RESUMEN
The merging of the human world and the information technology world is advancing at a pace, even for those with dementia there are many useful smart 'phone applications including reminders, family pictures display, GPS functions and video communications. This paper will report upon initial collaborative work developing a robotic solution to engaging individuals with advancing dementia in safe exercise regimes. The research team has been driven by the needs of people with advancing dementia and their carers through a focus group methodology, the format, discussions and outcomes of these groups will be reported. The plans for the next stage of the research will be outlined including the continuing collaboration with advancing dementia and their carers.
Asunto(s)
Demencia/rehabilitación , Terapia por Ejercicio/métodos , Sistemas Hombre-Máquina , Seguridad del Paciente , Robótica/métodos , Terapia Asistida por Computador/métodos , Demencia/diagnóstico , Diseño de Equipo , Análisis de Falla de Equipo , Terapia por Ejercicio/instrumentación , Humanos , Robótica/instrumentación , Terapia Asistida por Computador/instrumentación , Resultado del TratamientoRESUMEN
This paper presents salient features of human-human interaction where one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several salient features of the interaction between the guider and follower such as: 1) the order of an autoregressive (AR) control policy that maps states of the follower to actions of the guider; 2) how the guider may modulate the pulling force in response to the trust level of the follower; and 3) how learning may successively apportion the responsibility of control across different muscles of the guider. Based on experimental systems identification on human demonstrations from ten pairs of naive subjects, we show that guiders tend to adopt a third-order AR predictive control policy and followers tend to adopt second-order reactive control policy. Moreover, the extracted guider's control policy was implemented and validated by human-robot interaction experiments. By modeling the follower's dynamics with a time varying virtual damped inertial system, we found that it is the coefficient of virtual damping which is most sensitive to the trust level of the follower. We used these experimental insights to derive a novel controller that integrates an optimal order control policy with a push/pull force modulator in response to the trust level of the follower monitored using a time varying virtual damped inertial model.