these types of systems. The present study introduces an assistance timing controller that regulates assistance timing such that peak joint velocity and peak assistance power are offset by a reference value for our hip-type exoskeleton. This is followed by measuring the manner in which various assistance timing references affect an important metric for performance, namely metabolic cost. The results indicate that net metabolic cost exhibits a concave up pattern with the most reduction of 21%, when compared to walking without the exoskeleton, at 0% assistance timing reference. The study also examines assistance timing's effect on gait parameters; increase in assistance timing reference increases step length, decreases cadence, and increases walk ratio (i.e. step length/cadence ratio) during treadmill walking.

Junwon Jang

Papers

Dialogue system and dialogue method thereof

Schedule management system using interactive robot and method and computer-readable medium thereof

Online gait task recognition algorithm for hip exoskeleton

Delayed Output Feedback Control for Gait Assistance With a Robotic Hip Exoskeleton

Effects of assistance timing on metabolic cost, assistance power, and gait parameters for a hip-type exoskeleton