Archive for Ноябрь 12th, 2003
Development and Testing of a Haptic Interface to Assist and Improve the Manipulation Functions in Virtual Environments for Persons with Disabilities
- Тип контента: Научная статья
- Номер документа: 7658
- Название документа: Development and Testing of a Haptic Interface to Assist and Improve the Manipulation Functions in Virtual Environments for Persons with Disabilities
- Номер (DOI, IBSN, Патент): Не заполнено
- Изобретатель/автор: Rohit Tammana
- Правопреемник/учебное заведение: Department of Mechanical Engineering College of Engineering University of South Florida
- Дата публикации документа: 2003-11-12
- Страна опубликовавшая документ: США
- Язык документа: Английский
- Наименование изделия: Не заполнено
- Источник: Не заполнено
- Вложения: Да
- Аналитик: Глаголева Елена
Robotics in rehabilitation provides considerable opportunities to improve the quality of life for persons with disabilities. Computerized and Virtual Environment (VE) training systems for persons with disabilities, many of which utilize the haptic feedback, have gained increasing acceptance in the recent years. Our methodology here is based on creating virtual environments connected to a haptic interface as an input device. This robotic setup introduces the advantages of the haptic rendering features in the environment and also provides tactile feedback to the patients. This thesis aims to demonstrate the efficacy of assistance function algorithms in rehabilitation robotics in virtual environments. Assist functions are used to map limited human input to motions required to perform complex tasks. The purpose is to train individuals in task-oriented applications to insure that they can be incorporated into the workplace. Further, Hidden Markov Model (HMM) based motion recognition and skill learning are used for improving the skill levels of the users. For the Hidden Markov Model based motion recognition, the user’s motion intention is combined with environment information to apply an appropriate assistance function. We used this algorithm to perform a commonly used vocational therapy test referred to as the box and the blocks test. The Hidden Markov Model based skill approach can be used for learning human skill and transferring the skill to persons with disabilities. A relatively complex task of moving along a labyrinth is chosen as the task to be modeled by HMM. This kind of training allows a person with disability to learn the skill and improve it through practice. Its application to motion therapy system using a haptic interface helps in improving their motion control capabilities, tremor reduction and upper limb coordination. The results obtained from all the tests demonstrated that various forms of assistance provided reduced the execution times and increased the motion performance in chosen tasks. Two persons with disabilities volunteered to perform the above tasks and both of the disabled subjects expressed an interest and satisfaction with the philosophy behind these concepts.
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