Cristian Tapus

User-Robot Personality Matching and Assistive Robot Behavior Adaptation for Post-Stroke Rehabilitation Therapy

This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance.

The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia

Currently the 2 percent growth rate for the worlds older population exceeds the 1.2 rate for the worlds population as a whole. By 2050, the number of individuals over the age 85 is projected to be three times more than there is today. Most of these individuals will need physical, emotional, and cognitive assistance. In this paper, we present a new adaptive robotic system based on the socially assistive robotics (SAR) technology that tries to provide a customized help protocol through motivation, encouragements, and companionship to users suffering from cognitive changes related to aging and/or Alzheimers disease. Our results show that this approach can engage the patients and keep them interested in interacting with the robot, which, in turn, increases their positive behavior.

The role of physical embodiment of a therapist robot for individuals with cognitive impairments

This research focuses on studying the possible role of a socially interactive robot as a tool for monitoring and encouraging cognitive activities of the elderly and/or individuals suffering from dementia. One of the aims of this work is to show the benefits of the robots physical embodiment in human-robot social interactions. The social therapist robot tries to provide customized cognitive stimulation by playing a music game with the user. The results of the 8-month pilot study depict a more efficient, natural, and preferred interaction with the robot rather than with the simulated robot.

Hands-Off Therapist Robot Behavior Adaptation to User Personality for Post-Stroke Rehabilitation Therapy

This paper describes a hands-off therapist robot that monitors, assists, encourages, and socially interacts with post-stroke users in the process of rehabilitation exercises. We developed a behavior adaptation system that takes advantage of the users introversion-extroversion personality trait and the number of exercises performed in order to adjust its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward a customized post-stroke rehabilitation therapy. The experimental results demonstrate the robots autonomous behavior adaptation to the users personality and the resulting user improvements of the exercise task performance.

Long Term Learning and Online Robot Behavior Adaptation for Individuals with Physical and Cognitive Impairments

In this paper, we present an online adaptation approach and a long-term learning approach for socially assistive robotic (SAR) systems that aim to provide customized help protocols through motivation, encouragements, and companionship to users suffering from physical and/or cognitive changes related to stroke, aging and Alzheimer’s disease.

Kernel level speculative DSM

Interprocess communication (IPC) is ubiquitous in todays computing world. One of the simplest mechanisms for IPC is shared memory. We present a system that enhances the System V IPC API to support distributed shared memory (DSM) by using speculations. Speculations provide performance improvements by enabling rollback of overly optimistic speculative executions. This paper describes a speculative total order communication protocol, a speculative sequential consistency model, and a speculative distributed locking mechanism. All these are supported by a mathematical model showing the advantages of speculative execution over traditional execution. Our DSM system is part of the Mojave system, which consists of a compiler and the extensions of the operating system designed to support speculations and process migration. The goal of our system is to provide a simpler programming paradigm for designers of distributed systems.

Music therapist robot for individuals with cognitive impairments

Currently the 2 percent growth rate for the worlds older population exceeds the 1.2 percent rate for the worlds population as a whole. This difference is expected to increase rather than diminish so that by 2050, the number of individuals over the age 85 is projected to be three times what it is today. Most of these individuals will need physical, emotional, and cognitive assistance. In this paper, we present a new system based on the socially assistive robotics (SAR) technology that will play the role of a music therapist and will try to provide a customized help protocol through motivation, encouragements, and companionship to users suffering from cognitive changes related to aging and/or Alzheimers disease.

Music Therapist Robot for People Suffering from Dementia: Longitudinal Study

Background: The recent trend toward developing a new generation of robots capable of operating in human-centered environments, interacting with people, and participating in and assisting our daily lives has introduced the need for robotic systems capable of learning to use their embodiment to communicate and to react to their users in a social and engaging way. Social robots that interact with humans have thus become an important focus of robotics research. The scientific literature shows that activities, such as music therapy, can help individuals with dementia and cognitive impairment maintain their functional abilities and can enhance quality of life. Very few researches have been done in the area of therapeutic robots for individuals suffering from dementia and cognitive impairment. Methods: This work aims to validate that a robotic system can establish a productive interaction with the user, and can serve to motivate and remind the user about specific tasks/cognitive exercises.

The Mojave Compiler: Providing Language Primitives for Whole-Process Migration and Speculation for Distributed Applications

We present an approach for implementing language-level primitives for whole-process migration and speculative execution in a compiler and associated runtime environment. These primitives are exposed to the user through simple language constructs that do not require the user to manage process state explicitly. With migration and speculation we show how the user can quickly add persistent checkpoints to any large-scale distributed application that requires longevity in a faulty environment. We demonstrate the use of migration and speculation primitives for checkpointing in a canonical grid computation application, and analyze the results of this implementation.

FixD : Fault Detection, Bug Reporting, and Recoverability for Distributed Applications

Model checking, logging, debugging, and checkpointing/recovery are great tools to identify bugs in small sequential programs. The direct application of these techniques to the domain of distributed applications, however, has been less effective (mostly owing to the high degree of concurrency in this context). This paper presents the design of a hybrid tool, FixD, that attempts to address the deficiencies of these tools with respect to their application to distributed systems by using a novel composition of several of these existing techniques. The authors first identify and describe the four abstract components that comprise the FixD tool, then conclude with a proposal for how existing tools can be used to implement these components.