Exploring the bases for a mixed reality stroke rehabilitation system, Part I: A unified approach for representing action, quantitative evaluation, and interactive feedback

<p>Abstract</p> <p>Background</p> <p>Although principles based in motor learning, rehabilitation, and human-computer interfaces can guide the design of effective interactive systems for rehabilitation, a unified approach that connects these key principles into an integrated design, and can form a methodology that can be generalized to interactive stroke rehabilitation, is presently unavailable.</p> <p>Results</p> <p>This paper integrates phenomenological approaches to interaction and embodied knowledge with rehabilitation practices and theories to achieve the basis for a methodology that can support effective adaptive, interactive rehabilitation. Our resulting methodology provides guidelines for the development of an action representation, quantification of action, and the design of interactive feedback. As Part I of a two-part series, this paper presents key principles of the unified approach. Part II then describes the application of this approach within the implementation of the Adaptive Mixed Reality Rehabilitation (AMRR) system for stroke rehabilitation.</p> <p>Conclusions</p> <p>The accompanying principles for composing novel mixed reality environments for stroke rehabilitation can advance the design and implementation of effective mixed reality systems for the clinical setting, and ultimately be adapted for home-based application. They furthermore can be applied to other rehabilitation needs beyond stroke.</p

Multimodal archiving, real-time annotation and information visualization in a biofeedback system for stroke patient rehabilitation

In this paper we present our work on a system to support real-time multimodal archiving, collaborative annotation and offline information visualization for a biofeedback stroke-rehabilitation application. Our archiving / annotation / visualization system can play a critical role in the long-term biofeedback stroke therapy by supporting cooperative data analysis and media feedback as well as by providing the therapist with insight into computingsupported therapy. There are three contributions of this paper: (a) the design of a robust archiving system that archives in real time parametric model data (motion capture, motion analysis and audio / visual synthesis parameters) as well as audio / video from the biofeedback environment. (b) a web-based annotation tool designed with low cognitive load (c) a hierarchical information visualization tool that enables the therapist and other team members to examine quantitative motion analysis of subject performance with the context of media feedback, thus enabling collaborative insights. Our user studies indicate that the system performs well

Interactive rehabilitation and dynamical analysis of scalp EEG

Electroencephalography (EEG) has been used for decades to measure the brain\u27s electrical activity. Planning and performing a complex movement (e.g., reaching and grasping) requires the coordination of muscles by electrical activity that can be recorded with scalp EEG from relevant regions of the cortex. Prior studies, utilizing motion capture and kinematic measures, have shown that an augmented reality feedback system for rehabilitation of stroke patients can help patients develop new motor plans and perform reaching tasks more accurately. Historically, traditional signal analysis techniques have been utilized to quantify changes in EEG when subjects perform common, simple movements. These techniques have included measures of event-related potentials in the time and frequency domains (e.g., energy and coherence measures). In this study, a more advanced, nonlinear, analysis technique, mutual information (MI), is applied to the EEG to capture the dynamics of functional connections between brain sites. In particular, the cortical activity that results from the planning and execution of novel reach trajectories by normal subjects in an augmented reality system was quantified by using statistically significant MI interactions between brain sites over time. The results show that, during the preparation for as well as the execution of a reach, the functional connectivity of the brain changes in a consistent manner over time, in terms of both the number and strength of cortical connections. A similar analysis of EEG from stroke patients may provide new insights into the functional deficiencies developed in the brain after stroke, and contribute to evaluation, and possibly the design, of novel therapeutic schemes within the framework of rehabilitation and BMI (brain machine interface)

An auditory display system for aiding interjoint coordination

Presented of the 6th International Conference on Auditory Display (ICAD), Atlanta, GA, April 2-5, 2000Patients with lack of proprioception are unable to build and maintain `internal models' of their limbs and monitor their limb movements because these patients do not receive the appropriate information from muscles and joints. This project was undertaken to determine if auditory signals can provide proprioceptive information normally obtained through muscle and joint receptors. Sonification of spatial location and sonification of joint motion, for monitoring arm/hand motions, was attempted in two pilot experiments with a patient. Sonification of joint motion though strong time/synchronization cues was the most successful approach. These results are encouraging and suggest that auditory feedback of joint motions may be substitute for proprioceptive input. However, additional data will have to be collected and control experiments will have to be done

The Computational Extraction Of Temporal Formal Structures in the Interactive Dance Work ‘22’

In this paper we propose a framework for the computational extraction of time characteristics of a single choreographic work. Computational frameworks can aid in revealing nonsalient compositional structures in modern dance. The computational extraction of such features allows for the creation of interactive works where the movement and the digital feedback (graphics, sound etc) are integrally connected at deep level of structures. It also facilitates a better understanding of the choreographic process. There are two key contributions in this paper: (a) a systematic analysis of the observable and nonsalient aspects of solo dance form, (b) computational analysis of temporal phrasing structures guided by critical understanding of observable form. Our analysis results are excellent indicating the presence of rich, latent temporal organization in specific semi-improvisatory modern dance works that may provide rich structural material for interactivity. Categories and Subject descriptor

Exploring the bases for a mixed reality stroke rehabilitation system, Part II: Design of Interactive Feedback for upper limb rehabilitation

Abstract Background Few existing interactive rehabilitation systems can effectively communicate multiple aspects of movement performance simultaneously, in a manner that appropriately adapts across various training scenarios. In order to address the need for such systems within stroke rehabilitation training, a unified approach for designing interactive systems for upper limb rehabilitation of stroke survivors has been developed and applied for the implementation of an Adaptive Mixed Reality Rehabilitation (AMRR) System. Results The AMRR system provides computational evaluation and multimedia feedback for the upper limb rehabilitation of stroke survivors. A participant's movements are tracked by motion capture technology and evaluated by computational means. The resulting data are used to generate interactive media-based feedback that communicates to the participant detailed, intuitive evaluations of his performance. This article describes how the AMRR system's interactive feedback is designed to address specific movement challenges faced by stroke survivors. Multimedia examples are provided to illustrate each feedback component. Supportive data are provided for three participants of varying impairment levels to demonstrate the system's ability to train both targeted and integrated aspects of movement. Conclusions The AMRR system supports training of multiple movement aspects together or in isolation, within adaptable sequences, through cohesive feedback that is based on formalized compositional design principles. From preliminary analysis of the data, we infer that the system's ability to train multiple foci together or in isolation in adaptable sequences, utilizing appropriately designed feedback, can lead to functional improvement. The evaluation and feedback frameworks established within the AMRR system will be applied to the development of a novel home-based system to provide an engaging yet low-cost extension of training for longer periods of time.</p