In an ageing society, we expect that a robotic caregiver is able to persuade the elderly to perform a healthier behavior. In this work, pragmatic argument is adopted to make the elderly realize that a choice beneficial for health is really worthwhile, such as eating suitable fruits. Based on this concept, an adaptive recommendation dialogue system through pragmatic argumentation is proposed. There are three objectives in this system. First, a knowledge base for pragmatic argument construction is built, which concerns not only the effect of a decision but also the reason for the effect. Secondly, the robot is endowed with the ability to do recommendation that adapts to different states of the elder, and the recommendation is determined based on the integration of both the robot's and the elder's preference for different perspectives so that the robot knows how to reach a compromise with the elder. Lastly, through learning about the elder's preference for perspectives in conversation, the robot will try to select such a perspective to construct arguments that the elder can be more easily convinced to accept its recommendation. We invited 21 volunteers to interact with the robot. The experimental result has proved that the recommendation system has potential to affect the decision making of the elderly and help him/her pursue a healthier life.

In this paper, we propose a sensory cues guided robotic walker for improving gaits of Parkinson Disease (PD) patients. A completely non-intrusive, 3D real-time leg pose tracking and gait analysis are proposed by using a depth camera mounted on the rear of the robotic walker. It has been studied that the sensory cues can serve as effective stimuli to the PD patients for gait improvement. In our work, the sensory cues including visual and auditory cues are incorporated into the robotic walker. More specifically, both sensory cues are gait-adaptive, of which the visual cue in particular is projected onto the ground by a projector installed on the walker, in order to stimulate patients walking gait more easily. Since the adjustable cues can improve patients gaits and reduce their uncomfortableness simultaneously, the hereby developed robotic walker serves as a gait rehabilitation mechanism. To demonstrate the performance of the developed walker, several real experiments have been conducted. First, the accuracy of the proposed 3D leg pose tracking is verified by a standard motion capture system. Next, seven participants (4PD patients and 3 healthy elders) are recruited to test the system three days for verifying the effectiveness of participants gait improvement. The experimental results confirm the potential of the walker serving as a rehabilitation device for PD patients. Note to Practitioners-We proposed a completely non-intrusive, relatively inexpensive and real-time gait analyzer integrated with sensory cues guided rehabilitation system on an active robotic walker. Our goal is to provide a smart robotic walker with safety, reliability, and with rehabilitation function for elders whoever suffered from chronic disease or health problem. In this work, a reliable 3D leg pose tracking is proposed. Then, a gait analysis for acquiring spatio-temporal gait parameters such as stride length and gait velocity is proposed based on the tracking to analyze the walking gait of the patients. On the other hand, improving Parkinson disease patients gaits by using sensory cues which are known to have remarkable effects for Parkinson disease patients is in many research. Therefore, we concentrate on the sensory cues include visual cue and a rhythmic auditory cue cooperating with the robotic walker which aimed to stimulate and provide walkingassistance in their ambulation. For the sensory cues, an adaptive gait mechanism is proposed to improve patients gait based on their personal gait pattern as well as to reduce uncomfortableness of them by doing the rehabilitation. The experimental results confirm the potential of the walker serving as a rehabilitation device for Parkinson disease patients. We hope the new invention of this kind assistive robotic walker will become more popular and may provide more living aid facilities to elders.

In this paper, we propose a gait tracking and analysis method using a depth image sensor installed on robotic walker. Nowadays, robotic walker not only can assist elders who have suffered deteriorating mobility but also help to provide rehabilitating function to people who have crippled walking ability. This approach is meant to be sufficiently accurate, non-intrusive, and low-cost. The goal of this research is to enable the robotic walker to become more active in terms of walker control and comfortable user experiences thorough gait analysis. In experiment, the accuracy of the proposed 3D leg pose tracking method was evaluated by a motion capture system and the result is quite promising. After actual trials, the proposed method has the potential to be used in a safer and more reliable application such as those assisting elders and specific group of patient subjects.