Kai-Uwe Schmidt

Telerehabilitation needs: a survey of persons with acquired brain injury.

Objective:To survey individuals with acquired brain injury to assess multiple facets of interest, access, and familiarity necessary to implement new telerehabilitation technologies. Design:Anonymous mail survey. Setting:Community. Participants:Seventy-one respondents to a survey. These individuals had experienced acquired brain injury (predominantly severe traumatic brain injury [TBI]) and were living in the community. Surveys were mailed by a state chapter of the Brain Injury Association to a random selection of members with acquired brain injury. Main Outcome Measure:Survey designed specifically for this investigation. Results:The survey responses indicate that there is great interest in the possibility of accessing telerehabilitative services among individuals with acquired brain injury. In particular, there was strong interest expressed in services that could be used to assist with problems in memory, attention, problem-solving, and activities of daily living. Conclusions:Telemedicine, and more specifically telerehabilitation, holds great promise as an adjunct to traditional clinical service delivery. Little research in this area has been applied, however, to individuals with acquired brain injuries. Although on the surface, telerehabilitation seems to be an appropriate assessment and treatment modality for individuals with brain injury, it will only succeed if those individuals have the interest—and the access—necessary to use new and evolving technologies.

Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System

Probabilistic models such as Bayesian networks [6] are well suited for medical decision support and are the basis of many successful applications [1],[3],[4],[8],[9],[10]. Bayesian networks provide a rigorous and efficient framework for inference, i.e. for calculating the probability of each stochastic variable given a set of observations. However, knowledge acquisition and generation of the network are still demanding tasks when large medical domains have to be modelled.

Siemens Physio Assistant An Integrated Concept for Computer-Supported Orthopedic Rehabilitation

Abstract As an integrated concept for orthopedic rehabilitation, the Siemens Physio Assistant provides the central functions of training, training analysis and therapy progress analysis, as well as information and communication. The components containing these functions are the Training Assistant and the Gait Assistant. The Training Assistant offers patients multi-media real-time training programs and therapists differentiated training analyses. The Gait Assistant enables change of gait to be monitored through the course of the therapeutic process. Data transfer is telematic, so that the Physio Assistant can be used throughout all stages of rehabilitation.